adjusted risk estimates: Topics by Science.gov

Sample records for adjusted risk estimates

A risk adjustment approach to estimating the burden of skin disease in the United States.

PubMed

Lim, Henry W; Collins, Scott A B; Resneck, Jack S; Bolognia, Jean; Hodge, Julie A; Rohrer, Thomas A; Van Beek, Marta J; Margolis, David J; Sober, Arthur J; Weinstock, Martin A; Nerenz, David R; Begolka, Wendy Smith; Moyano, Jose V

2018-01-01

Direct insurance claims tabulation and risk adjustment statistical methods can be used to estimate health care costs associated with various diseases. In this third manuscript derived from the new national Burden of Skin Disease Report from the American Academy of Dermatology, a risk adjustment method that was based on modeling the average annual costs of individuals with or without specific diseases, and specifically tailored for 24 skin disease categories, was used to estimate the economic burden of skin disease. The results were compared with the claims tabulation method used in the first 2 parts of this project. The risk adjustment method estimated the direct health care costs of skin diseases to be $46 billion in 2013, approximately $15 billion less than estimates using claims tabulation. For individual skin diseases, the risk adjustment cost estimates ranged from 11% to 297% of those obtained using claims tabulation for the 10 most costly skin disease categories. Although either method may be used for purposes of estimating the costs of skin disease, the choice of method will affect the end result. These findings serve as an important reference for future discussions about the method chosen in health care payment models to estimate both the cost of skin disease and the potential cost impact of care changes. Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.
Alternative evaluation metrics for risk adjustment methods.

PubMed

Park, Sungchul; Basu, Anirban

2018-06-01

Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk-adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high-expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk-adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013-2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution-based estimators achieve higher group-level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual-level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade-off in selecting an appropriate risk-adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors. Copyright © 2018 John Wiley & Sons, Ltd.
Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus.

PubMed

Cohen, Mark E; Ko, Clifford Y; Bilimoria, Karl Y; Zhou, Lynn; Huffman, Kristopher; Wang, Xue; Liu, Yaoming; Kraemer, Kari; Meng, Xiangju; Merkow, Ryan; Chow, Warren; Matel, Brian; Richards, Karen; Hart, Amy J; Dimick, Justin B; Hall, Bruce L

2013-08-01

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) collects detailed clinical data from participating hospitals using standardized data definitions, analyzes these data, and provides participating hospitals with reports that permit risk-adjusted comparisons with a surgical quality standard. Since its inception, the ACS NSQIP has worked to refine surgical outcomes measurements and enhance statistical methods to improve the reliability and validity of this hospital profiling. From an original focus on controlling for between-hospital differences in patient risk factors with logistic regression, ACS NSQIP has added a variable to better adjust for the complexity and risk profile of surgical procedures (procedure mix adjustment) and stabilized estimates derived from small samples by using a hierarchical model with shrinkage adjustment. New models have been developed focusing on specific surgical procedures (eg, "Procedure Targeted" models), which provide opportunities to incorporate indication and other procedure-specific variables and outcomes to improve risk adjustment. In addition, comparative benchmark reports given to participating hospitals have been expanded considerably to allow more detailed evaluations of performance. Finally, procedures have been developed to estimate surgical risk for individual patients. This article describes the development of, and justification for, these new statistical methods and reporting strategies in ACS NSQIP. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
A demand-side view of risk adjustment.

PubMed

Feldman, R; Dowd, B E; Maciejewski, M

2001-01-01

This paper analyzes the efficient allocation of consumers to health plans. Specifically, we address the question of why employers that offer multiple health plans often make larger contributions to the premiums of the high-cost plans. Our perspective is that the subsidy for high-cost plans represents a form of demand-side risk adjustment that improves efficiency. Without such subsidies (and in the absence of formal risk adjustment), too few employees would choose the high-cost plans preferred by high-risk workers. We test the theory by estimating a model of the employer premium subsidy, using data from a survey of large public employers in 1994. Our empirical analysis shows that employers are more likely to subsidize high-cost plans when the benefits of risk adjustment are greater. The findings suggest that the premium subsidy can accomplish some of the benefits of formal risk adjustment.
Quantifying the impact of time-varying baseline risk adjustment in the self-controlled risk interval design.

PubMed

Li, Lingling; Kulldorff, Martin; Russek-Cohen, Estelle; Kawai, Alison Tse; Hua, Wei

2015-12-01

The self-controlled risk interval design is commonly used to assess the association between an acute exposure and an adverse event of interest, implicitly adjusting for fixed, non-time-varying covariates. Explicit adjustment needs to be made for time-varying covariates, for example, age in young children. It can be performed via either a fixed or random adjustment. The random-adjustment approach can provide valid point and interval estimates but requires access to individual-level data for an unexposed baseline sample. The fixed-adjustment approach does not have this requirement and will provide a valid point estimate but may underestimate the variance. We conducted a comprehensive simulation study to evaluate their performance. We designed the simulation study using empirical data from the Food and Drug Administration-sponsored Mini-Sentinel Post-licensure Rapid Immunization Safety Monitoring Rotavirus Vaccines and Intussusception study in children 5-36.9 weeks of age. The time-varying confounder is age. We considered a variety of design parameters including sample size, relative risk, time-varying baseline risks, and risk interval length. The random-adjustment approach has very good performance in almost all considered settings. The fixed-adjustment approach can be used as a good alternative when the number of events used to estimate the time-varying baseline risks is at least the number of events used to estimate the relative risk, which is almost always the case. We successfully identified settings in which the fixed-adjustment approach can be used as a good alternative and provided guidelines on the selection and implementation of appropriate analyses for the self-controlled risk interval design. Copyright © 2015 John Wiley & Sons, Ltd.
A Machine Learning Framework for Plan Payment Risk Adjustment.

PubMed

Rose, Sherri

2016-12-01

To introduce cross-validation and a nonparametric machine learning framework for plan payment risk adjustment and then assess whether they have the potential to improve risk adjustment. 2011-2012 Truven MarketScan database. We compare the performance of multiple statistical approaches within a broad machine learning framework for estimation of risk adjustment formulas. Total annual expenditure was predicted using age, sex, geography, inpatient diagnoses, and hierarchical condition category variables. The methods included regression, penalized regression, decision trees, neural networks, and an ensemble super learner, all in concert with screening algorithms that reduce the set of variables considered. The performance of these methods was compared based on cross-validated R 2 . Our results indicate that a simplified risk adjustment formula selected via this nonparametric framework maintains much of the efficiency of a traditional larger formula. The ensemble approach also outperformed classical regression and all other algorithms studied. The implementation of cross-validated machine learning techniques provides novel insight into risk adjustment estimation, possibly allowing for a simplified formula, thereby reducing incentives for increased coding intensity as well as the ability of insurers to "game" the system with aggressive diagnostic upcoding. © Health Research and Educational Trust.
A clinical economics workstation for risk-adjusted health care cost management.

PubMed Central

Eisenstein, E. L.; Hales, J. W.

1995-01-01

This paper describes a healthcare cost accounting system which is under development at Duke University Medical Center. Our approach differs from current practice in that this system will dynamically adjust its resource usage estimates to compensate for variations in patient risk levels. This adjustment is made possible by introducing a new cost accounting concept, Risk-Adjusted Quantity (RQ). RQ divides case-level resource usage variances into their risk-based component (resource consumption differences attributable to differences in patient risk levels) and their non-risk-based component (resource consumption differences which cannot be attributed to differences in patient risk levels). Because patient risk level is a factor in estimating resource usage, this system is able to simultaneously address the financial and quality dimensions of case cost management. In effect, cost-effectiveness analysis is incorporated into health care cost management. PMID:8563361
Affordable Care Act risk adjustment: overview, context, and challenges.

PubMed

Kautter, John; Pope, Gregory C; Keenan, Patricia

2014-01-01

Beginning in 2014, individuals and small businesses will be able to purchase private health insurance through competitive marketplaces. The Affordable Care Act (ACA) provides for a program of risk adjustment in the individual and small group markets in 2014 as Marketplaces are implemented and new market reforms take effect. The purpose of risk adjustment is to lessen or eliminate the influence of risk selection on the premiums that plans charge and the incentive for plans to avoid sicker enrollees. This article--the first of three in the Medicare & Medicaid Research Review--describes the key program goal and issues in the Department of Health and Human Services (HHS) developed risk adjustment methodology, and identifies key choices in how the methodology responds to these issues. The goal of the HHS risk adjustment methodology is to compensate health insurance plans for differences in enrollee health mix so that plan premiums reflect differences in scope of coverage and other plan factors, but not differences in health status. The methodology includes a risk adjustment model and a risk transfer formula that together address this program goal as well as three issues specific to ACA risk adjustment: 1) new population; 2) cost and rating factors; and 3) balanced transfers within state/market. The risk adjustment model, described in the second article, estimates differences in health risks taking into account the new population and scope of coverage (actuarial value level). The transfer formula, described in the third article, calculates balanced transfers that are intended to account for health risk differences while preserving permissible premium differences.
Using chronic disease risk factors to adjust Medicare capitation payments

PubMed Central

Schauffler, Helen Halpin; Howland, Jonathan; Cobb, Janet

1992-01-01

This study evaluates the use of risk factors for chronic disease as health status adjusters for Medicare's capitation formula, the average adjusted per capita costs (AAPCC). Risk factor data for the surviving members of the Framingham Study cohort who were examined in 1982-83 were merged with 100 percent Medicare payment data for 1984 and 1985, matching on Social Security number and sex. Seven different AAPCC models were estimated to assess the independent contributions of risk factors and measures of prior utilization and disability in increasing the explanatory power of AAPCC. The findings suggest that inclusion of risk factors for chronic disease as health status adjusters can improve substantially the predictive accuracy of AAPCC. PMID:10124441
Using risk-adjustment models to identify high-cost risks.

PubMed

Meenan, Richard T; Goodman, Michael J; Fishman, Paul A; Hornbrook, Mark C; O'Keeffe-Rosetti, Maureen C; Bachman, Donald J

2003-11-01

We examine the ability of various publicly available risk models to identify high-cost individuals and enrollee groups using multi-HMO administrative data. Five risk-adjustment models (the Global Risk-Adjustment Model [GRAM], Diagnostic Cost Groups [DCGs], Adjusted Clinical Groups [ACGs], RxRisk, and Prior-expense) were estimated on a multi-HMO administrative data set of 1.5 million individual-level observations for 1995-1996. Models produced distributions of individual-level annual expense forecasts for comparison to actual values. Prespecified "high-cost" thresholds were set within each distribution. The area under the receiver operating characteristic curve (AUC) for "high-cost" prevalences of 1% and 0.5% was calculated, as was the proportion of "high-cost" dollars correctly identified. Results are based on a separate 106,000-observation validation dataset. For "high-cost" prevalence targets of 1% and 0.5%, ACGs, DCGs, GRAM, and Prior-expense are very comparable in overall discrimination (AUCs, 0.83-0.86). Given a 0.5% prevalence target and a 0.5% prediction threshold, DCGs, GRAM, and Prior-expense captured $963,000 (approximately 3%) more "high-cost" sample dollars than other models. DCGs captured the most "high-cost" dollars among enrollees with asthma, diabetes, and depression; predictive performance among demographic groups (Medicaid members, members over 64, and children under 13) varied across models. Risk models can efficiently identify enrollees who are likely to generate future high costs and who could benefit from case management. The dollar value of improved prediction performance of the most accurate risk models should be meaningful to decision-makers and encourage their broader use for identifying high costs.
42 CFR 422.310 - Risk adjustment data.

Code of Federal Regulations, 2011 CFR

2011-10-01

... risk adjustment factors used to adjust payments, as required under §§ 422.304(a) and (c). CMS also may... submission of risk adjustment data. Risk adjustment factors for each payment year are based on risk... factors for affected individuals to determine if adjustments to payments are necessary. Risk adjustment...
42 CFR 422.310 - Risk adjustment data.

Code of Federal Regulations, 2010 CFR

2010-10-01

... risk adjustment factors used to adjust payments, as required under §§ 422.304(a) and (c). CMS also may... submission of risk adjustment data. Risk adjustment factors for each payment year are based on risk... factors for affected individuals to determine if adjustments to payments are necessary. Risk adjustment...
Lung cancer among coal miners, ore miners and quarrymen: smoking-adjusted risk estimates from the synergy pooled analysis of case-control studies.

PubMed

Taeger, Dirk; Pesch, Beate; Kendzia, Benjamin; Behrens, Thomas; Jöckel, Karl-Heinz; Dahmann, Dirk; Siemiatycki, Jack; Kromhout, Hans; Vermeulen, Roel; Peters, Susan; Olsson, Ann; Brüske, Irene; Wichmann, Heinz-Erich; Stücker, Isabelle; Guida, Florence; Tardón, Adonina; Merletti, Franco; Mirabelli, Dario; Richiardi, Lorenzo; Pohlabeln, Hermann; Ahrens, Wolfgang; Landi, Maria Teresa; Caporaso, Neil; Pesatori, Angela Cecilia; Mukeriya, Anush; Szeszenia-Dabrowska, Neonila; Lissowska, Jolanta; Gustavsson, Per; Field, John; Marcus, Michael W; Fabianova, Eleonora; 't Mannetje, Andrea; Pearce, Neil; Rudnai, Peter; Bencko, Vladimir; Janout, Vladimir; Dumitru, Rodica Stanescu; Foretova, Lenka; Forastiere, Francesco; McLaughlin, John; Paul Demers, Paul Demers; Bueno-de-Mesquita, Bas; Schüz, Joachim; Straif, Kurt; Brüning, Thomas

2015-09-01

Working in mines and quarries has been associated with an elevated lung cancer risk but with inconsistent results for coal miners. This study aimed to estimate the smoking-adjusted lung cancer risk among coal miners and compare the risk pattern with lung cancer risks among ore miners and quarrymen. We estimated lung cancer risks of coal and ore miners and quarrymen among 14 251 lung cancer cases and 17 267 controls from the SYNERGY pooled case-control study, controlling for smoking and employment in other at-risk occupations. Ever working as miner or quarryman (690 cases, 436 controls) was associated with an elevated odds ratio (OR) of 1.55 [95% confidence interval (95% CI) 1.34-1.79] for lung cancer. Ore miners (53 cases, 24 controls) had a higher OR (2.34, 95% CI 1.36-4.03) than quarrymen (67 cases, 39 controls; OR 1.92, 95% CI 1.21-3.05) and coal miners (442 cases, 297 controls; OR 1.40, 95% CI 1.18-1.67), but CI overlapped. We did not observe trends by duration of exposure or time since last exposure. This pooled analysis of population-based studies demonstrated an excess lung cancer risk among miners and quarrymen that remained increased after adjustment for detailed smoking history and working in other at-risk occupations. The increase in risk among coal miners were less pronounced than for ore miners or quarrymen.
Direct comparison of risk-adjusted and non-risk-adjusted CUSUM analyses of coronary artery bypass surgery outcomes.

PubMed

Novick, Richard J; Fox, Stephanie A; Stitt, Larry W; Forbes, Thomas L; Steiner, Stefan

2006-08-01

We previously applied non-risk-adjusted cumulative sum methods to analyze coronary bypass outcomes. The objective of this study was to assess the incremental advantage of risk-adjusted cumulative sum methods in this setting. Prospective data were collected in 793 consecutive patients who underwent coronary bypass grafting performed by a single surgeon during a period of 5 years. The composite occurrence of an "adverse outcome" included mortality or any of 10 major complications. An institutional logistic regression model for adverse outcome was developed by using 2608 contemporaneous patients undergoing coronary bypass. The predicted risk of adverse outcome in each of the surgeon's 793 patients was then calculated. A risk-adjusted cumulative sum curve was then generated after specifying control limits and odds ratio. This risk-adjusted curve was compared with the non-risk-adjusted cumulative sum curve, and the clinical significance of this difference was assessed. The surgeon's adverse outcome rate was 96 of 793 (12.1%) versus 270 of 1815 (14.9%) for all the other institution's surgeons combined (P = .06). The non-risk-adjusted curve reached below the lower control limit, signifying excellent outcomes between cases 164 and 313, 323 and 407, and 667 and 793, but transgressed the upper limit between cases 461 and 478. The risk-adjusted cumulative sum curve never transgressed the upper control limit, signifying that cases preceding and including 461 to 478 were at an increased predicted risk. Furthermore, if the risk-adjusted cumulative sum curve was reset to zero whenever a control limit was reached, it still signaled a decrease in adverse outcome at 166, 653, and 782 cases. Risk-adjusted cumulative sum techniques provide incremental advantages over non-risk-adjusted methods by not signaling a decrement in performance when preoperative patient risk is high.
Risk-adjusted outcome measurement in pediatric allogeneic stem cell transplantation.

PubMed

Matthes-Martin, Susanne; Pötschger, Ulrike; Bergmann, Kirsten; Frommlet, Florian; Brannath, Werner; Bauer, Peter; Klingebiel, Thomas

2008-03-01

The purpose of the study was to define a risk score for 1-year treatment-related mortality (TRM) in children undergoing allogeneic stem cell transplantation as a basis for risk-adjusted outcome assessment. We analyzed 1364 consecutive stem cell transplants performed in 24 German and Austrian centers between 1998 and 2003. Five well-established risk factors were tested by multivariate logistic regression for predictive power: patient age, disease status, donor other than matched sibling donor, T cell depletion (TCD), and preceding stem cell transplantation. The risk score was defined by rounding the parameter estimates of the significant risk factors to the nearest integer. Crossvalidation was performed on the basis of 5 randomly extracted equal-sized parts from the database. Additionally, the score was validated for different disease entities and for single centers. Multivariate analysis revealed a significant correlation of TRM with 3 risk factors: age >10 years, advanced disease, and alternative donor. The parameter estimates were 0.76 for age, 0.73 for disease status, and 0.97 for donor type. Rounding the estimates resulted in a score with 1 point for each risk factor. One-year TRM (overall survival [OS]) were 5% (89%) with a score of 0, 18% (74%) with 1, 28% (54%) with 2, and 53% (27%) with 3 points. Crossvalidation showed stable results with a good correlation between predicted and observed mortality but moderate discrimination. The score seems to be a simple instrument to estimate the expected mortality for each risk group and for each center. Measuring TRM risk-adjusted and the comparison between expected and observed mortality may be an additional tool for outcome assessment in pediatric stem cell transplantation.
Impact of UKPDS risk estimation added to a first subjective risk estimation on management of coronary disease risk in type 2 diabetes - An observational study.

PubMed

Wind, Anne E; Gorter, Kees J; van den Donk, Maureen; Rutten, Guy E H M

2016-02-01

To investigate the impact of the UKPDS risk engine on management of CHD risk in T2DM patients. Observational study among 139 GPs. Data from 933 consecutive patients treated with a maximum of two oral glucose lowering drugs, collected at baseline and after twelve months. GPs estimated the CHD risk themselves and afterwards they calculated this with the UKPDS risk engine. Under- and overestimation were defined as a difference >5 percentage points difference between both calculations. The impact of the UKPDS risk engine was assessed by measuring differences in medication adjustments between the over-, under- and accurately estimated group. In 42.0% the GP accurately estimated the CHD risk, in 32.4% the risk was underestimated and in 25.6% overestimated. Mean difference between the estimated (18.7%) and calculated (19.1%) 10 years CHD risk was -0.36% (95% CI -1.24 to 0.52). Male gender, current smoking and total cholesterol level were associated with underestimation. Patients with an subjectively underestimated CHD risk received significantly more medication adjustments. Their UKPDS 10 year CHD risk did not increase during the follow-up period, contrary to the other two groups of patients. The UKPDS risk engine may be of added value for risk management in T2DM. Copyright © 2015 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.
45 CFR 800.204 - Reinsurance, risk corridors, and risk adjustment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 3 2013-10-01 2013-10-01 false Reinsurance, risk corridors, and risk adjustment... Adjustment § 800.204 Reinsurance, risk corridors, and risk adjustment. (a) Transitional reinsurance program... transitional reinsurance program for the individual market. (b) Temporary risk corridors program. An MSPP...
45 CFR 800.204 - Reinsurance, risk corridors, and risk adjustment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 3 2014-10-01 2014-10-01 false Reinsurance, risk corridors, and risk adjustment... Adjustment § 800.204 Reinsurance, risk corridors, and risk adjustment. (a) Transitional reinsurance program... transitional reinsurance program for the individual market. (b) Temporary risk corridors program. An MSPP...
Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.
Risk-adjusted models for adverse obstetric outcomes and variation in risk-adjusted outcomes across hospitals.

PubMed

Bailit, Jennifer L; Grobman, William A; Rice, Madeline Murguia; Spong, Catherine Y; Wapner, Ronald J; Varner, Michael W; Thorp, John M; Leveno, Kenneth J; Caritis, Steve N; Shubert, Phillip J; Tita, Alan T; Saade, George; Sorokin, Yoram; Rouse, Dwight J; Blackwell, Sean C; Tolosa, Jorge E; Van Dorsten, J Peter

2013-11-01

Regulatory bodies and insurers evaluate hospital quality using obstetrical outcomes, however meaningful comparisons should take preexisting patient characteristics into account. Furthermore, if risk-adjusted outcomes are consistent within a hospital, fewer measures and resources would be needed to assess obstetrical quality. Our objective was to establish risk-adjusted models for 5 obstetric outcomes and assess hospital performance across these outcomes. We studied a cohort of 115,502 women and their neonates born in 25 hospitals in the United States from March 2008 through February 2011. Hospitals were ranked according to their unadjusted and risk-adjusted frequency of venous thromboembolism, postpartum hemorrhage, peripartum infection, severe perineal laceration, and a composite neonatal adverse outcome. Correlations between hospital risk-adjusted outcome frequencies were assessed. Venous thromboembolism occurred too infrequently (0.03%; 95% confidence interval [CI], 0.02-0.04%) for meaningful assessment. Other outcomes occurred frequently enough for assessment (postpartum hemorrhage, 2.29%; 95% CI, 2.20-2.38, peripartum infection, 5.06%; 95% CI, 4.93-5.19, severe perineal laceration at spontaneous vaginal delivery, 2.16%; 95% CI, 2.06-2.27, neonatal composite, 2.73%; 95% CI, 2.63-2.84). Although there was high concordance between unadjusted and adjusted hospital rankings, several individual hospitals had an adjusted rank that was substantially different (as much as 12 rank tiers) than their unadjusted rank. None of the correlations between hospital-adjusted outcome frequencies was significant. For example, the hospital with the lowest adjusted frequency of peripartum infection had the highest adjusted frequency of severe perineal laceration. Evaluations based on a single risk-adjusted outcome cannot be generalized to overall hospital obstetric performance. Copyright © 2013 Mosby, Inc. All rights reserved.

Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

PubMed Central

Ellis, Randall P.; Pope, Gregory C.; Iezzoni, Lisa I.; Ayanian, John Z.; Bates, David W.; Burstin, Helen; Ash, Arlene S.

1996-01-01

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula. PMID:10172666
45 CFR 153.610 - Risk adjustment issuer requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... HHS on behalf of the State. (b) Risk adjustment data storage. An issuer that offers risk adjustment... adjustment issuer requirements. (a) Data requirements. An issuer that offers risk adjustment covered plans must submit or make accessible all required risk adjustment data for those risk adjustment covered...
45 CFR 153.610 - Risk adjustment issuer requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HHS on behalf of the State. (b) Risk adjustment data storage. An issuer that offers risk adjustment... adjustment issuer requirements. (a) Data requirements. An issuer that offers risk adjustment covered plans must submit or make accessible all required risk adjustment data for those risk adjustment covered...
45 CFR 153.610 - Risk adjustment issuer requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... HHS on behalf of the State. (b) Risk adjustment data storage. An issuer that offers risk adjustment... adjustment issuer requirements. (a) Data requirements. An issuer that offers risk adjustment covered plans must submit or make accessible all required risk adjustment data for those risk adjustment covered...
Diagnostic Risk Adjustment for Medicaid: The Disability Payment System

PubMed Central

Kronick, Richard; Dreyfus, Tony; Lee, Lora; Zhou, Zhiyuan

1996-01-01

This article describes a system of diagnostic categories that Medicaid programs can use for adjusting capitation payments to health plans that enroll people with disability. Medicaid claims from Colorado, Michigan, Missouri, New York, and Ohio are analyzed to demonstrate that the greater predictability of costs among people with disabilities makes risk adjustment more feasible than for a general population and more critical to creating health systems for people with disability. The application of our diagnostic categories to State claims data is described, including estimated effects on subsequent-year costs of various diagnoses. The challenges of implementing adjustment by diagnosis are explored. PMID:10172665
Use of screening tests to assess cancer risk and to estimate the risk of adult T-cell leukemia/lymphoma.

PubMed Central

Yanagawa, T; Tokudome, S

1990-01-01

We developed methods to assess the cancer risks by screening tests. These methods estimate the size of the high risk group adjusted for the characteristics of screening tests and estimate the incidence rates of cancer among the high risk group adjusted for the characteristics of the tests. A method was also developed for selecting the cut-off point of a screening test. Finally, the methods were applied to estimate the risk of the adult T-cell leukemia/lymphoma. PMID:2269244
Do insurers respond to risk adjustment? A long-term, nationwide analysis from Switzerland.

PubMed

von Wyl, Viktor; Beck, Konstantin

2016-03-01

Community rating in social health insurance calls for risk adjustment in order to eliminate incentives for risk selection. Swiss risk adjustment is known to be insufficient, and substantial risk selection incentives remain. This study develops five indicators to monitor residual risk selection. Three indicators target activities of conglomerates of insurers (with the same ownership), which steer enrollees into specific carriers based on applicants' risk profiles. As a proxy for their market power, those indicators estimate the amount of premium-, health care cost-, and risk-adjustment transfer variability that is attributable to conglomerates. Two additional indicators, derived from linear regression, describe the amount of residual cost differences between insurers that are not covered by risk adjustment. All indicators measuring conglomerate-based risk selection activities showed increases between 1996 and 2009, paralleling the establishment of new conglomerates. At their maxima in 2009, the indicator values imply that 56% of the net risk adjustment volume, 34% of premium variability, and 51% cost variability in the market were attributable to conglomerates. From 2010 onwards, all indicators decreased, coinciding with a pre-announced risk adjustment reform implemented in 2012. Likewise, the regression-based indicators suggest that the volume and variance of residual cost differences between insurers that are not equaled out by risk adjustment have decreased markedly since 2009 as a result of the latest reform. Our analysis demonstrates that risk-selection, especially by conglomerates, is a real phenomenon in Switzerland. However, insurers seem to have reduced risk selection activities to optimize their losses and gains from the latest risk adjustment reform.
Risk-adjusted econometric model to estimate postoperative costs: an additional instrument for monitoring performance after major lung resection.

PubMed

Brunelli, Alessandro; Salati, Michele; Refai, Majed; Xiumé, Francesco; Rocco, Gaetano; Sabbatini, Armando

2007-09-01

The objectives of this study were to develop a risk-adjusted model to estimate individual postoperative costs after major lung resection and to use it for internal economic audit. Variable and fixed hospital costs were collected for 679 consecutive patients who underwent major lung resection from January 2000 through October 2006 at our unit. Several preoperative variables were used to develop a risk-adjusted econometric model from all patients operated on during the period 2000 through 2003 by a stepwise multiple regression analysis (validated by bootstrap). The model was then used to estimate the postoperative costs in the patients operated on during the 3 subsequent periods (years 2004, 2005, and 2006). Observed and predicted costs were then compared within each period by the Wilcoxon signed rank test. Multiple regression and bootstrap analysis yielded the following model predicting postoperative cost: 11,078 + 1340.3X (age > 70 years) + 1927.8X cardiac comorbidity - 95X ppoFEV1%. No differences between predicted and observed costs were noted in the first 2 periods analyzed (year 2004, $6188.40 vs $6241.40, P = .3; year 2005, $6308.60 vs $6483.60, P = .4), whereas in the most recent period (2006) observed costs were significantly lower than the predicted ones ($3457.30 vs $6162.70, P < .0001). Greater precision in predicting outcome and costs after therapy may assist clinicians in the optimization of clinical pathways and allocation of resources. Our economic model may be used as a methodologic template for economic audit in our specialty and complement more traditional outcome measures in the assessment of performance.
Burden of typhoid fever in low-income and middle-income countries: a systematic, literature-based update with risk-factor adjustment.

PubMed

Mogasale, Vittal; Maskery, Brian; Ochiai, R Leon; Lee, Jung Seok; Mogasale, Vijayalaxmi V; Ramani, Enusa; Kim, Young Eun; Park, Jin Kyung; Wierzba, Thomas F

2014-10-01

No access to safe water is an important risk factor for typhoid fever, yet risk-level heterogeneity is unaccounted for in previous global burden estimates. Since WHO has recommended risk-based use of typhoid polysaccharide vaccine, we revisited the burden of typhoid fever in low-income and middle-income countries (LMICs) after adjusting for water-related risk. We estimated the typhoid disease burden from studies done in LMICs based on blood-culture-confirmed incidence rates applied to the 2010 population, after correcting for operational issues related to surveillance, limitations of diagnostic tests, and water-related risk. We derived incidence estimates, correction factors, and mortality estimates from systematic literature reviews. We did scenario analyses for risk factors, diagnostic sensitivity, and case fatality rates, accounting for the uncertainty in these estimates and we compared them with previous disease burden estimates. The estimated number of typhoid fever cases in LMICs in 2010 after adjusting for water-related risk was 11·9 million (95% CI 9·9-14·7) cases with 129 000 (75 000-208 000) deaths. By comparison, the estimated risk-unadjusted burden was 20·6 million (17·5-24·2) cases and 223 000 (131 000-344 000) deaths. Scenario analyses indicated that the risk-factor adjustment and updated diagnostic test correction factor derived from systematic literature reviews were the drivers of differences between the current estimate and past estimates. The risk-adjusted typhoid fever burden estimate was more conservative than previous estimates. However, by distinguishing the risk differences, it will allow assessment of the effect at the population level and will facilitate cost-effectiveness calculations for risk-based vaccination strategies for future typhoid conjugate vaccine. Copyright © 2014 Mogasale et al. Open Access article distributed under the terms of CC BY-NC-SA. Published by .. All rights reserved.
Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies.

PubMed

Rakovitch, E; Gray, R; Baehner, F L; Sutradhar, R; Crager, M; Gu, S; Nofech-Mozes, S; Badve, S S; Hanna, W; Hughes, L L; Wood, W C; Davidson, N E; Paszat, L; Shak, S; Sparano, J A; Solin, L J

2018-06-01

Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological factors to provide refined estimates of the 10-year risk of LR after treatment by BCS alone. Data from E5194 and ODC were combined. Patients with positive margins or multifocality were excluded. Identical Cox regression models were fit for each study. Patient-specific meta-analysis was used to calculate precision-weighted estimates of 10-year LR risk by DS, age, tumor size and year of diagnosis. The combined cohort includes 773 patients. The DS and age at diagnosis, tumor size and year of diagnosis provided independent prognostic information on the 10-year LR risk (p ≤ 0.009). Hazard ratios from E5194 and ODC cohorts were similar for the DS (2.48, 1.95 per 50 units), tumor size ≤ 1 versus > 1-2.5 cm (1.45, 1.47), age ≥ 50 versus < 50 year (0.61, 0.84) and year ≥ 2000 (0.67, 0.49). Utilization of DS combined with tumor size and age at diagnosis predicted more women with very low (≤ 8%) or higher (> 15%) 10-year LR risk after BCS alone compared to utilization of DS alone or clinicopathological factors alone. The combined analysis provides refined estimates of 10-year LR risk after BCS for DCIS. Adding information on tumor size and age at diagnosis to the DS adjusting for year of diagnosis provides improved LR risk estimates to guide treatment decision making.
Risk-adjusted monitoring of survival times

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sego, Landon H.; Reynolds, Marion R.; Woodall, William H.

2009-02-26

We consider the monitoring of clinical outcomes, where each patient has a di®erent risk of death prior to undergoing a health care procedure.We propose a risk-adjusted survival time CUSUM chart (RAST CUSUM) for monitoring clinical outcomes where the primary endpoint is a continuous, time-to-event variable that may be right censored. Risk adjustment is accomplished using accelerated failure time regression models. We compare the average run length performance of the RAST CUSUM chart to the risk-adjusted Bernoulli CUSUM chart, using data from cardiac surgeries to motivate the details of the comparison. The comparisons show that the RAST CUSUM chart is moremore » efficient at detecting a sudden decrease in the odds of death than the risk-adjusted Bernoulli CUSUM chart, especially when the fraction of censored observations is not too high. We also discuss the implementation of a prospective monitoring scheme using the RAST CUSUM chart.« less
Assessing risk-adjustment approaches under non-random selection.

PubMed

Luft, Harold S; Dudley, R Adams

2004-01-01

Various approaches have been proposed to adjust for differences in enrollee risk in health plans. Because risk-selection strategies may have different effects on enrollment, we simulated three types of selection--dumping, skimming, and stinting. Concurrent diagnosis-based risk adjustment, and a hybrid using concurrent adjustment for about 8% of the cases and prospective adjustment for the rest, perform markedly better than prospective or demographic adjustments, both in terms of R2 and the extent to which plans experience unwarranted gains or losses. The simulation approach offers a valuable tool for analysts in assessing various risk-adjustment strategies under different selection situations.
Measurement and risk adjustment of prelabor cesarean rates in a large sample of California hospitals.

PubMed

Huesch, Marco D; Currid-Halkett, Elizabeth; Doctor, Jason N

2014-05-01

Prelabor cesareans in women without a prior cesarean is an important quality measure, yet one that is seldom tracked. We estimated patient-level risks and calculated how sensitive hospital rankings on this proposed quality metric were to risk adjustment. This retrospective cohort study linked Californian patient data from the Agency for Healthcare Research and Quality with hospital-level operational and financial data. Using the outcome of primary prelabor cesarean, we estimated patient-level logistic regressions in progressively more detailed models. We assessed incremental fit and discrimination, and aggregated the predicted patient-level event probabilities to construct hospital-level rankings. Of 408,355 deliveries by women without prior cesareans at 254 hospitals, 11.0% were prelabor cesareans. Including age, ethnicity, race, insurance, weekend and unscheduled admission, and 12 well-known patient risk factors yielded a model c-statistic of 0.83. Further maternal comorbidities, and hospital and obstetric unit characteristics only marginally improved fit. Risk adjusting hospital rankings led to a median absolute change in rank of 44 places compared to rankings based on observed rates. Of the 48 (49) hospitals identified as in the best (worst) quintile on observed rates, only 23 (18) were so identified by the risk-adjusted model. Models predict primary prelabor cesareans with good discrimination. Systematic hospital-level variation in patient risk factors requires risk adjustment to avoid considerably different classification of hospitals by outcome performance. An opportunity exists to define this metric and report such risk-adjusted outcomes to stakeholders. Copyright © 2014 Mosby, Inc. All rights reserved.
A risk-adjusted financial model to estimate the cost of a video-assisted thoracoscopic surgery lobectomy programme.

PubMed

Brunelli, Alessandro; Tentzeris, Vasileios; Sandri, Alberto; McKenna, Alexandra; Liew, Shan Liung; Milton, Richard; Chaudhuri, Nilanjan; Kefaloyannis, Emmanuel; Papagiannopoulos, Kostas

2016-05-01

To develop a clinically risk-adjusted financial model to estimate the cost associated with a video-assisted thoracoscopic surgery (VATS) lobectomy programme. Prospectively collected data of 236 VATS lobectomy patients (August 2012-December 2013) were analysed retrospectively. Fixed and variable intraoperative and postoperative costs were retrieved from the Hospital Accounting Department. Baseline and surgical variables were tested for a possible association with total cost using a multivariable linear regression and bootstrap analyses. Costs were calculated in GBP and expressed in Euros (EUR:GBP exchange rate 1.4). The average total cost of a VATS lobectomy was €11 368 (range €6992-€62 535). Average intraoperative (including surgical and anaesthetic time, overhead, disposable materials) and postoperative costs [including ward stay, high dependency unit (HDU) or intensive care unit (ICU) and variable costs associated with management of complications] were €8226 (range €5656-€13 296) and €3029 (range €529-€51 970), respectively. The following variables remained reliably associated with total costs after linear regression analysis and bootstrap: carbon monoxide lung diffusion capacity (DLCO) <60% predicted value (P = 0.02, bootstrap 63%) and chronic obstructive pulmonary disease (COPD; P = 0.035, bootstrap 57%). The following model was developed to estimate the total costs: 10 523 + 1894 × COPD + 2376 × DLCO < 60%. The comparison between predicted and observed costs was repeated in 1000 bootstrapped samples to verify the stability of the model. The two values were not different (P > 0.05) in 86% of the samples. A hypothetical patient with COPD and DLCO less than 60% would cost €4270 more than a patient without COPD and with higher DLCO values (€14 793 vs €10 523). Risk-adjusting financial data can help estimate the total cost associated with VATS lobectomy based on clinical factors. This model can be used to audit the internal financial
Applying risk adjusted cost-effectiveness (RAC-E) analysis to hospitals: estimating the costs and consequences of variation in clinical practice.

PubMed

Karnon, Jonathan; Caffrey, Orla; Pham, Clarabelle; Grieve, Richard; Ben-Tovim, David; Hakendorf, Paul; Crotty, Maria

2013-06-01

Cost-effectiveness analysis is well established for pharmaceuticals and medical technologies but not for evaluating variations in clinical practice. This paper describes a novel methodology--risk adjusted cost-effectiveness (RAC-E)--that facilitates the comparative evaluation of applied clinical practice processes. In this application, risk adjustment is undertaken with a multivariate matching algorithm that balances the baseline characteristics of patients attending different settings (e.g., hospitals). Linked, routinely collected data are used to analyse patient-level costs and outcomes over a 2-year period, as well as to extrapolate costs and survival over patient lifetimes. The study reports the relative cost-effectiveness of alternative forms of clinical practice, including a full representation of the statistical uncertainty around the mean estimates. The methodology is illustrated by a case study that evaluates the relative cost-effectiveness of services for patients presenting with acute chest pain across the four main public hospitals in South Australia. The evaluation finds that services provided at two hospitals were dominated, and of the remaining services, the more effective hospital gained life years at a low mean additional cost and had an 80% probability of being the most cost-effective hospital at realistic cost-effectiveness thresholds. Potential determinants of the estimated variation in costs and effects were identified, although more detailed analyses to identify specific areas of variation in clinical practice are required to inform improvements at the less cost-effective institutions. Copyright © 2012 John Wiley & Sons, Ltd.
Balancing Score Adjusted Targeted Minimum Loss-based Estimation

PubMed Central

Lendle, Samuel David; Fireman, Bruce; van der Laan, Mark J.

2015-01-01

Adjusting for a balancing score is sufficient for bias reduction when estimating causal effects including the average treatment effect and effect among the treated. Estimators that adjust for the propensity score in a nonparametric way, such as matching on an estimate of the propensity score, can be consistent when the estimated propensity score is not consistent for the true propensity score but converges to some other balancing score. We call this property the balancing score property, and discuss a class of estimators that have this property. We introduce a targeted minimum loss-based estimator (TMLE) for a treatment-specific mean with the balancing score property that is additionally locally efficient and doubly robust. We investigate the new estimator’s performance relative to other estimators, including another TMLE, a propensity score matching estimator, an inverse probability of treatment weighted estimator, and a regression-based estimator in simulation studies. PMID:26561539
45 CFR 153.310 - Risk adjustment administration.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 45 Public Welfare 1 2012-10-01 2012-10-01 false Risk adjustment administration. 153.310 Section 153.310 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE CARE...
45 CFR 153.310 - Risk adjustment administration.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Risk adjustment administration. 153.310 Section 153.310 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE CARE...
45 CFR 153.310 - Risk adjustment administration.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Risk adjustment administration. 153.310 Section 153.310 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE CARE...
Risk Selection, Risk Adjustment and Choice: Concepts and Lessons from the Americas

PubMed Central

Ellis, Randall P.; Fernandez, Juan Gabriel

2013-01-01

Interest has grown worldwide in risk adjustment and risk sharing due to their potential to contain costs, improve fairness, and reduce selection problems in health care markets. Significant steps have been made in the empirical development of risk adjustment models, and in the theoretical foundations of risk adjustment and risk sharing. This literature has often modeled the effects of risk adjustment without highlighting the institutional setting, regulations, and diverse selection problems that risk adjustment is intended to fix. Perhaps because of this, the existing literature and their recommendations for optimal risk adjustment or optimal payment systems are sometimes confusing. In this paper, we present a unified way of thinking about the organizational structure of health care systems, which enables us to focus on two key dimensions of markets that have received less attention: what choices are available that may lead to selection problems, and what financial or regulatory tools other than risk adjustment are used to influence these choices. We specifically examine the health care systems, choices, and problems in four countries: the US, Canada, Chile, and Colombia, and examine the relationship between selection-related efficiency and fairness problems and the choices that are allowed in each country, and discuss recent regulatory reforms that affect choices and selection problems. In this sample, countries and insurance programs with more choices have more selection problems. PMID:24284351

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.
Dynamic probability control limits for risk-adjusted CUSUM charts based on multiresponses.

PubMed

Zhang, Xiang; Loda, Justin B; Woodall, William H

2017-07-20

For a patient who has survived a surgery, there could be several levels of recovery. Thus, it is reasonable to consider more than two outcomes when monitoring surgical outcome quality. The risk-adjusted cumulative sum (CUSUM) chart based on multiresponses has been developed for monitoring a surgical process with three or more outcomes. However, there is a significant effect of varying risk distributions on the in-control performance of the chart when constant control limits are applied. To overcome this disadvantage, we apply the dynamic probability control limits to the risk-adjusted CUSUM charts for multiresponses. The simulation results demonstrate that the in-control performance of the charts with dynamic probability control limits can be controlled for different patient populations because these limits are determined for each specific sequence of patients. Thus, the use of dynamic probability control limits for risk-adjusted CUSUM charts based on multiresponses allows each chart to be designed for the corresponding patient sequence of a surgeon or a hospital and therefore does not require estimating or monitoring the patients' risk distribution. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
[Health-based risk adjustment. Effects and side effects].

PubMed

Jahn, R; Schillo, S; Wasem, J

2012-05-01

Numerous health systems have introduced competition between health plans while banning risk-rated premiums. Risk adjustment for health plans is introduced to reduce incentives for risk selection and to create incentives for health plans to permanently invest in care for the chronically ill. According to the international health economics state of the art, risk adjustment in the German social health insurance system has used information on health status (measured by diagnoses and drug prescriptions) on top of demographic information since 2009. In non-competitive health care systems similar mechanisms are sometimes established, e.g. to achieve an equitable distribution of resources between regions. An evaluation of the first year of health-based risk adjustment demonstrates a superior performance in comparison to the old, demographic risk adjustment. The old risk adjustment formula (without ex post high-cost pooling) showed R(2) of 5.8%, CPM of 10.4% and MAPE of 2,226 €, in contrast to the new health status-based risk adjustment formula (without cash benefit for sick allowance) which reaches R(2) 20.2%, CPM 22.5% and MAPE 1,817 €. However, to make competition between health plans functional for improvement of quality and efficiency of health care, health plans must be granted additional instruments to act as prudent buyers of health care.
45 CFR 153.340 - Data collection under risk adjustment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... issuers offering risk adjustment covered plans in the State comply with data privacy and security... 45 Public Welfare 1 2014-10-01 2014-10-01 false Data collection under risk adjustment. 153.340... CARE ACT State Standards Related to the Risk Adjustment Program § 153.340 Data collection under risk...
45 CFR 153.350 - Risk adjustment data validation standards.

Code of Federal Regulations, 2012 CFR

2012-10-01

... implementation of any risk adjustment software and ensure proper validation of a statistically valid sample of... respect to implementation of risk adjustment software or as a result of data validation conducted pursuant... implementation of risk adjustment software or data validation. ...
Poisson sampling - The adjusted and unadjusted estimator revisited

Treesearch

Michael S. Williams; Hans T. Schreuder; Gerardo H. Terrazas

1998-01-01

The prevailing assumption, that for Poisson sampling the adjusted estimator "Y-hat a" is always substantially more efficient than the unadjusted estimator "Y-hat u" , is shown to be incorrect. Some well known theoretical results are applicable since "Y-hat a" is a ratio-of-means estimator and "Y-hat u" a simple unbiased estimator...
42 CFR 422.310 - Risk adjustment data.

Code of Federal Regulations, 2013 CFR

2013-10-01

... include financial penalties for failure to submit complete data. (e) Validation of risk adjustment data... records for the validation of risk adjustment data, as required by CMS. There may be penalties for... the prior December 31. (2) CMS allows a reconciliation process to account for late data submissions...
42 CFR 422.310 - Risk adjustment data.

Code of Federal Regulations, 2012 CFR

2012-10-01

... include financial penalties for failure to submit complete data. (e) Validation of risk adjustment data... records for the validation of risk adjustment data, as required by CMS. There may be penalties for... the prior December 31. (2) CMS allows a reconciliation process to account for late data submissions...
A simple signaling rule for variable life-adjusted display derived from an equivalent risk-adjusted CUSUM chart.

PubMed

Wittenberg, Philipp; Gan, Fah Fatt; Knoth, Sven

2018-04-17

The variable life-adjusted display (VLAD) is the first risk-adjusted graphical procedure proposed in the literature for monitoring the performance of a surgeon. It displays the cumulative sum of expected minus observed deaths. It has since become highly popular because the statistic plotted is easy to understand. But it is also easy to misinterpret a surgeon's performance by utilizing the VLAD, potentially leading to grave consequences. The problem of misinterpretation is essentially caused by the variance of the VLAD's statistic that increases with sample size. In order for the VLAD to be truly useful, a simple signaling rule is desperately needed. Various forms of signaling rules have been developed, but they are usually quite complicated. Without signaling rules, making inferences using the VLAD alone is difficult if not misleading. In this paper, we establish an equivalence between a VLAD with V-mask and a risk-adjusted cumulative sum (RA-CUSUM) chart based on the difference between the estimated probability of death and surgical outcome. Average run length analysis based on simulation shows that this particular RA-CUSUM chart has similar performance as compared to the established RA-CUSUM chart based on the log-likelihood ratio statistic obtained by testing the odds ratio of death. We provide a simple design procedure for determining the V-mask parameters based on a resampling approach. Resampling from a real data set ensures that these parameters can be estimated appropriately. Finally, we illustrate the monitoring of a real surgeon's performance using VLAD with V-mask. Copyright © 2018 John Wiley & Sons, Ltd.
Odds per Adjusted Standard Deviation: Comparing Strengths of Associations for Risk Factors Measured on Different Scales and Across Diseases and Populations

PubMed Central

Hopper, John L.

2015-01-01

How can the “strengths” of risk factors, in the sense of how well they discriminate cases from controls, be compared when they are measured on different scales such as continuous, binary, and integer? Given that risk estimates take into account other fitted and design-related factors—and that is how risk gradients are interpreted—so should the presentation of risk gradients. Therefore, for each risk factor X0, I propose using appropriate regression techniques to derive from appropriate population data the best fitting relationship between the mean of X0 and all the other covariates fitted in the model or adjusted for by design (X1, X2, … , Xn). The odds per adjusted standard deviation (OPERA) presents the risk association for X0 in terms of the change in risk per s = standard deviation of X0 adjusted for X1, X2, … , Xn, rather than the unadjusted standard deviation of X0 itself. If the increased risk is relative risk (RR)-fold over A adjusted standard deviations, then OPERA = exp[ln(RR)/A] = RRs. This unifying approach is illustrated by considering breast cancer and published risk estimates. OPERA estimates are by definition independent and can be used to compare the predictive strengths of risk factors across diseases and populations. PMID:26520360
45 CFR 153.620 - Compliance with risk adjustment standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... with risk adjustment standards. (a) Issuer support of data validation. An issuer that offers risk adjustment covered plans must comply with any data validation requests by the State or HHS on behalf of the... must retain any information requested to support risk adjustment data validation for a period of at...
45 CFR 153.620 - Compliance with risk adjustment standards.

Code of Federal Regulations, 2012 CFR

2012-10-01

... with risk adjustment standards. (a) Issuer support of data validation. An issuer that offers risk adjustment covered plans must comply with any data validation requests by the State or HHS on behalf of the... must retain any information requested to support risk adjustment data validation for a period of at...
Risk-adjusted capitation: recent experiences in The Netherlands.

PubMed

van de Ven, W P; van Vliet, R C; van Barneveld, E M; Lamers, L M

1994-01-01

The market-oriented health care reforms taking place in the Netherlands show a clear resemblance to the proposals for managed competition in U.S. health care. In both countries good risk adjustment mechanisms that prevent cream skimming--that is, that prevent plans from selecting the best health risks--are critical to the success of the reforms. In this paper we present an overview of the Dutch reforms and of our research concerning risk-adjusted capitation payments. Although we are optimistic about the technical possibilities for solving the problem of cream skimming, the implementation of good risk-adjusted capitation is a long-term challenge.
Risk adjustment as basis for rational benchmarking: the example of colon carcinoma.

PubMed

Ptok, Henry; Marusch, Frank; Schmidt, Uwe; Gastinger, Ingo; Wenisch, Hubertus J C; Lippert, Hans

2011-01-01

The results of resection of colorectal carcinoma can vary greatly from one hospital to another. However, this does not necessarily reflect differences in the quality of treatment. The purpose of this study was to compare various tools for the risk-adjusted assessment of treatment results after resection of colorectal carcinoma within the context of hospital benchmarking. On the basis of a data pool provided by a multicentric observation study of patients with colon cancer, the postoperative in-hospital mortality rates at two high-volume hospitals ("A" and "B") were compared. After univariate comparison, risk-adjusted comparison of postoperative mortality was performed by logistic regression analysis (LReA), propensity-score analysis (PScA), and the CR-POSSUM score. Postoperative complications were compared by LReA and PScA. Although postoperative mortality differed significantly (P = 0.041) in univariate comparison of hospitals A and B (2.9% vs. 6.4%), no significant difference was found by LReA or PScA. Similarly, the observed mortality at these did not differ significantly from the mortality estimated by the CR-POSSUM score (hospital A, 2.9%/4.9%, P = 0.298; hospital B, 6.4%/6.5%, P = 1.000). Significant differences were seen in risk-adjusted comparison of most postoperative complications (by both LReA and PScA), but there were no differences in the rates of relaparotomy or anastomotic leakage that required surgery. For the hard outcome variable "postoperative mortality," none of the three risk adjustment procedures showed any difference between the hospitals. The CR-POSSUM score can be regarded as the most practicable tool for risk-adjusted comparison of the outcome of colon-carcinoma resection in clinical benchmarking.
Monitoring risk-adjusted medical outcomes allowing for changes over time.

PubMed

Steiner, Stefan H; Mackay, R Jock

2014-10-01

We consider the problem of monitoring and comparing medical outcomes, such as surgical performance, over time. Performance is subject to change due to a variety of reasons including patient heterogeneity, learning, deteriorating skills due to aging, etc. For instance, we expect inexperienced surgeons to improve their skills with practice. We propose a graphical method to monitor surgical performance that incorporates risk adjustment to account for patient heterogeneity. The procedure gives more weight to recent outcomes and down-weights the influence of outcomes further in the past. The chart is clinically interpretable as it plots an estimate of the failure rate for a "standard" patient. The chart also includes a measure of uncertainty in this estimate. We can implement the method using historical data or start from scratch. As the monitoring proceeds, we can base the estimated failure rate on a known risk model or use the observed outcomes to update the risk model as time passes. We illustrate the proposed method with an example from cardiac surgery. © The Author 2013. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Security Events and Vulnerability Data for Cybersecurity Risk Estimation.

PubMed

Allodi, Luca; Massacci, Fabio

2017-08-01

Current industry standards for estimating cybersecurity risk are based on qualitative risk matrices as opposed to quantitative risk estimates. In contrast, risk assessment in most other industry sectors aims at deriving quantitative risk estimations (e.g., Basel II in Finance). This article presents a model and methodology to leverage on the large amount of data available from the IT infrastructure of an organization's security operation center to quantitatively estimate the probability of attack. Our methodology specifically addresses untargeted attacks delivered by automatic tools that make up the vast majority of attacks in the wild against users and organizations. We consider two-stage attacks whereby the attacker first breaches an Internet-facing system, and then escalates the attack to internal systems by exploiting local vulnerabilities in the target. Our methodology factors in the power of the attacker as the number of "weaponized" vulnerabilities he/she can exploit, and can be adjusted to match the risk appetite of the organization. We illustrate our methodology by using data from a large financial institution, and discuss the significant mismatch between traditional qualitative risk assessments and our quantitative approach. © 2017 Society for Risk Analysis.
Managing loss adjustment expenses: strategies for health care risk managers.

PubMed

Quinley, K M

1991-01-01

Like most businesses, adjusting companies are not charitable organizations. They are entitled to a reasonable profit, which the risk manager should not begrudge. As a buyer of adjusting services, a risk manager with an inordinate obsession with slashing adjusting bills can destroy the goal of high-quality service. It is best for risk managers to pick and choose the areas for cutting adjusting expenses. To an extent, health care risk managers should view payment of high-quality adjusting services as an investment, with the payback being money saved by fighting fraudulent, exaggerated, and questionable claims.
Cause-specific premature death from ambient PM2.5 exposure in India: Estimate adjusted for baseline mortality.

PubMed

Chowdhury, Sourangsu; Dey, Sagnik

2016-05-01

In India, more than a billion population is at risk of exposure to ambient fine particulate matter (PM2.5) concentration exceeding World Health Organization air quality guideline, posing a serious threat to health. Cause-specific premature death from ambient PM2.5 exposure is poorly known for India. Here we develop a non-linear power law (NLP) function to estimate the relative risk associated with ambient PM2.5 exposure using satellite-based PM2.5 concentration (2001-2010) that is bias-corrected against coincident direct measurements. We show that estimate of annual premature death in India is lower by 14.7% (19.2%) using NLP (integrated exposure risk function, IER) for assumption of uniform baseline mortality across India (as considered in the global burden of disease study) relative to the estimate obtained by adjusting for state-specific baseline mortality using GDP as a proxy. 486,100 (811,000) annual premature death in India is estimated using NLP (IER) risk functions after baseline mortality adjustment. 54.5% of premature death estimated using NLP risk function is attributed to chronic obstructive pulmonary disease (COPD), 24.0% to ischemic heart disease (IHD), 18.5% to stroke and the remaining 3.0% to lung cancer (LC). 44,900 (5900-173,300) less premature death is expected annually, if India achieves its present annual air quality target of 40μgm(-3). Our results identify the worst affected districts in terms of ambient PM2.5 exposure and resulting annual premature death and call for initiation of long-term measures through a systematic framework of pollution and health data archive. Copyright © 2016 Elsevier Ltd. All rights reserved.
Level of education and multiple sclerosis risk after adjustment for known risk factors: The EnvIMS study.

PubMed

Bjørnevik, Kjetil; Riise, Trond; Cortese, Marianna; Holmøy, Trygve; Kampman, Margitta T; Magalhaes, Sandra; Myhr, Kjell-Morten; Wolfson, Christina; Pugliatti, Maura

2016-01-01

Several recent studies have found a higher risk of multiple sclerosis (MS) among people with a low level of education. This has been suggested to reflect an effect of smoking and lower vitamin D status in the social class associated with lower levels of education. The objective of this paper is to investigate the association between level of education and MS risk adjusting for the known risk factors smoking, infectious mononucleosis, indicators of vitamin D levels and body size. Within the case-control study on Environmental Factors In MS (EnvIMS), 953 MS patients and 1717 healthy controls from Norway reported educational level and history of exposure to putative environmental risk factors. Higher level of education were associated with decreased MS risk (p trend = 0.001) with an OR of 0.53 (95% CI 0.41-0.68) when comparing those with the highest and lowest level of education. This association was only moderately reduced after adjusting for known risk factors (OR 0.61, 95% CI 0.44-0.83). The estimates remained similar when cases with disease onset before age 28 were excluded. These findings suggest that factors related to lower socioeconomic status other than established risk factors are associated with MS risk. © The Author(s), 2015.
Level of education and multiple sclerosis risk after adjustment for known risk factors: The EnvIMS study

PubMed Central

Bjørnevik, Kjetil; Riise, Trond; Cortese, Marianna; Holmøy, Trygve; Kampman, Margitta T; Magalhaes, Sandra; Myhr, Kjell-Morten; Wolfson, Christina; Pugliatti, Maura

2016-01-01

Background: Several recent studies have found a higher risk of multiple sclerosis (MS) among people with a low level of education. This has been suggested to reflect an effect of smoking and lower vitamin D status in the social class associated with lower levels of education. Objective: The objective of this paper is to investigate the association between level of education and MS risk adjusting for the known risk factors smoking, infectious mononucleosis, indicators of vitamin D levels and body size. Methods: Within the case-control study on Environmental Factors In MS (EnvIMS), 953 MS patients and 1717 healthy controls from Norway reported educational level and history of exposure to putative environmental risk factors. Results: Higher level of education were associated with decreased MS risk (p trend = 0.001) with an OR of 0.53 (95% CI 0.41–0.68) when comparing those with the highest and lowest level of education. This association was only moderately reduced after adjusting for known risk factors (OR 0.61, 95% CI 0.44–0.83). The estimates remained similar when cases with disease onset before age 28 were excluded. Conclusion: These findings suggest that factors related to lower socioeconomic status other than established risk factors are associated with MS risk. PMID:26014605

Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations.

PubMed

Hopper, John L

2015-11-15

How can the "strengths" of risk factors, in the sense of how well they discriminate cases from controls, be compared when they are measured on different scales such as continuous, binary, and integer? Given that risk estimates take into account other fitted and design-related factors-and that is how risk gradients are interpreted-so should the presentation of risk gradients. Therefore, for each risk factor X0, I propose using appropriate regression techniques to derive from appropriate population data the best fitting relationship between the mean of X0 and all the other covariates fitted in the model or adjusted for by design (X1, X2, … , Xn). The odds per adjusted standard deviation (OPERA) presents the risk association for X0 in terms of the change in risk per s = standard deviation of X0 adjusted for X1, X2, … , Xn, rather than the unadjusted standard deviation of X0 itself. If the increased risk is relative risk (RR)-fold over A adjusted standard deviations, then OPERA = exp[ln(RR)/A] = RR(s). This unifying approach is illustrated by considering breast cancer and published risk estimates. OPERA estimates are by definition independent and can be used to compare the predictive strengths of risk factors across diseases and populations. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Antipsychotics and mortality: adjusting for mortality risk scores to address confounding by terminal illness.

PubMed

Park, Yoonyoung; Franklin, Jessica M; Schneeweiss, Sebastian; Levin, Raisa; Crystal, Stephen; Gerhard, Tobias; Huybrechts, Krista F

2015-03-01

To determine whether adjustment for prognostic indices specifically developed for nursing home (NH) populations affect the magnitude of previously observed associations between mortality and conventional and atypical antipsychotics. Cohort study. A merged data set of Medicaid, Medicare, Minimum Data Set (MDS), Online Survey Certification and Reporting system, and National Death Index for 2001 to 2005. Dual-eligible individuals aged 65 and older who initiated antipsychotic treatment in a NH (N=75,445). Three mortality risk scores (Mortality Risk Index Score, Revised MDS Mortality Risk Index, Advanced Dementia Prognostic Tool) were derived for each participant using baseline MDS data, and their performance was assessed using c-statistics and goodness-of-fit tests. The effect of adjusting for these indices in addition to propensity scores (PSs) on the association between antipsychotic medication and mortality was evaluated using Cox models with and without adjustment for risk scores. Each risk score showed moderate discrimination for 6-month mortality, with c-statistics ranging from 0.61 to 0.63. There was no evidence of lack of fit. Imbalances in risk scores between conventional and atypical antipsychotic users, suggesting potential confounding, were much lower within PS deciles than the imbalances in the full cohort. Accounting for each score in the Cox model did not change the relative risk estimates: 2.24 with PS-only adjustment versus 2.20, 2.20, and 2.22 after further adjustment for the three risk scores. Although causality cannot be proven based on nonrandomized studies, this study adds to the body of evidence rejecting explanations other than causality for the greater mortality risk associated with conventional antipsychotics than with atypical antipsychotics. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.
45 CFR 153.320 - Federally certified risk adjustment methodology.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Federally certified risk adjustment methodology. 153.320 Section 153.320 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE...
45 CFR 153.340 - Data collection under risk adjustment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Data collection under risk adjustment. 153.340 Section 153.340 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE...
45 CFR 153.330 - State alternate risk adjustment methodology.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 45 Public Welfare 1 2012-10-01 2012-10-01 false State alternate risk adjustment methodology. 153.330 Section 153.330 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE...
45 CFR 153.330 - State alternate risk adjustment methodology.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false State alternate risk adjustment methodology. 153.330 Section 153.330 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE...
45 CFR 153.320 - Federally certified risk adjustment methodology.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Federally certified risk adjustment methodology. 153.320 Section 153.320 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE...
45 CFR 153.620 - Compliance with risk adjustment standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Compliance with risk adjustment standards. 153.620 Section 153.620 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE...
45 CFR 153.320 - Federally certified risk adjustment methodology.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 45 Public Welfare 1 2012-10-01 2012-10-01 false Federally certified risk adjustment methodology. 153.320 Section 153.320 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE...
45 CFR 153.330 - State alternate risk adjustment methodology.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false State alternate risk adjustment methodology. 153.330 Section 153.330 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE...
[Risk-adjusted assessment: late-onset infection in neonates].

PubMed

Gmyrek, Dieter; Koch, Rainer; Vogtmann, Christoph; Kaiser, Annette; Friedrich, Annette

2011-01-01

The weak point of the countrywide perinatal/neonatal quality surveillance is the ignorance of interhospital differences in the case mix of patients. As a result, this approach does not produce reliable benchmarking. The objective of this study was to adjust the result of the late-onset infection incidence of different hospitals according to their risk profile of patients by multivariate analysis. The perinatal/neonatal database of 41,055 newborns of the Saxonian quality surveillance from 1998 to 2004 was analysed. Based on 18 possible risk factors, a logistic regression model was used to develop a specific risk predictor for the quality indicator "late-onset infection". The developed risk predictor for the incidence of late-onset infection could be described by 4 of the 18 analysed risk factors, namely gestational age, admission from home, hypoxic ischemic encephalopathy and B-streptococcal infection. The AUC(ROC) value of this quality indicator was 83.3%, which demonstrates its reliability. The hospital ranking based on the adjusted risk assessment was very different from hospital rankings before this adjustment. The average correction of ranking position was 4.96 for 35 clinics. The application of the risk adjustment method proposed here allows for a more objective comparison of the incidence of the quality indicator "late onset infection" among different hospitals. Copyright © 2011. Published by Elsevier GmbH.
Use of risk-adjusted CUSUM charts to monitor 30-day mortality in Danish hospitals.

PubMed

Rasmussen, Thomas Bøjer; Ulrichsen, Sinna Pilgaard; Nørgaard, Mette

2018-01-01

Monitoring hospital outcomes and clinical processes as a measure of clinical performance is an integral part of modern health care. The risk-adjusted cumulative sum (CUSUM) chart is a frequently used sequential analysis technique that can be implemented to monitor a wide range of different types of outcomes. The aim of this study was to describe how risk-adjusted CUSUM charts based on population-based nationwide medical registers were used to monitor 30-day mortality in Danish hospitals and to give an example on how alarms of increased hospital mortality from the charts can guide further in-depth analyses. We used routinely collected administrative data from the Danish National Patient Registry and the Danish Civil Registration System to create risk-adjusted CUSUM charts. We monitored 30-day mortality after hospital admission with one of 77 selected diagnoses in 24 hospital units in Denmark in 2015. The charts were set to detect a 50% increase in 30-day mortality, and control limits were determined by simulations. Among 1,085,576 hospital admissions, 441,352 admissions had one of the 77 selected diagnoses as their primary diagnosis and were included in the risk-adjusted CUSUM charts. The charts yielded a total of eight alarms of increased mortality. The median of the hospitals' estimated average time to detect a 50% increase in 30-day mortality was 50 days (interquartile interval, 43;54). In the selected example of an alarm, descriptive analyses indicated performance problems with 30-day mortality following hip fracture surgery and diagnosis of chronic obstructive pulmonary disease. The presented implementation of risk-adjusted CUSUM charts can detect significant increases in 30-day mortality within 2 months, on average, in most Danish hospitals. Together with descriptive analyses, it was possible to use an alarm from a risk-adjusted CUSUM chart to identify potential performance problems.
[Survival analysis with competing risks: estimating failure probability].

PubMed

Llorca, Javier; Delgado-Rodríguez, Miguel

2004-01-01

To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.
Risk Adjustment for a Children's Capitation Rate

PubMed Central

Newhouse, Joseph P.; Sloss, Elizabeth M.; Manning, Willard G.; Keeler, Emmett B.

1993-01-01

Few capitation arrangements vary premiums by a child's health characteristics, yielding an incentive to discriminate against children with predictably high expenditures from chronic diseases. In this article, we explore risk adjusters for the 35 percent of the variance in annual outpatient expenditure we find to be potentially predictable. Demographic factors such as age and gender only explain 5 percent of such variance; health status measures explain 25 percent, prior use and health status measures together explain 65 to 70 percent. The profit from risk selection falls less than proportionately with improved ability to adjust for risk. Partial capitation rates may be necessary to mitigate skimming and dumping. PMID:10133708
Risk adjustment for a children's capitation rate.

PubMed

Newhouse, J P; Sloss, E M; Manning, W G; Keeler, E B

1993-01-01

Few capitation arrangements vary premiums by a child's health characteristics, yielding an incentive to discriminate against children with predictably high expenditures from chronic diseases. In this article, we explore risk adjusters for the 35 percent of the variance in annual out-patient expenditure we find to be potentially predictable. Demographic factors such as age and gender only explain 5 percent of such variance; health status measures explain 25 percent, prior use and health status measures together explain 65 to 70 percent. The profit from risk selection falls less than proportionately with improved ability to adjust for risk. Partial capitation rates may be necessary to mitigate skimming and dumping.
45 CFR 153.340 - Data collection under risk adjustment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... program, the State may vary the amount and type of data collected, but the State must collect or calculate... 45 Public Welfare 1 2012-10-01 2012-10-01 false Data collection under risk adjustment. 153.340... CARE ACT State Standards Related to the Risk Adjustment Program § 153.340 Data collection under risk...
78 FR 32255 - HHS-Operated Risk Adjustment Data Validation Stakeholder Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-29

...-Operated Risk Adjustment Data Validation Stakeholder Meeting AGENCY: Centers for Medicare & Medicaid... Act HHS-operated risk adjustment data validation process. The purpose of this public meeting is to... interested parties about key HHS policy considerations pertaining to the HHS-operated risk adjustment data...
Health-Based Capitation Risk Adjustment in Minnesota Public Health Care Programs

PubMed Central

Gifford, Gregory A.; Edwards, Kevan R.; Knutson, David J.

2004-01-01

This article documents the history and implementation of health-based capitation risk adjustment in Minnesota public health care programs, and identifies key implementation issues. Capitation payments in these programs are risk adjusted using an historical, health plan risk score, based on concurrent risk assessment. Phased implementation of capitation risk adjustment for these programs began January 1, 2000. Minnesota's experience with capitation risk adjustment suggests that: (1) implementation can accelerate encounter data submission, (2) administrative decisions made during implementation can create issues that impact payment model performance, and (3) changes in diagnosis data management during implementation may require changes to the payment model. PMID:25372356
Hospital Variation in Risk-Adjusted Pediatric Sepsis Mortality.

PubMed

Ames, Stefanie G; Davis, Billie S; Angus, Derek C; Carcillo, Joseph A; Kahn, Jeremy M

2018-05-01

With continued attention to pediatric sepsis at both the clinical and policy levels, it is important to understand the quality of hospitals in terms of their pediatric sepsis mortality. We sought to develop a method to evaluate hospital pediatric sepsis performance using 30-day risk-adjusted mortality and to assess hospital variation in risk-adjusted sepsis mortality in a large state-wide sample. Retrospective cohort study using administrative claims data. Acute care hospitals in the state of Pennsylvania from 2011 to 2013. Patients between the ages of 0-19 years admitted to a hospital with sepsis defined using validated International Classification of Diseases, Ninth revision, Clinical Modification, diagnosis and procedure codes. None. During the study period, there were 9,013 pediatric sepsis encounters in 153 hospitals. After excluding repeat visits and hospitals with annual patient volumes too small to reliably assess hospital performance, there were 6,468 unique encounters in 24 hospitals. The overall unadjusted mortality rate was 6.5% (range across all hospitals: 1.5-11.9%). The median number of pediatric sepsis cases per hospital was 67 (range across all hospitals: 30-1,858). A hierarchical logistic regression model for 30-day risk-adjusted mortality controlling for patient age, gender, emergency department admission, infection source, presence of organ dysfunction at admission, and presence of chronic complex conditions showed good discrimination (C-statistic = 0.80) and calibration (slope and intercept of calibration plot: 0.95 and -0.01, respectively). The hospital-specific risk-adjusted mortality rates calculated from this model varied minimally, ranging from 6.0% to 7.4%. Although a risk-adjustment model for 30-day pediatric sepsis mortality had good performance characteristics, the use of risk-adjusted mortality rates as a hospital quality measure in pediatric sepsis is not useful due to the low volume of cases at most hospitals. Novel metrics to
45 CFR 153.350 - Risk adjustment data validation standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Risk adjustment data validation standards. 153.350... validation standards. (a) General requirement. The State, or HHS on behalf of the State, must ensure proper implementation of any risk adjustment software and ensure proper validation of a statistically valid sample of...

45 CFR 153.350 - Risk adjustment data validation standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Risk adjustment data validation standards. 153.350... validation standards. (a) General requirement. The State, or HHS on behalf of the State, must ensure proper implementation of any risk adjustment software and ensure proper validation of a statistically valid sample of...
Health plans and selection: formal risk adjustment vs. market design and contracts.

PubMed

Frank, R G; Rosenthal, M B

2001-01-01

In this paper, we explore the demand for risk adjustment by health plans that contract with private employers by considering the conditions under which plans might value risk adjustment. Three factors reduce the value of risk adjustment from the plans' point of view. First, only a relatively small segment of privately insured Americans face a choice of competing health plans. Second, health plans share much of their insurance risk with payers, providers, and reinsurers. Third, de facto experience rating that occurs during the premium negotiation process and management of coverage appear to substitute for risk adjustment. While the current environment has not generated much demand for risk adjustment, we reflect on its future potential.
Risk adjustment alternatives in paying for behavioral health care under Medicaid.

PubMed Central

Ettner, S L; Frank, R G; McGuire, T G; Hermann, R C

2001-01-01

OBJECTIVE: To compare the performance of various risk adjustment models in behavioral health applications such as setting mental health and substance abuse (MH/SA) capitation payments or overall capitation payments for populations including MH/SA users. DATA SOURCES/STUDY DESIGN: The 1991-93 administrative data from the Michigan Medicaid program were used. We compared mean absolute prediction error for several risk adjustment models and simulated the profits and losses that behavioral health care carve outs and integrated health plans would experience under risk adjustment if they enrolled beneficiaries with a history of MH/SA problems. Models included basic demographic adjustment, Adjusted Diagnostic Groups, Hierarchical Condition Categories, and specifications designed for behavioral health. PRINCIPAL FINDINGS: Differences in predictive ability among risk adjustment models were small and generally insignificant. Specifications based on relatively few MH/SA diagnostic categories did as well as or better than models controlling for additional variables such as medical diagnoses at predicting MH/SA expenditures among adults. Simulation analyses revealed that among both adults and minors considerable scope remained for behavioral health care carve outs to make profits or losses after risk adjustment based on differential enrollment of severely ill patients. Similarly, integrated health plans have strong financial incentives to avoid MH/SA users even after adjustment. CONCLUSIONS: Current risk adjustment methodologies do not eliminate the financial incentives for integrated health plans and behavioral health care carve-out plans to avoid high-utilizing patients with psychiatric disorders. PMID:11508640
Dynamic probability control limits for risk-adjusted Bernoulli CUSUM charts.

PubMed

Zhang, Xiang; Woodall, William H

2015-11-10

The risk-adjusted Bernoulli cumulative sum (CUSUM) chart developed by Steiner et al. (2000) is an increasingly popular tool for monitoring clinical and surgical performance. In practice, however, the use of a fixed control limit for the chart leads to a quite variable in-control average run length performance for patient populations with different risk score distributions. To overcome this problem, we determine simulation-based dynamic probability control limits (DPCLs) patient-by-patient for the risk-adjusted Bernoulli CUSUM charts. By maintaining the probability of a false alarm at a constant level conditional on no false alarm for previous observations, our risk-adjusted CUSUM charts with DPCLs have consistent in-control performance at the desired level with approximately geometrically distributed run lengths. Our simulation results demonstrate that our method does not rely on any information or assumptions about the patients' risk distributions. The use of DPCLs for risk-adjusted Bernoulli CUSUM charts allows each chart to be designed for the corresponding particular sequence of patients for a surgeon or hospital. Copyright © 2015 John Wiley & Sons, Ltd.
Risk-adjusted hospital outcomes for children's surgery.

PubMed

Saito, Jacqueline M; Chen, Li Ern; Hall, Bruce L; Kraemer, Kari; Barnhart, Douglas C; Byrd, Claudia; Cohen, Mark E; Fei, Chunyuan; Heiss, Kurt F; Huffman, Kristopher; Ko, Clifford Y; Latus, Melissa; Meara, John G; Oldham, Keith T; Raval, Mehul V; Richards, Karen E; Shah, Rahul K; Sutton, Laura C; Vinocur, Charles D; Moss, R Lawrence

2013-09-01

BACKGROUND The American College of Surgeons National Surgical Quality Improvement Program-Pediatric was initiated in 2008 to drive quality improvement in children's surgery. Low mortality and morbidity in previous analyses limited differentiation of hospital performance. Participating institutions included children's units within general hospitals and free-standing children's hospitals. Cases selected by Current Procedural Terminology codes encompassed procedures within pediatric general, otolaryngologic, orthopedic, urologic, plastic, neurologic, thoracic, and gynecologic surgery. Trained personnel abstracted demographic, surgical profile, preoperative, intraoperative, and postoperative variables. Incorporating procedure-specific risk, hierarchical models for 30-day mortality and morbidities were developed with significant predictors identified by stepwise logistic regression. Reliability was estimated to assess the balance of information versus error within models. In 2011, 46 281 patients from 43 hospitals were accrued; 1467 codes were aggregated into 226 groupings. Overall mortality was 0.3%, composite morbidity 5.8%, and surgical site infection (SSI) 1.8%. Hierarchical models revealed outlier hospitals with above or below expected performance for composite morbidity in the entire cohort, pediatric abdominal subgroup, and spine subgroup; SSI in the entire cohort and pediatric abdominal subgroup; and urinary tract infection in the entire cohort. Based on reliability estimates, mortality discriminates performance poorly due to very low event rate; however, reliable model construction for composite morbidity and SSI that differentiate institutions is feasible. The National Surgical Quality Improvement Program-Pediatric expansion has yielded risk-adjusted models to differentiate hospital performance in composite and specific morbidities. However, mortality has low utility as a children's surgery performance indicator. Programmatic improvements have resulted in
Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.
Breeds of risk-adjusted fundamentalist strategies in an order-driven market

NASA Astrophysics Data System (ADS)

LiCalzi, Marco; Pellizzari, Paolo

2006-01-01

This paper studies an order-driven stock market where agents have heterogeneous estimates of the fundamental value of the risky asset. The agents are budget-constrained and follow a value-based trading strategy which buys or sells depending on whether the price of the asset is below or above its risk-adjusted fundamental value. This environment generates returns that are remarkably leptokurtic and fat-tailed. By extending the study over a grid of different parameters for the fundamentalist trading strategy, we exhibit the existence of monotone relationships between the bid-ask spread demanded by the agents and several statistics of the returns. We conjecture that this effect, coupled with positive dependence of the risk premium on the volatility, generates positive feedbacks that might explain volatility bursts.
Bayesian effect estimation accounting for adjustment uncertainty.

PubMed

Wang, Chi; Parmigiani, Giovanni; Dominici, Francesca

2012-09-01

Model-based estimation of the effect of an exposure on an outcome is generally sensitive to the choice of which confounding factors are included in the model. We propose a new approach, which we call Bayesian adjustment for confounding (BAC), to estimate the effect of an exposure of interest on the outcome, while accounting for the uncertainty in the choice of confounders. Our approach is based on specifying two models: (1) the outcome as a function of the exposure and the potential confounders (the outcome model); and (2) the exposure as a function of the potential confounders (the exposure model). We consider Bayesian variable selection on both models and link the two by introducing a dependence parameter, ω, denoting the prior odds of including a predictor in the outcome model, given that the same predictor is in the exposure model. In the absence of dependence (ω= 1), BAC reduces to traditional Bayesian model averaging (BMA). In simulation studies, we show that BAC, with ω > 1, estimates the exposure effect with smaller bias than traditional BMA, and improved coverage. We, then, compare BAC, a recent approach of Crainiceanu, Dominici, and Parmigiani (2008, Biometrika 95, 635-651), and traditional BMA in a time series data set of hospital admissions, air pollution levels, and weather variables in Nassau, NY for the period 1999-2005. Using each approach, we estimate the short-term effects of on emergency admissions for cardiovascular diseases, accounting for confounding. This application illustrates the potentially significant pitfalls of misusing variable selection methods in the context of adjustment uncertainty. © 2012, The International Biometric Society.
45 CFR 153.365 - General oversight requirements for State-operated risk adjustment programs.

Code of Federal Regulations, 2014 CFR

2014-10-01

... risk adjustment programs. 153.365 Section 153.365 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE CARE ACT State Standards Related to the Risk Adjustment Program...
Real-time adjusting of rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch

2017-04-01

Urban stormwater predictions require reliable rainfall information with space-time resolution higher than commonly provided by standard rainfall monitoring networks of national weather services. Rainfall data from commercial microwave links (CMLs) could fill this gap. CMLs are line-of-sight radio connections widely used by cellular operators which operate at millimeter bands, where radio waves are attenuated by raindrops. Attenuation data of each single CML in the cellular network can be remotely accessed in (near) real-time with virtually arbitrary sampling frequency and convert to rainfall intensity. Unfortunately, rainfall estimates from CMLs can be substantially biased. Fencl et al., (2017), therefore, proposed adjusting method which enables to correct for this bias. They used rain gauge (RG) data from existing rainfall monitoring networks, which would have otherwise insufficient spatial and temporal resolution for urban rainfall monitoring when used alone without CMLs. In this investigation, we further develop the method to improve its performance in a real-time setting. First, a shortcoming of the original algorithm which delivers unreliable results at the beginning of a rainfall event is overcome by introducing model parameter prior distributions estimated from previous parameter realizations. Second, weights reflecting variance between RGs are introduced into cost function, which is minimized when optimizing model parameters. Finally, RG data used for adjusting are preprocessed by moving average filter. The performance of improved adjusting method is evaluated on four short CMLs (path length < 2 km) located in the small urban catchment (2.3 km2) in Prague-Letnany (CZ). The adjusted CMLs are compared to reference rainfall calculated from six RGs in the catchment. The suggested improvements of the method lead on average to 10% higher Nash-Sutcliffe efficiency coefficient (median value 0.85) for CML adjustment to hourly RG data. Reliability of CML rainfall
Children's Adjustment Following Divorce: Risk and Resilience Perspectives.

ERIC Educational Resources Information Center

Kelly, Joan B.; Emery, Robert E.

2003-01-01

Reviews the empirical literature on the longer-term adjustment of children of divorce from the perspective of (a) the stressors and elevated risks that divorce presents for children and (b) protective factors associated with better adjustment. The resiliency demonstrated by the majority of children is discussed, as are controversies regarding the…
28 CFR 100.19 - Adjustments to agreement estimate.

Code of Federal Regulations, 2012 CFR

2012-07-01

... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
28 CFR 100.19 - Adjustments to agreement estimate.

Code of Federal Regulations, 2011 CFR

2011-07-01

... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
28 CFR 100.19 - Adjustments to agreement estimate.

Code of Federal Regulations, 2013 CFR

2013-07-01

... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
28 CFR 100.19 - Adjustments to agreement estimate.

Code of Federal Regulations, 2014 CFR

2014-07-01

... the FBI when any change affecting the level of reimbursement occurs. (2) Upon such notification, if the adjustment results in an increase in the estimated reimbursement, the FBI will review the... expenditure. (3) The FBI will provide the decision as to the acceptability of any increase to the carrier in...
Functional form and risk adjustment of hospital costs: Bayesian analysis of a Box-Cox random coefficients model.

PubMed

Hollenbeak, Christopher S

2005-10-15

While risk-adjusted outcomes are often used to compare the performance of hospitals and physicians, the most appropriate functional form for the risk adjustment process is not always obvious for continuous outcomes such as costs. Semi-log models are used most often to correct skewness in cost data, but there has been limited research to determine whether the log transformation is sufficient or whether another transformation is more appropriate. This study explores the most appropriate functional form for risk-adjusting the cost of coronary artery bypass graft (CABG) surgery. Data included patients undergoing CABG surgery at four hospitals in the midwest and were fit to a Box-Cox model with random coefficients (BCRC) using Markov chain Monte Carlo methods. Marginal likelihoods and Bayes factors were computed to perform model comparison of alternative model specifications. Rankings of hospital performance were created from the simulation output and the rankings produced by Bayesian estimates were compared to rankings produced by standard models fit using classical methods. Results suggest that, for these data, the most appropriate functional form is not logarithmic, but corresponds to a Box-Cox transformation of -1. Furthermore, Bayes factors overwhelmingly rejected the natural log transformation. However, the hospital ranking induced by the BCRC model was not different from the ranking produced by maximum likelihood estimates of either the linear or semi-log model. Copyright (c) 2005 John Wiley & Sons, Ltd.
On-demand Reporting of Risk-adjusted and Smoothed Rates for Quality Profiling in ACS NSQIP.

PubMed

Cohen, Mark E; Liu, Yaoming; Huffman, Kristopher M; Ko, Clifford Y; Hall, Bruce L

2016-12-01

Surgical quality improvement depends on hospitals having accurate and timely information about comparative performance. Profiling accuracy is improved by risk adjustment and shrinkage adjustment to stabilize estimates. These adjustments are included in ACS NSQIP reports, where hospital odds ratios (OR) are estimated using hierarchical models built on contemporaneous data. However, the timeliness of feedback remains an issue. We describe an alternative, nonhierarchical approach, which yields risk- and shrinkage-adjusted rates. In contrast to our "Traditional" NSQIP method, this approach uses preexisting equations, built on historical data, which permits hospitals to have near immediate access to profiling results. We compared our traditional method to this new "on-demand" approach with respect to outlier determinations, kappa statistics, and correlations between logged OR and standardized rates, for 12 models (4 surgical groups by 3 outcomes). When both methods used the same contemporaneous data, there were similar numbers of hospital outliers and correlations between logged OR and standardized rates were high. However, larger differences were observed when the effect of contemporaneous versus historical data was added to differences in statistical methodology. The on-demand, nonhierarchical approach provides results similar to the traditional hierarchical method and offers immediacy, an "over-time" perspective, application to a broader range of models and data subsets, and reporting of more easily understood rates. Although the nonhierarchical method results are now available "on-demand" in a web-based application, the hierarchical approach has advantages, which support its continued periodic publication as the gold standard for hospital profiling in the program.
Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

PubMed Central

Maciejewski, Matthew L.; Liu, Chuan-Fen; Fihn, Stephan D.

2009-01-01

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS—This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R2 statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS—Administrative data–based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS—Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed. PMID:18945927
A longitudinal high-risk study of adolescent anxiety, depression and parent-severity on the developmental course of risk-adjustment.

PubMed

Rawal, Adhip; Riglin, Lucy; Ng-Knight, Terry; Collishaw, Stephan; Thapar, Anita; Rice, Frances

2014-11-01

Adolescence is associated with developments in the reward system and increased rates of emotional disorders. Familial risk for depression may be associated with disruptions in the reward system. However, it is unclear how symptoms of depression and anxiety influence the development of reward-processing over adolescence and whether variation in the severity of parental depression is associated with hyposensitivity to reward in a high-risk sample. We focused on risk-adjustment (adjusting decisions about reward according to the probability of obtaining reward) as this was hypothesized to improve over adolescence. In a one-year longitudinal sample (N = 197) of adolescent offspring of depressed parents, we examined how symptoms of depression and anxiety (generalized anxiety and social anxiety) influenced the development of risk-adjustment. We also examined how parental depression severity influenced adolescent risk-adjustment. Risk-adjustment improved over the course of the study indicating improved adjustment of reward-seeking to shifting contingencies. Depressive symptoms were associated with decreases in risk-adjustment over time while social anxiety symptoms were associated with increases in risk-adjustment over time. Specifically, depression was associated with reductions in reward-seeking at favourable reward probabilities only, whereas social anxiety (but not generalized anxiety) led to reductions in reward-seeking at low reward probabilities only. Parent depression severity was associated with lowered risk-adjustment in offspring and also influenced the longitudinal relationship between risk-adjustment and offspring depression. Anxiety and depression distinctly alter the pattern of longitudinal change in reward-processing. Severity of parent depression was associated with alterations in adolescent offspring reward-processing in a high-risk sample. © 2014 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of
REVIEW OF DRAFT REVISED BLUE BOOK ON ESTIMATING CANCER RISKS FROM EXPOSURE TO IONIZING RADIATION

EPA Science Inventory

In 1994, EPA published a report, referred to as the “Blue Book,” which lays out EPA’s current methodology for quantitatively estimating radiogenic cancer risks. A follow-on report made minor adjustments to the previous estimates and presented a partial analysis of the uncertainti...

Belgium: risk adjustment and financial responsibility in a centralised system.

PubMed

Schokkaert, Erik; Van de Voorde, Carine

2003-07-01

Since 1995 Belgian sickness funds are partially financed through a risk adjustment system and are held partially financially responsible for the difference between their actual and their risk-adjusted expenditures. However, they did not get the necessary instruments for exerting a real influence on expenditures and the health insurance market has not been opened for new entrants. At the same time the sickness funds have powerful tools for risk selection, because they also dominate the market for supplementary health insurance. The present risk-adjustment system is based on the results of a regression analysis with aggregate data. The main proclaimed purpose of this system is to guarantee a fair treatment to all the sickness funds. Until now the danger of risk selection has not been taken seriously. Consumer mobility has remained rather low. However, since the degree of financial responsibility is programmed to increase in the near future, the potential profits from cream skimming will increase.
Evaluation of the DAVROS (Development And Validation of Risk-adjusted Outcomes for Systems of emergency care) risk-adjustment model as a quality indicator for healthcare

PubMed Central

Wilson, Richard; Goodacre, Steve W; Klingbajl, Marcin; Kelly, Anne-Maree; Rainer, Tim; Coats, Tim; Holloway, Vikki; Townend, Will; Crane, Steve

2014-01-01

Background and objective Risk-adjusted mortality rates can be used as a quality indicator if it is assumed that the discrepancy between predicted and actual mortality can be attributed to the quality of healthcare (ie, the model has attributional validity). The Development And Validation of Risk-adjusted Outcomes for Systems of emergency care (DAVROS) model predicts 7-day mortality in emergency medical admissions. We aimed to test this assumption by evaluating the attributional validity of the DAVROS risk-adjustment model. Methods We selected cases that had the greatest discrepancy between observed mortality and predicted probability of mortality from seven hospitals involved in validation of the DAVROS risk-adjustment model. Reviewers at each hospital assessed hospital records to determine whether the discrepancy between predicted and actual mortality could be explained by the healthcare provided. Results We received 232/280 (83%) completed review forms relating to 179 unexpected deaths and 53 unexpected survivors. The healthcare system was judged to have potentially contributed to 10/179 (8%) of the unexpected deaths and 26/53 (49%) of the unexpected survivors. Failure of the model to appropriately predict risk was judged to be responsible for 135/179 (75%) of the unexpected deaths and 2/53 (4%) of the unexpected survivors. Some 10/53 (19%) of the unexpected survivors died within a few months of the 7-day period of model prediction. Conclusions We found little evidence that deaths occurring in patients with a low predicted mortality from risk-adjustment could be attributed to the quality of healthcare provided. PMID:23605036
Gaming in risk-adjusted mortality rates: effect of misclassification of risk factors in the benchmarking of cardiac surgery risk-adjusted mortality rates.

PubMed

Siregar, Sabrina; Groenwold, Rolf H H; Versteegh, Michel I M; Noyez, Luc; ter Burg, Willem Jan P P; Bots, Michiel L; van der Graaf, Yolanda; van Herwerden, Lex A

2013-03-01

Upcoding or undercoding of risk factors could affect the benchmarking of risk-adjusted mortality rates. The aim was to investigate the effect of misclassification of risk factors on the benchmarking of mortality rates after cardiac surgery. A prospective cohort was used comprising all adult cardiac surgery patients in all 16 cardiothoracic centers in The Netherlands from January 1, 2007, to December 31, 2009. A random effects model, including the logistic European system for cardiac operative risk evaluation (EuroSCORE) was used to benchmark the in-hospital mortality rates. We simulated upcoding and undercoding of 5 selected variables in the patients from 1 center. These patients were selected randomly (nondifferential misclassification) or by the EuroSCORE (differential misclassification). In the random patients, substantial misclassification was required to affect benchmarking: a 1.8-fold increase in prevalence of the 4 risk factors changed an underperforming center into an average performing one. Upcoding of 1 variable required even more. When patients with the greatest EuroSCORE were upcoded (ie, differential misclassification), a 1.1-fold increase was sufficient: moderate left ventricular function from 14.2% to 15.7%, poor left ventricular function from 8.4% to 9.3%, recent myocardial infarction from 7.9% to 8.6%, and extracardiac arteriopathy from 9.0% to 9.8%. Benchmarking using risk-adjusted mortality rates can be manipulated by misclassification of the EuroSCORE risk factors. Misclassification of random patients or of single variables will have little effect. However, limited upcoding of multiple risk factors in high-risk patients can greatly influence benchmarking. To minimize "gaming," the prevalence of all risk factors should be carefully monitored. Copyright © 2013 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.
When methods meet politics: how risk adjustment became part of Medicare managed care.

PubMed

Weissman, Joel S; Wachterman, Melissa; Blumenthal, David

2005-06-01

Health-based risk adjustment has long been touted as key to the success of competitive models of health care. Because it decreases the incentive to enroll only healthy patients in insurance plans, risk adjustment was incorporated into Medicare policy via the Balanced Budget Act of 1997. However, full implementation of risk adjustment was delayed due to clashes with the managed care industry over payment policy, concerns over perverse incentives, and problems of data burden. We review the history of risk adjustment leading up to the Balanced Budget Act and examine the controversies surrounding attempts to stop or delay its implementation during the years that followed. The article provides lessons for the future of health-based risk adjustment and possible alternatives.
Integrating Risk Adjustment and Enrollee Premiums in Health Plan Payment

PubMed Central

McGuire, Thomas G.; Glazer, Jacob; Newhouse, Joseph P.; Normand, Sharon-Lise; Shi, Julie; Sinaiko, Anna D.; Zuvekas, Samuel

2013-01-01

In two important health policy contexts – private plans in Medicare and the new state-run “Exchanges” created as part of the Affordable Care Act (ACA) – plan payments come from two sources: risk-adjusted payments from a Regulator and premiums charged to individual enrollees. This paper derives principles for integrating risk-adjusted payments and premium policy in individual health insurance markets based on fitting total plan payments to health plan costs per person as closely as possible. A least squares regression including both health status and variables used in premiums reveals the weights a Regulator should put on risk adjusters when markets determine premiums. We apply the methods to an Exchange-eligible population drawn from the Medical Expenditure Panel Survey (MEPS). PMID:24308878
42 CFR 403.750 - Estimate of expenditures and adjustments.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
42 CFR 403.750 - Estimate of expenditures and adjustments.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 2 2014-10-01 2014-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
42 CFR 403.750 - Estimate of expenditures and adjustments.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
42 CFR 403.750 - Estimate of expenditures and adjustments.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 42 Public Health 2 2012-10-01 2012-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
42 CFR 403.750 - Estimate of expenditures and adjustments.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 42 Public Health 2 2013-10-01 2013-10-01 false Estimate of expenditures and adjustments. 403.750 Section 403.750 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Religious Nonmedical Health Care Institutions...
Performance of diagnosis-based risk adjustment measures in a population of sick Australians.

PubMed

Duckett, S J; Agius, P A

2002-12-01

Australia is beginning to explore 'managed competition' as an organising framework for the health care system. This requires setting fair capitation rates, i.e. rates that adjust for the risk profile of covered lives. This paper tests two US-developed risk adjustment approaches using Australian data. Data from the 'co-ordinated care' dataset (which incorporates all service costs of 16,538 participants in a large health service research project conducted in 1996-99) were grouped into homogenous risk categories using risk adjustment 'grouper software'. The grouper products yielded three sets of homogenous categories: Diagnostic Groups and Diagnostic cost Groups. A two-stage analysis of predictive power was used: probability of any service use in the concurrent year, next year and the year after (logistic regression) and, for service users, a regression of logged cost of service use. The independent variables were diagnosis gender, a SES variable and the Age, gender and diagnosis-based risk adjustment measures explain around 40-45% of variation in costs of service use in the current year for untrimmed data (compared with around 15% for age and gender alone). Prediction of subsequent use is much poorer (around 20%). Using more information to assign people to risk categories generally improves prediction. Predictive power of diagnosis-base risk adjusters on this Australian dataset is similar to that found in Low predictive power carries policy risks of cream skimming rather than managing population health and care. Competitive funding models with risk adjustment on prior year experience could reduce system efficiency if implemented with current risk adjustment technology.
Risk adjusting community rated health plan premiums: a survey of risk assessment literature and policy applications.

PubMed

Giacomini, M; Luft, H S; Robinson, J C

1995-01-01

This paper surveys recent health care reform debates and empirical evidence regarding the potential role for risk adjusters in addressing the problem of competitive risk segmentation under capitated financing. We discuss features of health plan markets affecting risk selection, methodological considerations in measuring it, and alternative approaches to financial correction for risk differentials. The appropriate approach to assessing risk differences between health plans depends upon the nature of market risk selection allowed under a given reform scenario. Because per capita costs depend on a health plan's population risk, efficiency, and quality of service, risk adjustment will most strongly promote efficiency in environments with commensurately strong incentives for quality care.
Integrating risk adjustment and enrollee premiums in health plan payment.

PubMed

McGuire, Thomas G; Glazer, Jacob; Newhouse, Joseph P; Normand, Sharon-Lise; Shi, Julie; Sinaiko, Anna D; Zuvekas, Samuel H

2013-12-01

In two important health policy contexts - private plans in Medicare and the new state-run "Exchanges" created as part of the Affordable Care Act (ACA) - plan payments come from two sources: risk-adjusted payments from a Regulator and premiums charged to individual enrollees. This paper derives principles for integrating risk-adjusted payments and premium policy in individual health insurance markets based on fitting total plan payments to health plan costs per person as closely as possible. A least squares regression including both health status and variables used in premiums reveals the weights a Regulator should put on risk adjusters when markets determine premiums. We apply the methods to an Exchange-eligible population drawn from the Medical Expenditure Panel Survey (MEPS). Copyright © 2013 Elsevier B.V. All rights reserved.
Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its
Monitoring risk-adjusted outcomes in congenital heart surgery: does the appropriateness of a risk model change with time?

PubMed

Tsang, Victor T; Brown, Katherine L; Synnergren, Mats Johanssen; Kang, Nicholas; de Leval, Marc R; Gallivan, Steve; Utley, Martin

2009-02-01

Risk adjustment of outcomes in pediatric congenital heart surgery is challenging due to the great diversity in diagnoses and procedures. We have previously shown that variable life-adjusted display (VLAD) charts provide an effective graphic display of risk-adjusted outcomes in this specialty. A question arises as to whether the risk model used remains appropriate over time. We used a recently developed graphic technique to evaluate the performance of an existing risk model among those patients at a single center during 2000 to 2003 originally used in model development. We then compared the distribution of predicted risk among these patients with that among patients in 2004 to 2006. Finally, we constructed a VLAD chart of risk-adjusted outcomes for the latter period. Among 1083 patients between April 2000 and March 2003, the risk model performed well at predicted risks above 3%, underestimated mortality at 2% to 3% predicted risk, and overestimated mortality below 2% predicted risk. There was little difference in the distribution of predicted risk among these patients and among 903 patients between June 2004 and October 2006. Outcomes for the more recent period were appreciably better than those expected according to the risk model. This finding cannot be explained by any apparent bias in the risk model combined with changes in case-mix. Risk models can, and hopefully do, become out of date. There is scope for complacency in the risk-adjusted audit if the risk model used is not regularly recalibrated to reflect changing standards and expectations.
Assessing uncertainty in published risk estimates using ...

EPA Pesticide Factsheets

Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective is to characterize model uncertainty by evaluating estimates across published epidemiologic studies of the same cohort.Methods: This analysis was based on 5 studies analyzing a cohort of 2,357 workers employed from 1950-74 in a chromate production plant in Maryland. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability within and between model forms. A total of 5 similarly parameterized analyses were considered across model form, and 16 analyses with alternative parameterizations were considered within model form (10 Cox; 6 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients (betas) for 5 similar analyses ranged from 2.47 to 4.33 (mean=2.97, σ2=0.63). Within the 10 Cox models, coefficients ranged from 2.53 to 4.42 (mean=3.29, σ2=0.
Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality.

PubMed

Coresh, Josef; Turin, Tanvir Chowdhury; Matsushita, Kunihiro; Sang, Yingying; Ballew, Shoshana H; Appel, Lawrence J; Arima, Hisatomi; Chadban, Steven J; Cirillo, Massimo; Djurdjev, Ognjenka; Green, Jamie A; Heine, Gunnar H; Inker, Lesley A; Irie, Fujiko; Ishani, Areef; Ix, Joachim H; Kovesdy, Csaba P; Marks, Angharad; Ohkubo, Takayoshi; Shalev, Varda; Shankar, Anoop; Wen, Chi Pang; de Jong, Paul E; Iseki, Kunitoshi; Stengel, Benedicte; Gansevoort, Ron T; Levey, Andrew S

2014-06-25

The established chronic kidney disease (CKD) progression end point of end-stage renal disease (ESRD) or a doubling of serum creatinine concentration (corresponding to a change in estimated glomerular filtration rate [GFR] of −57% or greater) is a late event. To characterize the association of decline in estimated GFR with subsequent progression to ESRD with implications for using lesser declines in estimated GFR as potential alternative end points for CKD progression. Because most people with CKD die before reaching ESRD, mortality risk also was investigated. Individual meta-analysis of 1.7 million participants with 12,344 ESRD events and 223,944 deaths from 35 cohorts in the CKD Prognosis Consortium with a repeated measure of serum creatinine concentration over 1 to 3 years and outcome data. Transfer of individual participant data or standardized analysis of outputs for random-effects meta-analysis conducted between July 2012 and September 2013, with baseline estimated GFR values collected from 1975 through 2012. End-stage renal disease (initiation of dialysis or transplantation) or all-cause mortality risk related to percentage change in estimated GFR over 2 years, adjusted for potential confounders and first estimated GFR. The adjusted hazard ratios (HRs) of ESRD and mortality were higher with larger estimated GFR decline. Among participants with baseline estimated GFR of less than 60 mL/min/1.73 m2, the adjusted HRs for ESRD were 32.1 (95% CI, 22.3-46.3) for changes of −57% in estimated GFR and 5.4 (95% CI, 4.5-6.4) for changes of −30%. However, changes of −30% or greater (6.9% [95% CI, 6.4%-7.4%] of the entire consortium) were more common than changes of −57% (0.79% [95% CI, 0.52%-1.06%]). This association was strong and consistent across the length of the baseline period (1 to 3 years), baseline estimated GFR, age, diabetes status, or albuminuria. Average adjusted 10-year risk of ESRD (in patients with a baseline estimated GFR of 35 mL/min/1.73 m2
Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

NASA Astrophysics Data System (ADS)

Karbalaee, Negar; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2017-04-01

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the Integrated Multisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained.
Risk Adjustment May Lessen Penalties On Hospitals Treating Complex Cardiac Patients Under Medicare's Bundled Payments.

PubMed

Markovitz, Adam A; Ellimoottil, Chandy; Sukul, Devraj; Mullangi, Samyukta; Chen, Lena M; Nallamothu, Brahmajee K; Ryan, Andrew M

2017-12-01

To reduce variation in spending, Medicare has considered implementing a cardiac bundled payment program for acute myocardial infarction and coronary artery bypass graft. Because the proposed program does not account for patient risk factors when calculating hospital penalties or rewards ("reconciliation payments"), it might unfairly penalize certain hospitals. We estimated the impact of adjusting for patients' medical complexity and social risk on reconciliation payments for Medicare beneficiaries hospitalized for the two conditions in the period 2011-13. Average spending per episode was $29,394. Accounting for medical complexity substantially narrowed the gap in reconciliation payments between hospitals with high medical severity (from a penalty of $1,809 to one of $820, or a net reduction of $989), safety-net hospitals (from a penalty of $217 to one of $87, a reduction of $130), and minority-serving hospitals (from a penalty of $70 to a reward of $56, an improvement of $126) and their counterparts. Accounting for social risk alone narrowed these gaps but had minimal incremental effects after medical complexity was accounted for. Risk adjustment may preserve incentives to care for patients with complex conditions under Medicare bundled payment programs.
Use of Prolonged Travel to Improve Pediatric Risk-Adjustment Models

PubMed Central

Lorch, Scott A; Silber, Jeffrey H; Even-Shoshan, Orit; Millman, Andrea

2009-01-01

Objective To determine whether travel variables could explain previously reported differences in lengths of stay (LOS), readmission, or death at children's hospitals versus other hospital types. Data Source Hospital discharge data from Pennsylvania between 1996 and 1998. Study Design A population cohort of children aged 1–17 years with one of 19 common pediatric conditions was created (N=51,855). Regression models were constructed to determine difference for LOS, readmission, or death between children's hospitals and other types of hospitals after including five types of additional illness severity variables to a traditional risk-adjustment model. Principal Findings With the traditional risk-adjustment model, children traveling longer to children's or rural hospitals had longer adjusted LOS and higher readmission rates. Inclusion of either a geocoded travel time variable or a nongeocoded travel distance variable provided the largest reduction in adjusted LOS, adjusted readmission rates, and adjusted mortality rates for children's hospitals and rural hospitals compared with other types of hospitals. Conclusions Adding a travel variable to traditional severity adjustment models may improve the assessment of an individual hospital's pediatric care by reducing systematic differences between different types of hospitals. PMID:19207591

Risk adjustment and the fear of markets: the case of Belgium.

PubMed

Schokkaert, E; Van de Voorde, C

2000-02-01

In Belgium the management and administration of the compulsory and universal health insurance is left to a limited number of non-governmental non-profit sickness funds. Since 1995 these sickness funds are partially financed in a prospective way. The risk adjustment scheme is based on a regression model to explain medical expenditures for different social groups. Medical supply is taken out of the formula to construct risk-adjusted capitation payments. The risk-adjustment formula still leaves scope for risk selection. At the same time, the sickness funds were not given the instruments to exert a real influence on expenditures and the health insurance market has not been opened for new entrants. As a consequence, Belgium runs the danger of ending up in a situation with little incentives for efficiency and considerable profits from cream skimming.
Appraisal and coping as mediators of the effects of cumulative risk on preadolescent adjustment

PubMed Central

Thompson, Stephanie F.; Lengua, Liliana J.; Garcia, Connie Meza

2016-01-01

This study examined the concurrent and longitudinal relations among cumulative risk, appraisal, coping, and adjustment. Longitudinal path models were tested in a community sample of 316 children in preadolescence to examine hypotheses that threat appraisal and avoidant coping mediate the effects of cumulative risk on child adjustment, whereas positive appraisal and active coping were hypothesized to predict better adjustment independently. Children and their mothers were assessed during in-home interviews at three time points at one-year intervals. Children reported on appraisal and coping strategies. Mothers and children reported on child adjustment problems and positive adjustment. Rank-order changes in appraisal and coping predicted rank-order changes in adjustment. Cumulative risk was concurrently related to higher threat appraisal and avoidant coping at each time point. Threat appraisal and avoidant coping mediated the relations of cumulative risk to rank-order changes in adjustment. There is specificity in the relations of cumulative risk to threat appraisal and avoidant coping, whereas positive appraisal and active coping are independent of risk and operate as individual resource factors. PMID:27110087
Sperm competition risk drives rapid ejaculate adjustments mediated by seminal fluid

PubMed Central

Steeves, Tammy E; Gemmell, Neil J; Rosengrave, Patrice C

2017-01-01

In many species, males can make rapid adjustments to ejaculate performance in response to sperm competition risk; however, the mechanisms behind these changes are not understood. Here, we manipulate male social status in an externally fertilising fish, chinook salmon (Oncorhynchus tshawytscha), and find that in less than 48 hr, males can upregulate sperm velocity when faced with an increased risk of sperm competition. Using a series of in vitro sperm manipulation and competition experiments, we show that rapid changes in sperm velocity are mediated by seminal fluid and the effect of seminal fluid on sperm velocity directly impacts paternity share and therefore reproductive success. These combined findings, completely consistent with sperm competition theory, provide unequivocal evidence that sperm competition risk drives plastic adjustment of ejaculate quality, that seminal fluid harbours the mechanism for the rapid adjustment of sperm velocity and that fitness benefits accrue to males from such adjustment. PMID:29084621
Sperm competition risk drives rapid ejaculate adjustments mediated by seminal fluid.

PubMed

Bartlett, Michael J; Steeves, Tammy E; Gemmell, Neil J; Rosengrave, Patrice C

2017-10-31

In many species, males can make rapid adjustments to ejaculate performance in response to sperm competition risk; however, the mechanisms behind these changes are not understood. Here, we manipulate male social status in an externally fertilising fish, chinook salmon ( Oncorhynchus tshawytscha ), and find that in less than 48 hr, males can upregulate sperm velocity when faced with an increased risk of sperm competition. Using a series of in vitro sperm manipulation and competition experiments, we show that rapid changes in sperm velocity are mediated by seminal fluid and the effect of seminal fluid on sperm velocity directly impacts paternity share and therefore reproductive success. These combined findings, completely consistent with sperm competition theory, provide unequivocal evidence that sperm competition risk drives plastic adjustment of ejaculate quality, that seminal fluid harbours the mechanism for the rapid adjustment of sperm velocity and that fitness benefits accrue to males from such adjustment.
Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.
A Review on Methods of Risk Adjustment and their Use in Integrated Healthcare Systems

PubMed Central

Juhnke, Christin; Bethge, Susanne

2016-01-01

Introduction: Effective risk adjustment is an aspect that is more and more given weight on the background of competitive health insurance systems and vital healthcare systems. The objective of this review was to obtain an overview of existing models of risk adjustment as well as on crucial weights in risk adjustment. Moreover, the predictive performance of selected methods in international healthcare systems should be analysed. Theory and methods: A comprehensive, systematic literature review on methods of risk adjustment was conducted in terms of an encompassing, interdisciplinary examination of the related disciplines. Results: In general, several distinctions can be made: in terms of risk horizons, in terms of risk factors or in terms of the combination of indicators included. Within these, another differentiation by three levels seems reasonable: methods based on mortality risks, methods based on morbidity risks as well as those based on information on (self-reported) health status. Conclusions and discussion: After the final examination of different methods of risk adjustment it was shown that the methodology used to adjust risks varies. The models differ greatly in terms of their included morbidity indicators. The findings of this review can be used in the evaluation of integrated healthcare delivery systems and can be integrated into quality- and patient-oriented reimbursement of care providers in the design of healthcare contracts. PMID:28316544
Incorporating Comorbidity Within Risk Adjustment for UK Pediatric Cardiac Surgery.

PubMed

Brown, Katherine L; Rogers, Libby; Barron, David J; Tsang, Victor; Anderson, David; Tibby, Shane; Witter, Thomas; Stickley, John; Crowe, Sonya; English, Kate; Franklin, Rodney C; Pagel, Christina

2017-07-01

When considering early survival rates after pediatric cardiac surgery it is essential to adjust for risk linked to case complexity. An important but previously less well understood component of case mix complexity is comorbidity. The National Congenital Heart Disease Audit data representing all pediatric cardiac surgery procedures undertaken in the United Kingdom and Ireland between 2009 and 2014 was used to develop and test groupings for comorbidity and additional non-procedure-based risk factors within a risk adjustment model for 30-day mortality. A mixture of expert consensus based opinion and empiric statistical analyses were used to define and test the new comorbidity groups. The study dataset consisted of 21,838 pediatric cardiac surgical procedure episodes in 18,834 patients with 539 deaths (raw 30-day mortality rate, 2.5%). In addition to surgical procedure type, primary cardiac diagnosis, univentricular status, age, weight, procedure type (bypass, nonbypass, or hybrid), and era, the new risk factor groups of non-Down congenital anomalies, acquired comorbidities, increased severity of illness indicators (eg, preoperative mechanical ventilation or circulatory support) and additional cardiac risk factors (eg, heart muscle conditions and raised pulmonary arterial pressure) all independently increased the risk of operative mortality. In an era of low mortality rates across a wide range of operations, non-procedure-based risk factors form a vital element of risk adjustment and their presence leads to wide variations in the predicted risk of a given operation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Reinforcing flood-risk estimation.

PubMed

Reed, Duncan W

2002-07-15

Flood-frequency estimation is inherently uncertain. The practitioner applies a combination of gauged data, scientific method and hydrological judgement to derive a flood-frequency curve for a particular site. The resulting estimate can be thought fully satisfactory only if it is broadly consistent with all that is reliably known about the flood-frequency behaviour of the river. The paper takes as its main theme the search for information to strengthen a flood-risk estimate made from peak flows alone. Extra information comes in many forms, including documentary and monumental records of historical floods, and palaeological markers. Meteorological information is also useful, although rainfall rarity is difficult to assess objectively and can be a notoriously unreliable indicator of flood rarity. On highly permeable catchments, groundwater levels present additional data. Other types of information are relevant to judging hydrological similarity when the flood-frequency estimate derives from data pooled across several catchments. After highlighting information sources, the paper explores a second theme: that of consistency in flood-risk estimates. Following publication of the Flood estimation handbook, studies of flood risk are now using digital catchment data. Automated calculation methods allow estimates by standard methods to be mapped basin-wide, revealing anomalies at special sites such as river confluences. Such mapping presents collateral information of a new character. Can this be used to achieve flood-risk estimates that are coherent throughout a river basin?
77 FR 21775 - Risk Adjustment Meeting-May 7, 2012 and May 8, 2012

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-11

... notice announces a meeting on the risk adjustment program, which is open to the public. The purpose of... plan average actuarial risk, calculation of payments and charges, data collection approach, and the..., calculation of payments and charges, data collection approach, and the schedule for running risk adjustment...
Patient Protection and Affordable Care Act; standards related to reinsurance, risk corridors, and risk adjustment. Final rule.

PubMed

2012-03-23

This final rule implements standards for States related to reinsurance and risk adjustment, and for health insurance issuers related to reinsurance, risk corridors, and risk adjustment consistent with title I of the Patient Protection and Affordable Care Act as amended by the Health Care and Education Reconciliation Act of 2010, referred to collectively as the Affordable Care Act. These programs will mitigate the impact of potential adverse selection and stabilize premiums in the individual and small group markets as insurance reforms and the Affordable Insurance Exchanges ("Exchanges") are implemented, starting in 2014. The transitional State-based reinsurance program serves to reduce uncertainty by sharing risk in the individual market through making payments for high claims costs for enrollees. The temporary Federally administered risk corridors program serves to protect against uncertainty in rate setting by qualified health plans sharing risk in losses and gains with the Federal government. The permanent State-based risk adjustment program provides payments to health insurance issuers that disproportionately attract high-risk populations (such as individuals with chronic conditions).
45 CFR 153.360 - Application of risk adjustment to the small group market.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Application of risk adjustment to the small group market. 153.360 Section 153.360 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER...
45 CFR 153.360 - Application of risk adjustment to the small group market.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Application of risk adjustment to the small group market. 153.360 Section 153.360 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS STANDARDS RELATED TO REINSURANCE, RISK CORRIDORS, AND RISK ADJUSTMENT UNDER...
45 CFR 153.630 - Data validation requirements when HHS operates risk adjustment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Data validation requirements when HHS operates... Program § 153.630 Data validation requirements when HHS operates risk adjustment. (a) General requirement... performed on its risk adjustment data as described in this section. (b) Initial validation audit. (1) An...
45 CFR 153.630 - Data validation requirements when HHS operates risk adjustment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Data validation requirements when HHS operates... Program § 153.630 Data validation requirements when HHS operates risk adjustment. (a) General requirement... performed on its risk adjustment data as described in this section. (b) Initial validation audit. (1) An...
An Online Tool for Global Benchmarking of Risk-Adjusted Surgical Outcomes.

PubMed

Spence, Richard T; Chang, David C; Chu, Kathryn; Panieri, Eugenio; Mueller, Jessica L; Hutter, Matthew M

2017-01-01

Increasing evidence demonstrates significant variation in adverse outcomes following surgery between countries. In order to better quantify these variations, we hypothesize that freely available online risk calculators can be used as a tool to generate global benchmarking of risk-adjusted surgical outcomes. This is a prospective cohort study conducted at an academic teaching hospital in South Africa (GSH). Consecutive adult patients undergoing major general or vascular surgery who met the ACS-NSQIP inclusion criteria for a 3-month period were included. Data variables required by the ACS risk calculator were prospectively collected, and patients were followed for 30 days post-surgery for the occurrence of endpoints. Calculating observed-to-expected ratios for ten outcome measures of interest generated risk-adjusted outcomes benchmarked against the ACS-NSQIP consortium. A total of 373 major general and vascular surgery procedures met the inclusion criteria. The GSH operative cohort varied significantly compared to the 2012 ACS-NSQIP database. The risk-adjusted O/E ratios were significant for any complication O/E 1.91 (95 % CI 1.57-2.31), surgical site infections O/E 4.76 (95 % CI 3.71-6.01), renal failure O/E 3.29 (95 % CI 1.50-6.24), death O/E 3.43 (95 % CI 2.19-5.11), and total length of stay (LOS) O/E 3.43 (95 % CI 2.19-5.11). Freely available online risk calculators can be utilized as tools for global benchmarking of risk-adjusted surgical outcomes.
A risk-adjusted definition of biochemical recurrence after radical prostatectomy.

PubMed

Morgan, T M; Meng, M V; Cooperberg, M R; Cowan, J E; Weinberg, V; Carroll, P R; Lin, D W

2014-06-01

To determine whether a variable definition of biochemical recurrence (BCR) based on clincopathologic features facilitates early identification of patients likely to suffer from disease progression. The definition of BCR after radical prostatectomy (RP) bears important implications for patient counseling and management; however, there remains a significant debate regarding the appropriate definition. The study cohort consisted of 3619 men who underwent RP for localized prostate cancer from 1989 to 2007, with data abstracted from the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry. Patients were stratified into three risk groups according to Cancer of the Prostate Risk Assessment post-Surgical (CAPRA-S) score. Three single threshold PSA cut-points for BCR were evaluated (PSA > or =0.05, > or =0.2 and > or =0.4 ng ml(-1)) as well as a variable cut-point defined by risk group. After reaching the cut-points, patients were followed for further PSA progression. The proportion of patients with BCR differed by cut-point and risk group, ranging from 7 to 37% (low risk), 22 to 58% (intermediate risk) and 60 to 86% (high risk). The positive-predictive value (PPV) for predicting further PSA progression was 49% for the PSA > or =0.05 ng ml(-1), 62% for the PSA > or =0.2 ng ml(-1), 65% for the PSA > or =0.4 ng ml(-1) and 68% for the risk-adjusted definition. Five-year progression-free survival was 39% for the risk-adjusted definition compared with 45-52% for the other definitions of BCR. These data suggest that a variable definition of BCR determined by clinicopathologic risk may improve the identification of early recurrence after RP without increasing the overdiagnosis of BCR. By using a risk-adjusted BCR definition, clinicians can better predict future PSA progression and more appropriately counsel patients regarding salvage therapies.
HMO penetration, competition, and risk-adjusted hospital mortality.

PubMed

Mukamel, D B; Zwanziger, J; Tomaszewski, K J

2001-12-01

HMOs have been shown to have an effect on the care provided directly to their enrollees. They may also influence the care provided to individuals in fee-for-service plans through a spill-over effect. The objective of this study was to investigate the associations among HMO market penetration, HMO and hospital competition, and the quality of care received by Medicare fee-for-service patients measured by risk-adjusted hospital mortality rates. The 1990 data for 1,927 hospitals in 134 metropolitan statistical areas (with five or more hospitals) included Medicare fee-for-service risk-adjusted mortality rates from the Medicare Hospital Information Reports, hospital characteristics from the American Hospital Association annual survey, and HMO market penetration and competition calculated from InterStudy and Group Health Association of America data. Statistical regression techniques were used to identify the associations between HMO market penetration, competition, and risk-adjusted mortality, controlling for other hospital characteristics and region. Higher HMO market penetration and to a lesser degree increased HMO competition were associated with better mortality outcomes for fee-for-service Medicare enrollees. Competition between hospitals did not exhibit a significant association. HMOs may have a spill-over effect on quality of care received by individuals enrolled in fee-for-service plans. These findings may be explained by a positive effect on local practice styles or a preferential selection by HMOs for areas with better hospital care.
HMO penetration, competition, and risk-adjusted hospital mortality.

PubMed Central

Mukamel, D B; Zwanziger, J; Tomaszewski, K J

2001-01-01

OBJECTIVE: HMOs have been shown to have an effect on the care provided directly to their enrollees. They may also influence the care provided to individuals in fee-for-service plans through a spill-over effect. The objective of this study was to investigate the associations among HMO market penetration, HMO and hospital competition, and the quality of care received by Medicare fee-for-service patients measured by risk-adjusted hospital mortality rates. DATA SOURCES: The 1990 data for 1,927 hospitals in 134 metropolitan statistical areas (with five or more hospitals) included Medicare fee-for-service risk-adjusted mortality rates from the Medicare Hospital Information Reports, hospital characteristics from the American Hospital Association annual survey, and HMO market penetration and competition calculated from InterStudy and Group Health Association of America data. STUDY DESIGN: Statistical regression techniques were used to identify the associations between HMO market penetration, competition, and risk-adjusted mortality, controlling for other hospital characteristics and region. PRINCIPAL FINDINGS: Higher HMO market penetration and to a lesser degree increased HMO competition were associated with better mortality outcomes for fee-for-service Medicare enrollees. Competition between hospitals did not exhibit a significant association. CONCLUSIONS: HMOs may have a spill-over effect on quality of care received by individuals enrolled in fee-for-service plans. These findings may be explained by a positive effect on local practice styles or a preferential selection by HMOs for areas with better hospital care. PMID:11775665
The HHS-HCC Risk Adjustment Model for Individual and Small Group Markets under the Affordable Care Act

PubMed Central

Kautter, John; Pope, Gregory C; Ingber, Melvin; Freeman, Sara; Patterson, Lindsey; Cohen, Michael; Keenan, Patricia

2014-01-01

Beginning in 2014, individuals and small businesses are able to purchase private health insurance through competitive Marketplaces. The Affordable Care Act (ACA) provides for a program of risk adjustment in the individual and small group markets in 2014 as Marketplaces are implemented and new market reforms take effect. The purpose of risk adjustment is to lessen or eliminate the influence of risk selection on the premiums that plans charge. The risk adjustment methodology includes the risk adjustment model and the risk transfer formula. This article is the second of three in this issue of the Review that describe the Department of Health and Human Services (HHS) risk adjustment methodology and focuses on the risk adjustment model. In our first companion article, we discuss the key issues and choices in developing the methodology. In this article, we present the risk adjustment model, which is named the HHS-Hierarchical Condition Categories (HHS-HCC) risk adjustment model. We first summarize the HHS-HCC diagnostic classification, which is the key element of the risk adjustment model. Then the data and methods, results, and evaluation of the risk adjustment model are presented. Fifteen separate models are developed. For each age group (adult, child, and infant), a model is developed for each cost sharing level (platinum, gold, silver, and bronze metal levels, as well as catastrophic plans). Evaluation of the risk adjustment models shows good predictive accuracy, both for individuals and for groups. Lastly, this article provides examples of how the model output is used to calculate risk scores, which are an input into the risk transfer formula. Our third companion paper describes the risk transfer formula. PMID:25360387
Anesthesiologist- and System-Related Risk Factors for Risk-Adjusted Pediatric Anesthesia-Related Cardiac Arrest.

PubMed

Zgleszewski, Steven E; Graham, Dionne A; Hickey, Paul R; Brustowicz, Robert M; Odegard, Kirsten C; Koka, Rahul; Seefelder, Christian; Navedo, Andres T; Randolph, Adrienne G

2016-02-01

Pediatric anesthesia-related cardiac arrest (ARCA) is an uncommon but potentially preventable adverse event. Infants and children with more severe underlying disease are at highest risk. We aimed to identify system- and anesthesiologist-related risk factors for ARCA. We analyzed a prospectively collected patient cohort data set of anesthetics administered from 2000 to 2011 to children at a large tertiary pediatric hospital. Pre-procedure systemic disease level was characterized by ASA physical status (ASA-PS). Two reviewers independently reviewed cardiac arrests and categorized their anesthesia relatedness. Factors associated with ARCA in the univariate analyses were identified for reevaluation after adjustment for patient age and ASA-PS. Cardiac arrest occurred in 142 of 276,209 anesthetics (incidence 5.1/10,000 anesthetics); 72 (2.6/10,000 anesthetics) were classified as anesthesia-related. In the univariate analyses, risk of ARCA was much higher in cardiac patients and for anesthesiologists with lower annual caseload and/or fewer annual days delivering anesthetics (all P < 0.001). Anesthesiologists with the highest academic rank and years of experience also had higher odds of ARCA (P = 0.02). After risk adjustment for ASA-PS ≥ III and age ≤ 6 months, however, the association with lower annual days delivering anesthetics remained (P = 0.03), but the other factors were no longer significant. Case-mix explained most associations between higher risk of pediatric ARCA and anesthesiologist-related variables at our institution, but the association with fewer annual days delivering anesthetics remained. Our findings highlight the need for rigorous adjustment for patient risk factors in anesthesia patient safety studies.

Ants avoid superinfections by performing risk-adjusted sanitary care.

PubMed

Konrad, Matthias; Pull, Christopher D; Metzler, Sina; Seif, Katharina; Naderlinger, Elisabeth; Grasse, Anna V; Cremer, Sylvia

2018-03-13

Being cared for when sick is a benefit of sociality that can reduce disease and improve survival of group members. However, individuals providing care risk contracting infectious diseases themselves. If they contract a low pathogen dose, they may develop low-level infections that do not cause disease but still affect host immunity by either decreasing or increasing the host's vulnerability to subsequent infections. Caring for contagious individuals can thus significantly alter the future disease susceptibility of caregivers. Using ants and their fungal pathogens as a model system, we tested if the altered disease susceptibility of experienced caregivers, in turn, affects their expression of sanitary care behavior. We found that low-level infections contracted during sanitary care had protective or neutral effects on secondary exposure to the same (homologous) pathogen but consistently caused high mortality on superinfection with a different (heterologous) pathogen. In response to this risk, the ants selectively adjusted the expression of their sanitary care. Specifically, the ants performed less grooming and more antimicrobial disinfection when caring for nestmates contaminated with heterologous pathogens compared with homologous ones. By modulating the components of sanitary care in this way the ants acquired less infectious particles of the heterologous pathogens, resulting in reduced superinfection. The performance of risk-adjusted sanitary care reveals the remarkable capacity of ants to react to changes in their disease susceptibility, according to their own infection history and to flexibly adjust collective care to individual risk.
Tamoxifen for breast cancer risk reduction: impact of alternative approaches to quality-of-life adjustment on cost-effectiveness analysis.

PubMed

Melnikow, Joy; Birch, Stephen; Slee, Christina; McCarthy, Theodore J; Helms, L Jay; Kuppermann, Miriam

2008-09-01

In cost-effectiveness analysis (CEA), the effects of health-care interventions on multiple health dimensions typically require consideration of both quantity and quality of life. To explore the impact of alternative approaches to quality-of-life adjustment using patient preferences (utilities) on the outcome of a CEA on use of tamoxifen for breast cancer risk reduction. A state transition Markov model tracked hypothetical cohorts of women who did or did not take 5 years of tamoxifen for breast cancer risk reduction. Incremental quality-adjusted effectiveness and cost-effectiveness ratios (ICERs) for models including and excluding a utility adjustment for menopausal symptoms were compared with each other and to a global utility model. Two hundred fifty-five women aged 50 and over with estimated 5-year breast cancer risk >or=1.67% participated in utility assessment interviews. Standard gamble utilities were assessed for specified tamoxifen-related health outcomes, current health, and for a global assessment of possible outcomes of tamoxifen use. Inclusion of a utility for menopausal symptoms in the outcome-specific models substantially increased the ICER; at the threshold 5-year breast cancer risk of 1.67%, tamoxifen was dominated. When a global utility for tamoxifen was used in place of outcome-specific utilities, tamoxifen was dominated under all circumstances. CEAs may be profoundly affected by the types of outcomes considered for quality-of-life adjustment and how these outcomes are grouped for utility assessment. Comparisons of ICERs across analyses must consider effects of different approaches to using utilities for quality-of-life adjustment.
Cancer Risk Estimates from Space Flight Estimated Using Yields of Chromosome Damage in Astronaut's Blood Lymphocytes

NASA Technical Reports Server (NTRS)

George, Kerry A.; Rhone, J.; Chappell, L. J.; Cucinotta, F. A.

2011-01-01

To date, cytogenetic damage has been assessed in blood lymphocytes from more than 30 astronauts before and after they participated in long-duration space missions of three months or more on board the International Space Station. Chromosome damage was assessed using fluorescence in situ hybridization whole chromosome analysis techniques. For all individuals, the frequency of chromosome damage measured within a month of return from space was higher than their preflight yield, and biodosimetry estimates were within the range expected from physical dosimetry. Follow up analyses have been performed on most of the astronauts at intervals ranging from around 6 months to many years after flight, and the cytogenetic effects of repeat long-duration missions have so far been assessed in four individuals. Chromosomal aberrations in peripheral blood lymphocytes have been validated as biomarkers of cancer risk and cytogenetic damage can therefore be used to characterize excess health risk incurred by individual crewmembers after their respective missions. Traditional risk assessment models are based on epidemiological data obtained on Earth in cohorts exposed predominantly to acute doses of gamma-rays, and the extrapolation to the space environment is highly problematic, involving very large uncertainties. Cytogenetic damage could play a key role in reducing uncertainty in risk estimation because it is incurred directly in the space environment, using specimens from the astronauts themselves. Relative cancer risks were estimated from the biodosimetry data using the quantitative approach derived from the European Study Group on Cytogenetic Biomarkers and Health database. Astronauts were categorized into low, medium, or high tertiles according to their yield of chromosome damage. Age adjusted tertile rankings were used to estimate cancer risk and results were compared with values obtained using traditional modeling approaches. Individual tertile rankings increased after space
Needs for further improvement: risk adjustment in the German health insurance system.

PubMed

Buchner, Florian; Wasem, Jürgen

2003-07-01

The German risk adjustment mechanism is used only within the public system. It was introduced in two steps, 1994 and 1995. Because of the income-related contribution, which the insured pay directly to their sickness fund, income of the insured is equalized by the mechanism and causes the biggest part of the payments among the sickness funds. On the expenditure side age, gender, disability and entitlement for sickness allowances are used as risk adjusters. The mechanism is retrospective, calculating average costs for each of the 670 risk cells defined by the risk adjusters and using these "standardized expenditures" as a base for the payment a single sickness fund gets because of its risk structure. There do still exist incentives for risk selection. The experience shows that mostly the young and healthy are willing to change sickness funds motivated by lower contribution rates. This can be used and is used for self-selection. Another cause of risk selection is regional differences. The central suggestion of an expertise on behalf of the German Ministry of Health on experiences and improvement proposals is the change to a direct modeling of morbidity.
Mental Health Risk Adjustment with Clinical Categories and Machine Learning.

PubMed

Shrestha, Akritee; Bergquist, Savannah; Montz, Ellen; Rose, Sherri

2017-12-15

To propose nonparametric ensemble machine learning for mental health and substance use disorders (MHSUD) spending risk adjustment formulas, including considering Clinical Classification Software (CCS) categories as diagnostic covariates over the commonly used Hierarchical Condition Category (HCC) system. 2012-2013 Truven MarketScan database. We implement 21 algorithms to predict MHSUD spending, as well as a weighted combination of these algorithms called super learning. The algorithm collection included seven unique algorithms that were supplied with three differing sets of MHSUD-related predictors alongside demographic covariates: HCC, CCS, and HCC + CCS diagnostic variables. Performance was evaluated based on cross-validated R 2 and predictive ratios. Results show that super learning had the best performance based on both metrics. The top single algorithm was random forests, which improved on ordinary least squares regression by 10 percent with respect to relative efficiency. CCS categories-based formulas were generally more predictive of MHSUD spending compared to HCC-based formulas. Literature supports the potential benefit of implementing a separate MHSUD spending risk adjustment formula. Our results suggest there is an incentive to explore machine learning for MHSUD-specific risk adjustment, as well as considering CCS categories over HCCs. © Health Research and Educational Trust.
Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta

USGS Publications Warehouse

Holbrook, Christopher M.; Perry, Russell W.; Brandes, Patricia L.; Adams, Noah S.

2013-01-01

In telemetry studies, premature tag failure causes negative bias in fish survival estimates because tag failure is interpreted as fish mortality. We used mark-recapture modeling to adjust estimates of fish survival for a previous study where premature tag failure was documented. High rates of tag failure occurred during the Vernalis Adaptive Management Plan’s (VAMP) 2008 study to estimate survival of fall-run Chinook salmon (Oncorhynchus tshawytscha) during migration through the San Joaquin River and Sacramento-San Joaquin Delta, California. Due to a high rate of tag failure, the observed travel time distribution was likely negatively biased, resulting in an underestimate of tag survival probability in this study. Consequently, the bias-adjustment method resulted in only a small increase in estimated fish survival when the observed travel time distribution was used to estimate the probability of tag survival. Since the bias-adjustment failed to remove bias, we used historical travel time data and conducted a sensitivity analysis to examine how fish survival might have varied across a range of tag survival probabilities. Our analysis suggested that fish survival estimates were low (95% confidence bounds range from 0.052 to 0.227) over a wide range of plausible tag survival probabilities (0.48–1.00), and this finding is consistent with other studies in this system. When tags fail at a high rate, available methods to adjust for the bias may perform poorly. Our example highlights the importance of evaluating the tag life assumption during survival studies, and presents a simple framework for evaluating adjusted survival estimates when auxiliary travel time data are available.
Risk-adjusted Outcomes of Clinically Relevant Pancreatic Fistula Following Pancreatoduodenectomy: A Model for Performance Evaluation.

PubMed

McMillan, Matthew T; Soi, Sameer; Asbun, Horacio J; Ball, Chad G; Bassi, Claudio; Beane, Joal D; Behrman, Stephen W; Berger, Adam C; Bloomston, Mark; Callery, Mark P; Christein, John D; Dixon, Elijah; Drebin, Jeffrey A; Castillo, Carlos Fernandez-Del; Fisher, William E; Fong, Zhi Ven; House, Michael G; Hughes, Steven J; Kent, Tara S; Kunstman, John W; Malleo, Giuseppe; Miller, Benjamin C; Salem, Ronald R; Soares, Kevin; Valero, Vicente; Wolfgang, Christopher L; Vollmer, Charles M

2016-08-01

To evaluate surgical performance in pancreatoduodenectomy using clinically relevant postoperative pancreatic fistula (CR-POPF) occurrence as a quality indicator. Accurate assessment of surgeon and institutional performance requires (1) standardized definitions for the outcome of interest and (2) a comprehensive risk-adjustment process to control for differences in patient risk. This multinational, retrospective study of 4301 pancreatoduodenectomies involved 55 surgeons at 15 institutions. Risk for CR-POPF was assessed using the previously validated Fistula Risk Score, and pancreatic fistulas were stratified by International Study Group criteria. CR-POPF variability was evaluated and hierarchical regression analysis assessed individual surgeon and institutional performance. There was considerable variability in both CR-POPF risk and occurrence. Factors increasing the risk for CR-POPF development included increasing Fistula Risk Score (odds ratio 1.49 per point, P < 0.00001) and octreotide (odds ratio 3.30, P < 0.00001). When adjusting for risk, performance outliers were identified at the surgeon and institutional levels. Of the top 10 surgeons (≥15 cases) for nonrisk-adjusted performance, only 6 remained in this high-performing category following risk adjustment. This analysis of pancreatic fistulas following pancreatoduodenectomy demonstrates considerable variability in both the risk and occurrence of CR-POPF among surgeons and institutions. Disparities in patient risk between providers reinforce the need for comprehensive, risk-adjusted modeling when assessing performance based on procedure-specific complications. Furthermore, beyond inherent patient risk factors, surgical decision-making influences fistula outcomes.
Log Pearson type 3 quantile estimators with regional skew information and low outlier adjustments

USGS Publications Warehouse

Griffis, V.W.; Stedinger, Jery R.; Cohn, T.A.

2004-01-01

The recently developed expected moments algorithm (EMA) [Cohn et al., 1997] does as well as maximum likelihood estimations at estimating log‐Pearson type 3 (LP3) flood quantiles using systematic and historical flood information. Needed extensions include use of a regional skewness estimator and its precision to be consistent with Bulletin 17B. Another issue addressed by Bulletin 17B is the treatment of low outliers. A Monte Carlo study compares the performance of Bulletin 17B using the entire sample with and without regional skew with estimators that use regional skew and censor low outliers, including an extended EMA estimator, the conditional probability adjustment (CPA) from Bulletin 17B, and an estimator that uses probability plot regression (PPR) to compute substitute values for low outliers. Estimators that neglect regional skew information do much worse than estimators that use an informative regional skewness estimator. For LP3 data the low outlier rejection procedure generally results in no loss of overall accuracy, and the differences between the MSEs of the estimators that used an informative regional skew are generally modest in the skewness range of real interest. Samples contaminated to model actual flood data demonstrate that estimators which give special treatment to low outliers significantly outperform estimators that make no such adjustment.
Log Pearson type 3 quantile estimators with regional skew information and low outlier adjustments

NASA Astrophysics Data System (ADS)

Griffis, V. W.; Stedinger, J. R.; Cohn, T. A.

2004-07-01

The recently developed expected moments algorithm (EMA) [, 1997] does as well as maximum likelihood estimations at estimating log-Pearson type 3 (LP3) flood quantiles using systematic and historical flood information. Needed extensions include use of a regional skewness estimator and its precision to be consistent with Bulletin 17B. Another issue addressed by Bulletin 17B is the treatment of low outliers. A Monte Carlo study compares the performance of Bulletin 17B using the entire sample with and without regional skew with estimators that use regional skew and censor low outliers, including an extended EMA estimator, the conditional probability adjustment (CPA) from Bulletin 17B, and an estimator that uses probability plot regression (PPR) to compute substitute values for low outliers. Estimators that neglect regional skew information do much worse than estimators that use an informative regional skewness estimator. For LP3 data the low outlier rejection procedure generally results in no loss of overall accuracy, and the differences between the MSEs of the estimators that used an informative regional skew are generally modest in the skewness range of real interest. Samples contaminated to model actual flood data demonstrate that estimators which give special treatment to low outliers significantly outperform estimators that make no such adjustment.
Crossover effect of spouse weekly working hours on estimated 10-years risk of cardiovascular disease.

PubMed

Kang, Mo-Yeol; Hong, Yun-Chul

2017-01-01

To investigate the association between spouse weekly working hours (SWWH) and the estimated 10-years risk of cardiovascular disease (CVD). This cross-sectional study was based on the data obtained from the Korean National Health and Nutrition Examination Survey 2007-2012. Data of 16,917 participants (8,330 husbands, 8,587 wives) were used for this analysis. The participants' clinical data were collected to estimate the 10-years risk of CVD, as well as weekly working hours. Multiple logistic regression was conducted to investigate the association between SWWH and the estimated 10-years risk of CVD. We also performed a stratified analysis according to each participant's and their spouse's employment status. Compared to those whose spouses worked 30 hours per week, estimated 10-years risk of CVD was significantly higher as SWWH increase among those whose spouses worked >30 hours per week. After adjusting for covariates, the odds ratio for high CVD risk was found to increase as SWWH increased, up to 2.52 among husbands and 2.43 among wives. We also found that the association between SWWH and the estimated 10-years risk of CVD varied according to the employment status. Analysis of each component included in the CVD appraisal model showed that SWWH had close relationship with diabetes in men, and smoking habits in women. Spouse's long working hours are associated with individual's risk of CVD in future, especially among husbands.
Adjustment for survey non‐representativeness using record‐linkage: refined estimates of alcohol consumption by deprivation in Scotland

PubMed Central

Gorman, Emma; Leyland, Alastair H.; McCartney, Gerry; Katikireddi, Srinivasa Vittal; Rutherford, Lisa; Graham, Lesley; Robinson, Mark

2017-01-01

Abstract Background and aims Analytical approaches to addressing survey non‐participation bias typically use only demographic information to improve estimates. We applied a novel methodology which uses health information from data linkage to adjust for non‐representativeness. We illustrate the method by presenting adjusted alcohol consumption estimates for Scotland. Design Data on consenting respondents to the Scottish Health Surveys (SHeSs) 1995–2010 were linked confidentially to routinely collected hospital admission and mortality records. Synthetic observations representing non‐respondents were created using general population data. Multiple imputation was performed to compute adjusted alcohol estimates given a range of assumptions about the missing data. Adjusted estimates of mean weekly consumption were additionally calibrated to per‐capita alcohol sales data. Setting Scotland. Participants 13 936 male and 18 021 female respondents to the SHeSs 1995–2010, aged 20–64 years. Measurements Weekly alcohol consumption, non‐, binge‐ and problem‐drinking. Findings Initial adjustment for non‐response resulted in estimates of mean weekly consumption that were elevated by up to 17.8% [26.5 units (18.6–34.4)] compared with corrections based solely on socio‐demographic data [22.5 (17.7–27.3)]; other drinking behaviour estimates were little changed. Under more extreme assumptions the overall difference was up to 53%, and calibrating to sales estimates resulted in up to 88% difference. Increases were especially pronounced among males in deprived areas. Conclusions The use of routinely collected health data to reduce bias arising from survey non‐response resulted in higher alcohol consumption estimates among working‐age males in Scotland, with less impact for females. This new method of bias reduction can be generalized to other surveys to improve estimates of alternative harmful behaviours. PMID:28276110
The Social Distribution of Health: Estimating Quality-Adjusted Life Expectancy in England.

PubMed

Love-Koh, James; Asaria, Miqdad; Cookson, Richard; Griffin, Susan

2015-07-01

To model the social distribution of quality-adjusted life expectancy (QALE) in England by combining survey data on health-related quality of life with administrative data on mortality. Health Survey for England data sets for 2010, 2011, and 2012 were pooled (n = 35,062) and used to model health-related quality of life as a function of sex, age, and socioeconomic status (SES). Office for National Statistics mortality rates were used to construct life tables for age-sex-SES groups. These quality-of-life and length-of-life estimates were then combined to predict QALE as a function of these characteristics. Missing data were imputed, and Monte-Carlo simulation was used to estimate standard errors. Sensitivity analysis was conducted to explore alternative regression models and measures of SES. Socioeconomic inequality in QALE at birth was estimated at 11.87 quality-adjusted life-years (QALYs), with a sex difference of 1 QALY. When the socioeconomic-sex subgroups are ranked by QALE, a differential of 10.97 QALYs is found between the most and least healthy quintile groups. This differential can be broken down into a life expectancy difference of 7.28 years and a quality-of-life adjustment of 3.69 years. The methods proposed in this article refine simple binary quality-adjustment measures such as the widely used disability-free life expectancy, providing a more accurate picture of overall health inequality in society than has hitherto been available. The predictions also lend themselves well to the task of evaluating the health inequality impact of interventions in the context of cost-effectiveness analysis. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Apples to apples: the origin and magnitude of differences in asbestos cancer risk estimates derived using varying protocols.

PubMed

Berman, D Wayne

2011-08-01

Given that new protocols for assessing asbestos-related cancer risk have recently been published, questions arise concerning how they compare to the "IRIS" protocol currently used by regulators. The newest protocols incorporate findings from 20 additional years of literature. Thus, differences between the IRIS and newer Berman and Crump protocols are examined to evaluate whether these protocols can be reconciled. Risks estimated by applying these protocols to real exposure data from both laboratory and field studies are also compared to assess the relative health protectiveness of each protocol. The reliability of risks estimated using the two protocols are compared by evaluating the degree with which each potentially reproduces the known epidemiology study risks. Results indicate that the IRIS and Berman and Crump protocols can be reconciled; while environment-specific variation within fiber type is apparently due primarily to size effects (not addressed by IRIS), the 10-fold (average) difference between amphibole asbestos risks estimated using each protocol is attributable to an arbitrary selection of the lowest of available mesothelioma potency factors in the IRIS protocol. Thus, the IRIS protocol may substantially underestimate risk when exposure is primarily to amphibole asbestos. Moreover, while the Berman and Crump protocol is more reliable than the IRIS protocol overall (especially for predicting amphibole risk), evidence is presented suggesting a new fiber-size-related adjustment to the Berman and Crump protocol may ultimately succeed in reconciling the entire epidemiology database. However, additional data need to be developed before the performance of the adjusted protocol can be fully validated. © 2011 Society for Risk Analysis.
48 CFR 215.404-71-3 - Contract type risk and working capital adjustment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... provisions for performance-based payments, do not compute a working capital adjustment. (d) Evaluation... working capital adjustment. 215.404-71-3 Section 215.404-71-3 Federal Acquisition Regulations System... CONTRACTING BY NEGOTIATION Contract Pricing 215.404-71-3 Contract type risk and working capital adjustment. (a...
Health-based risk adjustment: is inpatient and outpatient diagnostic information sufficient?

PubMed

Lamers, L M

Adequate risk adjustment is critical to the success of market-oriented health care reforms in many countries. Currently used risk adjusters based on demographic and diagnostic cost groups (DCGs) do not reflect expected costs accurately. This study examines the simultaneous predictive accuracy of inpatient and outpatient morbidity measures and prior costs. DCGs, pharmacy cost groups (PCGs), and prior year's costs improve the predictive accuracy of the demographic model substantially. DCGs and PCGs seem complementary in their ability to predict future costs. However, this study shows that the combination of DCGs and PCGs still leaves room for cream skimming.
A case-control study estimating accident risk for alcohol, medicines and illegal drugs.

PubMed

Kuypers, Kim Paula Colette; Legrand, Sara-Ann; Ramaekers, Johannes Gerardus; Verstraete, Alain Gaston

2012-01-01

The aim of the present study was to assess the risk of having a traffic accident after using alcohol, single drugs, or a combination, and to determine the concentrations at which this risk is significantly increased. A population-based case-control study was carried out, collecting whole blood samples of both cases and controls, in which a number of drugs were detected. The risk of having an accident when under the influence of drugs was estimated using logistic regression adjusting for gender, age and time period of accident (cases)/sampling (controls). The main outcome measures were odds ratio (OR) for accident risk associated with single and multiple drug use. In total, 337 cases (negative: 176; positive: 161) and 2726 controls (negative: 2425; positive: 301) were included in the study. Main findings were that 1) alcohol in general (all the concentrations together) caused an elevated crash risk; 2) cannabis in general also caused an increase in accident risk; at a cut-off of 2 ng/mL THC the risk of having an accident was four times the risk associated with the lowest THC concentrations; 3) when ranking the adjusted OR from lowest to highest risk, alcohol alone or in combination with other drugs was related to a very elevated crash risk, with the highest risk for stimulants combined with sedatives. The study demonstrated a concentration-dependent crash risk for THC positive drivers. Alcohol and alcohol-drug combinations are by far the most prevalent substances in drivers and subsequently pose the largest risk in traffic, both in terms of risk and scope.
Adjustment of Children Born to Teenage Mothers: The Contribution of Risk and Protective Factors.

ERIC Educational Resources Information Center

Dubow, Eric F.; Luster, Tom

1990-01-01

Examined contribution of risk and protective factors in adjustment of 721 children, age 8-15, born to teenage mothers. Results showed that exposure to increasing number of risk factors (poverty, urban residence, mother's self-esteem) was associated with greater vulnerability to adjustment problems, while protective factors (intelligence,…
On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.

PubMed

Tang, Yongqiang

2017-12-01

Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.
A risk-adjusted O-E CUSUM with monitoring bands for monitoring medical outcomes.

PubMed

Sun, Rena Jie; Kalbfleisch, John D

2013-03-01

In order to monitor a medical center's survival outcomes using simple plots, we introduce a risk-adjusted Observed-Expected (O-E) Cumulative SUM (CUSUM) along with monitoring bands as decision criterion.The proposed monitoring bands can be used in place of a more traditional but complicated V-shaped mask or the simultaneous use of two one-sided CUSUMs. The resulting plot is designed to simultaneously monitor for failure time outcomes that are "worse than expected" or "better than expected." The slopes of the O-E CUSUM provide direct estimates of the relative risk (as compared to a standard or expected failure rate) for the data being monitored. Appropriate rejection regions are obtained by controlling the false alarm rate (type I error) over a period of given length. Simulation studies are conducted to illustrate the performance of the proposed method. A case study is carried out for 58 liver transplant centers. The use of CUSUM methods for quality improvement is stressed. Copyright © 2013, The International Biometric Society.
Risk Adjustment for Medicare Total Knee Arthroplasty Bundled Payments.

PubMed

Clement, R Carter; Derman, Peter B; Kheir, Michael M; Soo, Adrianne E; Flynn, David N; Levin, L Scott; Fleisher, Lee

2016-09-01

The use of bundled payments is growing because of their potential to align providers and hospitals on the goal of cost reduction. However, such gain sharing could incentivize providers to "cherry-pick" more profitable patients. Risk adjustment can prevent this unintended consequence, yet most bundling programs include minimal adjustment techniques. This study was conducted to determine how bundled payments for total knee arthroplasty (TKA) should be adjusted for risk. The authors collected financial data for all Medicare patients (age≥65 years) undergoing primary unilateral TKA at an academic center over a period of 2 years (n=941). Multivariate regression was performed to assess the effect of patient factors on the costs of acute inpatient care, including unplanned 30-day readmissions. This analysis mirrors a bundling model used in the Medicare Bundled Payments for Care Improvement initiative. Increased age, American Society of Anesthesiologists (ASA) class, and the presence of a Medicare Major Complications/Comorbid Conditions (MCC) modifier (typically representing major complications) were associated with increased costs (regression coefficients, $57 per year; $729 per ASA class beyond I; and $3122 for patients meeting MCC criteria; P=.003, P=.001, and P<.001, respectively). Differences in costs were not associated with body mass index, sex, or race. If the results are generalizable, Medicare bundled payments for TKA encompassing acute inpatient care should be adjusted upward by the stated amounts for older patients, those with elevated ASA class, and patients meeting MCC criteria. This is likely an underestimate for many bundling models, including the Comprehensive Care for Joint Replacement program, incorporating varying degrees of postacute care. Failure to adjust for factors that affect costs may create adverse incentives, creating barriers to care for certain patient populations. [Orthopedics. 2016; 39(5):e911-e916.]. Copyright 2016, SLACK Incorporated.

Risk selection and risk adjustment: improving insurance in the individual and small group markets.

PubMed

Baicker, Katherine; Dow, William H

2009-01-01

Insurance market reforms face the key challenge of addressing the threat that risk selection poses to the availability, of stable, high-value insurance policies that provide long-term risk protection. Many of the strategies in use today fail to address this breakdown in risk pooling, and some even exacerbate it. Flexible risk adjustment schemes are a promising avenue for promoting market stability and limiting insurer cream-skimming, potentially providing greater benefits at lower cost. Reforms intended to increase insurance coverage and the value of care delivered will be much more effective if implemented in conjunction with policies that address these fundamental selection issues.
A comparative evaluation of risk-adjustment models for benchmarking amputation-free survival after lower extremity bypass.

PubMed

Simons, Jessica P; Goodney, Philip P; Flahive, Julie; Hoel, Andrew W; Hallett, John W; Kraiss, Larry W; Schanzer, Andres

2016-04-01

Providing patients and payers with publicly reported risk-adjusted quality metrics for the purpose of benchmarking physicians and institutions has become a national priority. Several prediction models have been developed to estimate outcomes after lower extremity revascularization for critical limb ischemia, but the optimal model to use in contemporary practice has not been defined. We sought to identify the highest-performing risk-adjustment model for amputation-free survival (AFS) at 1 year after lower extremity bypass (LEB). We used the national Society for Vascular Surgery Vascular Quality Initiative (VQI) database (2003-2012) to assess the performance of three previously validated risk-adjustment models for AFS. The Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL), Finland National Vascular (FINNVASC) registry, and the modified Project of Ex-vivo vein graft Engineering via Transfection III (PREVENT III [mPIII]) risk scores were applied to the VQI cohort. A novel model for 1-year AFS was also derived using the VQI data set and externally validated using the PIII data set. The relative discrimination (Harrell c-index) and calibration (Hosmer-May goodness-of-fit test) of each model were compared. Among 7754 patients in the VQI who underwent LEB for critical limb ischemia, the AFS was 74% at 1 year. Each of the previously published models for AFS demonstrated similar discriminative performance: c-indices for BASIL, FINNVASC, mPIII were 0.66, 0.60, and 0.64, respectively. The novel VQI-derived model had improved discriminative ability with a c-index of 0.71 and appropriate generalizability on external validation with a c-index of 0.68. The model was well calibrated in both the VQI and PIII data sets (goodness of fit P = not significant). Currently available prediction models for AFS after LEB perform modestly when applied to national contemporary VQI data. Moreover, the performance of each model was inferior to that of the novel VQI-derived model
Association of surgical care improvement project infection-related process measure compliance with risk-adjusted outcomes: implications for quality measurement.

PubMed

Ingraham, Angela M; Cohen, Mark E; Bilimoria, Karl Y; Dimick, Justin B; Richards, Karen E; Raval, Mehul V; Fleisher, Lee A; Hall, Bruce L; Ko, Clifford Y

2010-12-01

Facility-level process measure adherence is being publicly reported. However, the association between measure adherence and surgical outcomes is not well-established. Our objective was to determine the degree to which Surgical Care Improvement Project (SCIP) process measures are associated with American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) risk-adjusted outcomes. This cross-sectional study included hospitals participating in the ACS NSQIP and SCIP (n = 200). ACS NSQIP outcomes (30-day overall morbidity, serious morbidity, surgical site infections [SSI], and mortality) and adherence to SCIP SSI-related process measures (from the Hospital Compare database) were collected from January 1, 2008, through December 31, 2008. Hospital-level correlation coefficients between compliance with 4 process measures (ie, antibiotic administration within 1 hour before incision [SCIP-1]; appropriate antibiotic prophylaxis [SCIP-2]; antibiotic discontinuation within 24 hours after surgery [SCIP-3]; and appropriate hair removal [SCIP 6]) and 4 risk-adjusted outcomes were calculated. Regression analyses estimated the contribution of process measure adherence to risk-adjusted outcomes. Of 211 ACS NSQIP hospitals, 95% had data reported by Hospital Compare. Depending on the measure, hospital-level compliance ranged from 60% to 100%. Of the 16 correlations, 15 demonstrated nonsignificant associations with risk-adjusted outcomes. The exception was the relationship between SCIP-2 and SSI (p = 0.004). SCIP-1 demonstrated an intriguing but nonsignificant relationship with SSI (p = 0.08) and overall morbidity (p = 0.08). Although adherence to SCIP-2 was a significant predictor of risk-adjusted SSI (p < 0.0001) and overall morbidity (p < 0.0001), inclusion of compliance for SCIP-1 and SCIP-2 caused only slight improvement in model quality. Better adherence to infection-related process measures over the observed range was not significantly associated with
Inappropriate use of payment weights to risk adjust readmission rates.

PubMed

Fuller, Richard L; Goldfield, Norbert I; Averill, Richard F; Hughes, John S

2012-01-01

In this article, the authors demonstrate that the use of relative weights, as incorporated within the National Quality Forum-endorsed PacifiCare readmission measure, is inappropriate for risk adjusting rates of hospital readmission.
Real time monitoring of risk-adjusted paediatric cardiac surgery outcomes using variable life-adjusted display: implementation in three UK centres

PubMed Central

Pagel, Christina; Utley, Martin; Crowe, Sonya; Witter, Thomas; Anderson, David; Samson, Ray; McLean, Andrew; Banks, Victoria; Tsang, Victor; Brown, Katherine

2013-01-01

Objective To implement routine in-house monitoring of risk-adjusted 30-day mortality following paediatric cardiac surgery. Design Collaborative monitoring software development and implementation in three specialist centres. Patients and methods Analyses incorporated 2 years of data routinely audited by the National Institute of Cardiac Outcomes Research (NICOR). Exclusion criteria were patients over 16 or undergoing non-cardiac or only catheter procedures. We applied the partial risk adjustment in surgery (PRAiS) risk model for death within 30 days following surgery and generated variable life-adjusted display (VLAD) charts for each centre. These were shared with each clinical team and feedback was sought. Results Participating centres were Great Ormond Street Hospital, Evelina Children's Hospital and The Royal Hospital for Sick Children in Glasgow. Data captured all procedures performed between 1 January 2010 and 31 December 2011. This incorporated 2490 30-day episodes of care, 66 of which were associated with a death within 30 days.The VLAD charts generated for each centre displayed trends in outcomes benchmarked to recent national outcomes. All centres ended the 2-year period within four deaths from what would be expected. The VLAD charts were shared in multidisciplinary meetings and clinical teams reported that they were a useful addition to existing quality assurance initiatives. Each centre is continuing to use the prototype software to monitor their in-house surgical outcomes. Conclusions Timely and routine monitoring of risk-adjusted mortality following paediatric cardiac surgery is feasible. Close liaison with hospital data managers as well as clinicians was crucial to the success of the project. PMID:23564473
Identifying Military and Combat-Specific Risk Factors for Child Adjustment: Comparing High and Low Risk Military Families and Civilian Families

DTIC Science & Technology

2016-08-01

Award Number: W81XWH-12-2-0034 TITLE: Identifying Military and Combat-Specific Risk Factors for Child Adjustment: Comparing High and Low Risk...2. REPORT TYPE Final 3. DATES COVERED (From - To) 15May2012 - 31Aug2016 Identifying Military and Combat-Specific Risk Factors for Child Adjustment...deployment and has a child between the age of 3 and 7 and comparison groups of civilain single parent families (N=200) and civilian dual parent
Food-Frequency Questionnaire Based Estimates of Total Antioxidant Capacity and Risk of Non-Hodgkin Lymphoma

PubMed Central

Holtan, Shernan G.; O’Connor, Helen M.; Fredericksen, Zachary S.; Liebow, Mark; Thompson, Carrie A.; Macon, William R.; Micallef, Ivana N.; Wang, Alice H.; Slager, Susan L.; Habermann, Thomas M.; Call, Timothy G.; Cerhan, James R.

2011-01-01

Antioxidants, primarily from fruits and vegetables, have been hypothesized to protect against non-Hodgkin lymphoma (NHL). The Oxygen Radical Absorbance Capacity (ORAC) assay, which measures total antioxidant capacity of individual foods and accounts for synergism, can be estimated using a food-frequency questionnaire (FFQ). We tested the hypothesis that higher intake of antioxidant nutrients from foods, supplements, and FFQ-based ORAC values are associated with a lower risk of NHL in a clinic-based study of 603 incident cases and 1007 frequency-matched controls. Diet was assessed with a 128-item FFQ. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals adjusted for age, sex, residence and total energy. Dietary intake of α-tocopherol (OR=0.50; p-trend=0.0002), β-carotene (OR=0.58; p-trend=0.0005), lutein/zeaxanthin (OR=0.62; p-trend=0.005), zinc (OR=0.54; p-trend=0.003) and chromium (OR=0.68; p-trend=0.032) were inversely associated with NHL risk. Inclusion of supplement use had little impact on these associations. Total vegetables (OR=0.52; p-trend<0.0001), particularly green leafy (OR=0.52; p-trend<0.0001) and cruciferous (OR=0.68; p-trend=0.045) vegetables, were inversely associated with NHL risk. NHL risk was inversely associated with both hydrophilic ORAC (OR=0.61, p-trend=0.003) and lipophilic ORAC (OR=0.48, p-trend=0.0002), although after simultaneous adjustment for other antioxidants or total vegetables only the association for lipophilic ORAC remained significant. There was no striking heterogeneity in results across the common NHL subtypes. Higher antioxidant intake as estimated by the FFQ-ORAC, particularly the lipophilic component, was associated with a lower NHL risk after accounting for other antioxidant nutrients and vegetable intake, supporting this as potentially useful summary measure of total antioxidant intake. PMID:22038870
Association Between Sitting Time and Cardiometabolic Risk Factors After Adjustment for Cardiorespiratory Fitness, Cooper Center Longitudinal Study, 2010–2013

PubMed Central

Shuval, Kerem; Balasubramanian, Bijal A.; Kendzor, Darla E.; Radford, Nina B.; DeFina, Laura F.; Gabriel, Kelley Pettee

2016-01-01

Introduction Objective estimates, based on waist-worn accelerometers, indicate that adults spend over half their day (55%) in sedentary behaviors. Our study examined the association between sitting time and cardiometabolic risk factors after adjustment for cardiorespiratory fitness (CRF). Methods A cross-sectional analysis was conducted with 4,486 men and 1,845 women who reported daily estimated sitting time, had measures for adiposity, blood lipids, glucose, and blood pressure, and underwent maximal stress testing. We used a modeling strategy using logistic regression analysis to assess CRF as a potential effect modifier and to control for potential confounding effects of CRF. Results Men who sat almost all of the time (about 100%) were more likely to be obese whether defined by waist girth (OR, 2.61; 95% CI, 1.25–5.47) or percentage of body fat (OR, 3.33; 95% CI, 1.35–8.20) than were men who sat almost none of the time (about 0%). Sitting time was not significantly associated with other cardiometabolic risk factors after adjustment for CRF level. For women, no significant associations between sitting time and cardiometabolic risk factors were observed after adjustment for CRF and other covariates. Conclusion As health professionals struggle to find ways to combat obesity and its health effects, reducing sitting time can be an initial step in a total physical activity plan that includes strategies to reduce sedentary time through increases in physical activity among men. In addition, further research is needed to elucidate the relationships between sitting time and CRF for women as well as the underlying mechanisms involved in these relationships. PMID:28033088
Suboptimal decision making by children with ADHD in the face of risk: Poor risk adjustment and delay aversion rather than general proneness to taking risks.

PubMed

Sørensen, Lin; Sonuga-Barke, Edmund; Eichele, Heike; van Wageningen, Heidi; Wollschlaeger, Daniel; Plessen, Kerstin Jessica

2017-02-01

Suboptimal decision making in the face of risk (DMR) in children with attention-deficit hyperactivity disorder (ADHD) may be mediated by deficits in a number of different neuropsychological processes. We investigated DMR in children with ADHD using the Cambridge Gambling Task (CGT) to distinguish difficulties in adjusting to changing probabilities of choice outcomes (so-called risk adjustment) from general risk proneness, and to distinguish these 2 processes from delay aversion (the tendency to choose the least delayed option) and impairments in the ability to reflect on choice options. Based on previous research, we predicted that suboptimal performance on this task in children with ADHD would be primarily relate to problems with risk adjustment and delay aversion rather than general risk proneness. Drug naïve children with ADHD (n = 36), 8 to 12 years, and an age-matched group of typically developing children (n = 34) performed the CGT. As predicted, children with ADHD were not more prone to making risky choices (i.e., risk proneness). However, they had difficulty adjusting to changing risk levels and were more delay aversive-with these 2 effects being correlated. Our findings add to the growing body of evidence that children with ADHD do not favor risk taking per se when performing gambling tasks, but rather may lack the cognitive skills or motivational style to appraise changing patterns of risk effectively. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Estimation of the Standardized Risk Difference and Ratio in a Competing Risks Framework: Application to Injection Drug Use and Progression to AIDS After Initiation of Antiretroviral Therapy

PubMed Central

Cole, Stephen R.; Lau, Bryan; Eron, Joseph J.; Brookhart, M. Alan; Kitahata, Mari M.; Martin, Jeffrey N.; Mathews, William C.; Mugavero, Michael J.; Cole, Stephen R.; Brookhart, M. Alan; Lau, Bryan; Eron, Joseph J.; Kitahata, Mari M.; Martin, Jeffrey N.; Mathews, William C.; Mugavero, Michael J.

2015-01-01

There are few published examples of absolute risk estimated from epidemiologic data subject to censoring and competing risks with adjustment for multiple confounders. We present an example estimating the effect of injection drug use on 6-year risk of acquired immunodeficiency syndrome (AIDS) after initiation of combination antiretroviral therapy between 1998 and 2012 in an 8-site US cohort study with death before AIDS as a competing risk. We estimate the risk standardized to the total study sample by combining inverse probability weights with the cumulative incidence function; estimates of precision are obtained by bootstrap. In 7,182 patients (83% male, 33% African American, median age of 38 years), we observed 6-year standardized AIDS risks of 16.75% among 1,143 injection drug users and 12.08% among 6,039 nonusers, yielding a standardized risk difference of 4.68 (95% confidence interval: 1.27, 8.08) and a standardized risk ratio of 1.39 (95% confidence interval: 1.12, 1.72). Results may be sensitive to the assumptions of exposure-version irrelevance, no measurement bias, and no unmeasured confounding. These limitations suggest that results be replicated with refined measurements of injection drug use. Nevertheless, estimating the standardized risk difference and ratio is straightforward, and injection drug use appears to increase the risk of AIDS. PMID:24966220
Gauge-adjusted rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Rieckermann, Jörg; Bareš, Vojtěch

2017-01-01

Increasing urbanization makes it more and more important to have accurate stormwater runoff predictions, especially with potentially severe weather and climatic changes on the horizon. Such stormwater predictions in turn require reliable rainfall information. Especially for urban centres, the problem is that the spatial and temporal resolution of rainfall observations should be substantially higher than commonly provided by weather services with their standard rainfall monitoring networks. Commercial microwave links (CMLs) are non-traditional sensors, which have been proposed about a decade ago as a promising solution. CMLs are line-of-sight radio connections widely used by operators of mobile telecommunication networks. They are typically very dense in urban areas and can provide path-integrated rainfall observations at sub-minute resolution. Unfortunately, quantitative precipitation estimates (QPEs) from CMLs are often highly biased due to several epistemic uncertainties, which significantly limit their usability. In this manuscript we therefore suggest a novel method to reduce this bias by adjusting QPEs to existing rain gauges. The method has been specifically designed to produce reliable results even with comparably distant rain gauges or cumulative observations. This eliminates the need to install reference gauges and makes it possible to work with existing information. First, the method is tested on data from a dedicated experiment, where a CML has been specifically set up for rainfall monitoring experiments, as well as operational CMLs from an existing cellular network. Second, we assess the performance for several experimental layouts of ground truth from rain gauges (RGs) with different spatial and temporal resolutions. The results suggest that CMLs adjusted by RGs with a temporal aggregation of up to 1 h (i) provide precise high-resolution QPEs (relative error < 7 %, Nash-Sutcliffe efficiency coefficient > 0.75) and (ii) that the
Finasteride Does Not Increase the Risk of High-grade Prostate Cancer: A Bias-adjusted Modeling Approach

PubMed Central

Redman, Mary W.; Tangen, Catherine M.; Goodman, Phyllis J.; Parnes, Howard; Ford, Leslie G.; Lucia, M. Scott; Coltman, Charles A.; Thompson, Ian M.

2010-01-01

The Prostate Cancer Prevention Trial found that seven years of administration of finasteride reduced the risk of prostate cancer by 25% but with an apparent increased risk of high grade disease. Subsequent analyses found that finasteride affects cancer detection and improves accuracy of tumor grading at biopsy. We herein estimate the impact of finasteride on the risk of overall and high grade prostate cancer, accounting for these biases. Study endpoints (biopsy-proven cancer or a 7-year end-of-study biopsy) were available in 10,182 of 15,990 subjects assessable for 7-year status and grading information from 500 subjects diagnosed with cancer who underwent radical prostatectomy. Prostate cancer was observed in 22.9% (4.8% with high grade) in the placebo group versus 16.6% (5.8% with high grade) in the finasteride group. In this bias-adjusted analysis, the estimated rates are 21.1% (4.2%) and 14.7% (4.8%), respectively, a 30% risk reduction in prostate cancer (RR =0.70 (95% confidence interval (CI) =0.64-0.76, p<0.0001) and a non-significant 14% increase in high grade cancer (RR=1.14 (95% CI = (0.96-1.35), p=0.12) with finasteride. Incorporating the prostatectomy data, estimated rates of high grade cancers are 8.2% (placebo) versus 6.0% (finasteride), a 27% risk reduction (RR = 0.73 (95% CI=0.56-0.96, p=0.02)) with finasteride. While the observed risk of high grade disease is greater with finasteride, this appears to be through facilitated diagnosis, primarily due to increased biopsy sensitivity. Men undergoing regular prostate cancer screening or who express an interest in cancer prevention should be informed of this prevention opportunity. PMID:19138953
A Case-Control Study Estimating Accident Risk for Alcohol, Medicines and Illegal Drugs

PubMed Central

Kuypers, Kim Paula Colette; Legrand, Sara-Ann; Ramaekers, Johannes Gerardus; Verstraete, Alain Gaston

2012-01-01

Background The aim of the present study was to assess the risk of having a traffic accident after using alcohol, single drugs, or a combination, and to determine the concentrations at which this risk is significantly increased. Methods A population-based case-control study was carried out, collecting whole blood samples of both cases and controls, in which a number of drugs were detected. The risk of having an accident when under the influence of drugs was estimated using logistic regression adjusting for gender, age and time period of accident (cases)/sampling (controls). The main outcome measures were odds ratio (OR) for accident risk associated with single and multiple drug use. In total, 337 cases (negative: 176; positive: 161) and 2726 controls (negative: 2425; positive: 301) were included in the study. Results Main findings were that 1) alcohol in general (all the concentrations together) caused an elevated crash risk; 2) cannabis in general also caused an increase in accident risk; at a cut-off of 2 ng/mL THC the risk of having an accident was four times the risk associated with the lowest THC concentrations; 3) when ranking the adjusted OR from lowest to highest risk, alcohol alone or in combination with other drugs was related to a very elevated crash risk, with the highest risk for stimulants combined with sedatives. Conclusion The study demonstrated a concentration-dependent crash risk for THC positive drivers. Alcohol and alcohol-drug combinations are by far the most prevalent substances in drivers and subsequently pose the largest risk in traffic, both in terms of risk and scope. PMID:22952694
Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment.

PubMed

Rosenberg, Barry L; Kellar, Joshua A; Labno, Anna; Matheson, David H M; Ringel, Michael; VonAchen, Paige; Lesser, Richard I; Li, Yue; Dimick, Justin B; Gawande, Atul A; Larsson, Stefan H; Moses, Hamilton

2016-01-01

Despite numerous studies of geographic variation in healthcare cost and utilization at the local, regional, and state levels across the U.S., a comprehensive characterization of geographic variation in outcomes has not been published. Our objective was to quantify variation in US health outcomes in an all-payer population before and after risk-adjustment. We used information from 16 independent data sources, including 22 million all-payer inpatient admissions from the Healthcare Cost and Utilization Project (which covers regions where 50% of the U.S. population lives) to analyze 24 inpatient mortality, inpatient safety, and prevention outcomes. We compared outcome variation at state, hospital referral region, hospital service area, county, and hospital levels. Risk-adjusted outcomes were calculated after adjusting for population factors, co-morbidities, and health system factors. Even after risk-adjustment, there exists large geographical variation in outcomes. The variation in healthcare outcomes exceeds the well publicized variation in US healthcare costs. On average, we observed a 2.1-fold difference in risk-adjusted mortality outcomes between top- and bottom-decile hospitals. For example, we observed a 2.3-fold difference for risk-adjusted acute myocardial infarction inpatient mortality. On average a 10.2-fold difference in risk-adjusted patient safety outcomes exists between top and bottom-decile hospitals, including an 18.3-fold difference for risk-adjusted Central Venous Catheter Bloodstream Infection rates. A 3.0-fold difference in prevention outcomes exists between top- and bottom-decile counties on average; including a 2.2-fold difference for risk-adjusted congestive heart failure admission rates. The population, co-morbidity, and health system factors accounted for a range of R2 between 18-64% of variability in mortality outcomes, 3-39% of variability in patient safety outcomes, and 22-70% of variability in prevention outcomes. The amount of variability
The Experience of Risk-Adjusted Capitation Payment for Family Physicians in Iran: A Qualitative Study.

PubMed

Esmaeili, Reza; Hadian, Mohammad; Rashidian, Arash; Shariati, Mohammad; Ghaderi, Hossien

2016-04-01

When a country's health system is faced with fundamental flaws that require the redesign of financing and service delivery, primary healthcare payment systems are often reformed. This study was conducted with the purpose of exploring the experiences of risk-adjusted capitation payment of urban family physicians in Iran when it comes to providing primary health care (PHC). This is a qualitative study using the framework method. Data were collected via digitally audio-recorded semi-structured interviews with 24 family physicians and 5 executive directors in two provinces of Iran running the urban family physician pilot program. The participants were selected using purposive and snowball sampling. The codes were extracted using inductive and deductive methods. Regarding the effects of risk-adjusted capitation on the primary healthcare setting, five themes with 11 subthemes emerged, including service delivery, institutional structure, financing, people's behavior, and the challenges ahead. Our findings indicated that the health system is enjoying some major changes in the primary healthcare setting through the implementation of risk-adjusted capitation payment. With regard to the current challenges in Iran's health system, using risk-adjusted capitation as a primary healthcare payment system can lead to useful changes in the health system's features. However, future research should focus on the development of the risk-adjusted capitation model.
Sensitivity analysis for mistakenly adjusting for mediators in estimating total effect in observational studies.

PubMed

Wang, Tingting; Li, Hongkai; Su, Ping; Yu, Yuanyuan; Sun, Xiaoru; Liu, Yi; Yuan, Zhongshang; Xue, Fuzhong

2017-11-20

In observational studies, epidemiologists often attempt to estimate the total effect of an exposure on an outcome of interest. However, when the underlying diagram is unknown and limited knowledge is available, dissecting bias performances is essential to estimating the total effect of an exposure on an outcome when mistakenly adjusting for mediators under logistic regression. Through simulation, we focused on six causal diagrams concerning different roles of mediators. Sensitivity analysis was conducted to assess the bias performances of varying across exposure-mediator effects and mediator-outcome effects when adjusting for the mediator. Based on the causal relationships in the real world, we compared the biases of varying across the effects of exposure-mediator with those of varying across the effects of mediator-outcome when adjusting for the mediator. The magnitude of the bias was defined by the difference between the estimated effect (using logistic regression) and the total effect of the exposure on the outcome. In four scenarios (a single mediator, two series mediators, two independent parallel mediators or two correlated parallel mediators), the biases of varying across the effects of exposure-mediator were greater than those of varying across the effects of mediator-outcome when adjusting for the mediator. In contrast, in two other scenarios (a single mediator or two independent parallel mediators in the presence of unobserved confounders), the biases of varying across the effects of exposure-mediator were less than those of varying across the effects of mediator-outcome when adjusting for the mediator. The biases were more sensitive to the variation of effects of exposure-mediator than the effects of mediator-outcome when adjusting for the mediator in the absence of unobserved confounders, while the biases were more sensitive to the variation of effects of mediator-outcome than those of exposure-mediator in the presence of an unobserved confounder. �
Decreased risk adjusted 30-day mortality for hospital admitted injuries: a multi-centre longitudinal study.

PubMed

Larsen, Robert; Bäckström, Denise; Fredrikson, Mats; Steinvall, Ingrid; Gedeborg, Rolf; Sjoberg, Folke

2018-04-03

The interpretation of changes in injury-related mortality over time requires an understanding of changes in the incidence of the various types of injury, and adjustment for their severity. Our aim was to investigate changes over time in incidence of hospital admission for injuries caused by falls, traffic incidents, or assaults, and to assess the risk-adjusted short-term mortality for these patients. All patients admitted to hospital with injuries caused by falls, traffic incidents, or assaults during the years 2001-11 in Sweden were identified from the nationwide population-based Patient Registry. The trend in mortality over time for each cause of injury was adjusted for age, sex, comorbidity and severity of injury as classified from the International Classification of diseases, version 10 Injury Severity Score (ICISS). Both the incidence of fall (689 to 636/100000 inhabitants: p = 0.047, coefficient - 4.71) and traffic related injuries (169 to 123/100000 inhabitants: p < 0.0001, coefficient - 5.37) decreased over time while incidence of assault related injuries remained essentially unchanged during the study period. There was an overall decrease in risk-adjusted 30-day mortality in all three groups (OR 1.00; CI95% 0.99-1.00). Decreases in traffic (OR 0.95; 95% CI 0.93 to 0.97) and assault (OR 0.93; 95% CI 0.87 to 0.99) related injuries was significant whereas falls were not during this 11-year period. Risk-adjustment is a good way to use big materials to find epidemiological changes. However after adjusting for age, year, sex and risk we find that a possible factor is left in the pre- and/or in-hospital care. The decrease in risk-adjusted mortality may suggest changes over time in pre- and/or in-hospital care. A non-significantdecrease in risk-adjusted mortality was registered for falls, which may indicate that low-energy trauma has not benefited for the increased survivability as much as high-energy trauma, ie traffic- and assault related
Estimates of over-diagnosis of breast cancer due to population-based mammography screening in South Australia after adjustment for lead time effects.

PubMed

Beckmann, Kerri; Duffy, Stephen W; Lynch, John; Hiller, Janet; Farshid, Gelareh; Roder, David

2015-09-01

To estimate over-diagnosis due to population-based mammography screening using a lead time adjustment approach, with lead time measures based on symptomatic cancers only. Women aged 40-84 in 1989-2009 in South Australia eligible for mammography screening. Numbers of observed and expected breast cancer cases were compared, after adjustment for lead time. Lead time effects were modelled using age-specific estimates of lead time (derived from interval cancer rates and predicted background incidence, using maximum likelihood methods) and screening sensitivity, projected background breast cancer incidence rates (in the absence of screening), and proportions screened, by age and calendar year. Lead time estimates were 12, 26, 43 and 53 months, for women aged 40-49, 50-59, 60-69 and 70-79 respectively. Background incidence rates were estimated to have increased by 0.9% and 1.2% per year for invasive and all breast cancer. Over-diagnosis among women aged 40-84 was estimated at 7.9% (0.1-12.0%) for invasive cases and 12.0% (5.7-15.4%) when including ductal carcinoma in-situ (DCIS). We estimated 8% over-diagnosis for invasive breast cancer and 12% inclusive of DCIS cancers due to mammography screening among women aged 40-84. These estimates may overstate the extent of over-diagnosis if the increasing prevalence of breast cancer risk factors has led to higher background incidence than projected. © The Author(s) 2015.
Risk-Adjustment Simulation: Plans May Have Incentives To Distort Mental Health And Substance Use Coverage

PubMed Central

Montz, Ellen; Layton, Tim; Busch, Alisa B.; Ellis, Randall P.; Rose, Sherri; McGuire, Thomas G.

2016-01-01

Under the Affordable Care Act, the risk-adjustment program is designed to compensate health plans for enrolling people with poorer health status so that plans compete on cost and quality rather than the avoidance of high-cost individuals. This study examined health plan incentives to limit covered services for mental health and substance use disorders under the risk-adjustment system used in the health insurance Marketplaces. Through a simulation of the program on a population constructed to reflect Marketplace enrollees, we analyzed the cost consequences for plans enrolling people with mental health and substance use disorders. Our assessment points to systematic underpayment to plans for people with these diagnoses. We document how Marketplace risk adjustment does not remove incentives for plans to limit coverage for services associated with mental health and substance use disorders. Adding mental health and substance use diagnoses used in Medicare Part D risk adjustment is one potential policy step toward addressing this problem in the Marketplaces. PMID:27269018
Risk-adjusted capitation payments for catastrophic risks based on multi-year prior costs.

PubMed

van Barneveld, E M; van Vliet, R C; van de Ven, W P

1997-02-01

In many countries regulated competition among health insurance companies has recently been proposed or implemented. A crucial issue is whether or not the benefits package offered by competing insurers should also cover catastrophic risks (like several forms of expensive long-term care) in addition to non-catastrophic risks (like hospital care and physician services). In 1988 the Dutch government proposed compulsory national health insurance based on regulated competition among insurer as well as among providers of care. The competing insurers should offer a benefits package covering both non-catastrophic risks and catastrophic risks. The insurers would be largely financed via risk-adjusted capitation payments. The government intended to use a capitation formula that is, besides some demographic variables, based on multi-year prior costs. This paper presents the results of an explorative empirical analysis of the possible consequences of such a capitation formula for catastrophic risks. The main conclusion is that this formula would be inadequate because it would leave ample room for cream skimming.

Estimating lifetime and age-conditional probabilities of developing cancer.

PubMed

Wun, L M; Merrill, R M; Feuer, E J

1998-01-01

Lifetime and age-conditional risk estimates of developing cancer provide a useful summary to the public of the current cancer risk and how this risk compares with earlier periods and among select subgroups of society. These reported estimates, commonly quoted in the popular press, have the potential to promote early detection efforts, to increase cancer awareness, and to serve as an aid in study planning. However, they can also be easily misunderstood and frightening to the general public. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute and the American Cancer Society have recently begun including in annual reports lifetime and age-conditional risk estimates of developing cancer. These risk estimates are based on incidence rates that reflect new cases of the cancer in a population free of the cancer. To compute these estimates involves a cancer prevalence adjustment that is computed cross-sectionally from current incidence and mortality data derived within a multiple decrement life table. This paper presents a detailed description of the methodology for deriving lifetime and age-conditional risk estimates of developing cancer. In addition, an extension is made which, using a triple decrement life table, adjusts for a surgical procedure that removes individuals from the risk of developing a given cancer. Two important results which provide insights into the basic methodology are included in the discussion. First, the lifetime risk estimate does not depend on the cancer prevalence adjustment, although this is not the case for age-conditional risk estimates. Second, the lifetime risk estimate is always smaller when it is corrected for a surgical procedure that takes people out of the risk pool to develop the cancer. The methodology is applied to corpus and uterus NOS cancers, with a correction made for hysterectomy prevalence. The interpretation and limitations of risk estimates are also discussed.
Estimation of group means when adjusting for covariates in generalized linear models.

PubMed

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.
Using Quantile and Asymmetric Least Squares Regression for Optimal Risk Adjustment.

PubMed

Lorenz, Normann

2017-06-01

In this paper, we analyze optimal risk adjustment for direct risk selection (DRS). Integrating insurers' activities for risk selection into a discrete choice model of individuals' health insurance choice shows that DRS has the structure of a contest. For the contest success function (csf) used in most of the contest literature (the Tullock-csf), optimal transfers for a risk adjustment scheme have to be determined by means of a restricted quantile regression, irrespective of whether insurers are primarily engaged in positive DRS (attracting low risks) or negative DRS (repelling high risks). This is at odds with the common practice of determining transfers by means of a least squares regression. However, this common practice can be rationalized for a new csf, but only if positive and negative DRSs are equally important; if they are not, optimal transfers have to be calculated by means of a restricted asymmetric least squares regression. Using data from German and Swiss health insurers, we find considerable differences between the three types of regressions. Optimal transfers therefore critically depend on which csf represents insurers' incentives for DRS and, if it is not the Tullock-csf, whether insurers are primarily engaged in positive or negative DRS. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Uncertainty-based Estimation of the Secure Range for ISO New England Dynamic Interchange Adjustment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Etingov, Pavel V.; Makarov, Yuri V.; Wu, Di

2014-04-14

The paper proposes an approach to estimate the secure range for dynamic interchange adjustment, which assists system operators in scheduling the interchange with neighboring control areas. Uncertainties associated with various sources are incorporated. The proposed method is implemented in the dynamic interchange adjustment (DINA) tool developed by Pacific Northwest National Laboratory (PNNL) for ISO New England. Simulation results are used to validate the effectiveness of the proposed method.
A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims

PubMed Central

Sharp, Sandra M; Bevan, Gwyn; Skinner, Jonathan S; Gottlieb, Daniel J

2014-01-01

Objective To compare the performance of two new approaches to risk adjustment that are free of the influence of observational intensity with methods that depend on diagnoses listed in administrative databases. Setting Administrative data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. Design Cross sectional analysis. Participants 20% sample of fee for service Medicare beneficiaries residing in one of 306 hospital referral regions in the United States in 2007 (n=5 153 877). Main outcome measures The effect of health risk adjustment on age, sex, and race adjusted mortality and spending rates among hospital referral regions using four indices: the standard Centers for Medicare and Medicaid Services—Hierarchical Condition Categories (HCC) index used by the US Medicare program (calculated from diagnoses listed in Medicare’s administrative database); a visit corrected HCC index (to reduce the effects of observational intensity on frequency of diagnoses); a poverty index (based on US census); and a population health index (calculated using data on incidence of hip fractures and strokes, and responses from a population based annual survey of health from the Centers for Disease Control and Prevention). Results Estimated variation in age, sex, and race adjusted mortality rates across hospital referral regions was reduced using the indices based on population health, poverty, and visit corrected HCC, but increased using the standard HCC index. Most of the residual variation in age, sex, and race adjusted mortality was explained (in terms of weighted R2) by the population health index: R2=0.65. The other indices explained less: R2=0.20 for the visit corrected HCC index; 0.19 for the poverty index, and 0.02 for the standard HCC index. The residual variation in age, sex, race, and price adjusted spending per capita across the 306 hospital referral regions explained by the indices (in terms of weighted R2) were 0.50 for
A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims.

PubMed

Wennberg, David E; Sharp, Sandra M; Bevan, Gwyn; Skinner, Jonathan S; Gottlieb, Daniel J; Wennberg, John E

2014-04-10

To compare the performance of two new approaches to risk adjustment that are free of the influence of observational intensity with methods that depend on diagnoses listed in administrative databases. Administrative data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. Cross sectional analysis. 20% sample of fee for service Medicare beneficiaries residing in one of 306 hospital referral regions in the United States in 2007 (n = 5,153,877). The effect of health risk adjustment on age, sex, and race adjusted mortality and spending rates among hospital referral regions using four indices: the standard Centers for Medicare and Medicaid Services--Hierarchical Condition Categories (HCC) index used by the US Medicare program (calculated from diagnoses listed in Medicare's administrative database); a visit corrected HCC index (to reduce the effects of observational intensity on frequency of diagnoses); a poverty index (based on US census); and a population health index (calculated using data on incidence of hip fractures and strokes, and responses from a population based annual survey of health from the Centers for Disease Control and Prevention). Estimated variation in age, sex, and race adjusted mortality rates across hospital referral regions was reduced using the indices based on population health, poverty, and visit corrected HCC, but increased using the standard HCC index. Most of the residual variation in age, sex, and race adjusted mortality was explained (in terms of weighted R2) by the population health index: R2=0.65. The other indices explained less: R2=0.20 for the visit corrected HCC index; 0.19 for the poverty index, and 0.02 for the standard HCC index. The residual variation in age, sex, race, and price adjusted spending per capita across the 306 hospital referral regions explained by the indices (in terms of weighted R2) were 0.50 for the standard HCC index, 0.21 for the population health index, 0.12 for the
Estimation of the standardized risk difference and ratio in a competing risks framework: application to injection drug use and progression to AIDS after initiation of antiretroviral therapy.

PubMed

Cole, Stephen R; Lau, Bryan; Eron, Joseph J; Brookhart, M Alan; Kitahata, Mari M; Martin, Jeffrey N; Mathews, William C; Mugavero, Michael J

2015-02-15

There are few published examples of absolute risk estimated from epidemiologic data subject to censoring and competing risks with adjustment for multiple confounders. We present an example estimating the effect of injection drug use on 6-year risk of acquired immunodeficiency syndrome (AIDS) after initiation of combination antiretroviral therapy between 1998 and 2012 in an 8-site US cohort study with death before AIDS as a competing risk. We estimate the risk standardized to the total study sample by combining inverse probability weights with the cumulative incidence function; estimates of precision are obtained by bootstrap. In 7,182 patients (83% male, 33% African American, median age of 38 years), we observed 6-year standardized AIDS risks of 16.75% among 1,143 injection drug users and 12.08% among 6,039 nonusers, yielding a standardized risk difference of 4.68 (95% confidence interval: 1.27, 8.08) and a standardized risk ratio of 1.39 (95% confidence interval: 1.12, 1.72). Results may be sensitive to the assumptions of exposure-version irrelevance, no measurement bias, and no unmeasured confounding. These limitations suggest that results be replicated with refined measurements of injection drug use. Nevertheless, estimating the standardized risk difference and ratio is straightforward, and injection drug use appears to increase the risk of AIDS. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Variance computations for functional of absolute risk estimates.

PubMed

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.
Variance computations for functional of absolute risk estimates

PubMed Central

Pfeiffer, R.M.; Petracci, E.

2011-01-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476
Using VS30 to Estimate Station ML Adjustments (dML)

NASA Astrophysics Data System (ADS)

Yong, A.; Herrick, J.; Cochran, E. S.; Andrews, J. R.; Yu, E.

2017-12-01

Currently, new seismic stations added to a regional seismic network cannot be used to calculate local or Richter magnitude (ML) until a revised region-wide amplitude decay function is developed. The new station must record a minimum number of local and regional events that meet specific amplitude requirements prior to re-calibration of the amplitude decay function. Therefore, there can be significant delay between when a new station starts contributing real-time waveform packets and when the data can be included in magnitude estimation. The station component adjustments (dML; Uhrhammer et al., 2011) are calculated after first inverting for a new regional amplitude decay function, constrained by the sum of dML for long-running stations. Here, we propose a method to calculate an initial dML using known or proxy values of seismic site conditions. For site conditions, we use the time-averaged shear-wave velocity (VS) of the upper 30 m (VS30). We solve for dML as described in Equation (1) by Uhrhammer et al. (2011): ML = log (A) - log A0 (r) + dML, where A is the maximum Wood and Anderson (1925) trace amplitude (mm), r is the distance (km), and dML is the station adjustment. Measured VS30 and estimated dML data are comprised of records from 887 horizontal components (east-west and north-south orientations) from 93 seismic monitoring stations in the California Integrated Seismic Network. VS30 values range from 202 m/s to 1464 m/s and dML range from -1.10 to 0.39. VS30 and dML exhibit a positive correlation coefficient (R = 0.72), indicating that as VS30 increases, dML increases. This implies that greater site amplification (i.e., lower VS30) results in smaller ML. When we restrict VS30 < 760 m/s to focus on dML at soft soil to soft rock sites, R increases to 0.80. In locations where measured VS30 data are unavailable, we evaluate the use of proxy-based VS30 estimates based on geology, topographic slope and terrain classification, as well as other hybridized methods
The risk-adjusted vision beyond casemix (DRG) funding in Australia. International lessons in high complexity and capitation.

PubMed

Antioch, Kathryn M; Walsh, Michael K

2004-06-01

Hospitals throughout the world using funding based on diagnosis-related groups (DRG) have incurred substantial budgetary deficits, despite high efficiency. We identify the limitations of DRG funding that lack risk (severity) adjustment for State-wide referral services. Methods to risk adjust DRGs are instructive. The average price in casemix funding in the Australian State of Victoria is policy based, not benchmarked. Average cost weights are too low for high-complexity DRGs relating to State-wide referral services such as heart and lung transplantation and trauma. Risk-adjusted specified grants (RASG) are required for five high-complexity respiratory, cardiology and stroke DRGs incurring annual deficits of $3.6 million due to high casemix complexity and government under-funding despite high efficiency. Five stepwise linear regressions for each DRG excluded non-significant variables and assessed heteroskedasticity and multicollinearlity. Cost per patient was the dependent variable. Significant independent variables were age, length-of-stay outliers, number of disease types, diagnoses, procedures and emergency status. Diagnosis and procedure severity markers were identified. The methodology and the work of the State-wide Risk Adjustment Working Group can facilitate risk adjustment of DRGs State-wide and for Treasury negotiations for expenditure growth. The Alfred Hospital previously negotiated RASG of $14 million over 5 years for three trauma and chronic DRGs. Some chronic diseases require risk-adjusted capitation funding models for Australian Health Maintenance Organizations as an alternative to casemix funding. The use of Diagnostic Cost Groups can facilitate State and Federal government reform via new population-based risk adjusted funding models that measure health need.
Evaluating variation in use of definitive therapy and risk-adjusted prostate cancer mortality in England and the USA.

PubMed

Sachdeva, Ashwin; van der Meulen, Jan H; Emberton, Mark; Cathcart, Paul J

2015-02-24

Prostate cancer mortality (PCM) in the USA is among the lowest in the world, whereas PCM in England is among the highest in Europe. This paper aims to assess the association of variation in use of definitive therapy on risk-adjusted PCM in England as compared with the USA. Observational study. Cancer registry data from England and the USA. Men diagnosed with non-metastatic prostate cancer (PCa) in England and the USA between 2004 and 2008. Competing-risks survival analyses to estimate subhazard ratios (SHR) of PCM adjusted for age, ethnicity, year of diagnosis, Gleason score (GS) and clinical tumour (cT) stage. 222,163 men were eligible for inclusion. Compared with American patients, English patients were more likely to present at an older age (70-79 years: England 44.2%, USA 29.3%, p<0.001), with higher tumour stage (cT3-T4: England 25.1%, USA 8.6%, p<0.001) and higher GS (GS 8-10: England 20.7%, USA 11.2%, p<0.001). They were also less likely to receive definitive therapy (England 38%, USA 77%, p<0.001). English patients were more likely to die of PCa (SHR=1.9, 95% CI 1.7 to 2.0, p<0.001). However, this difference was no longer statistically significant when also adjusted for use of definitive therapy (SHR=1.0, 95% CI 1.0 to 1.1, p=0.3). Risk-adjusted PCM is significantly higher in England compared with the USA. This difference may be explained by less frequent use of definitive therapy in England. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Comparison of risk estimates using life-table methods.

PubMed

Sullivan, R E; Weng, P S

1987-08-01

Risk estimates promulgated by various radiation protection authorities in recent years have become increasingly more complex. Early "integral" estimates in the form of health effects per 0.01 person-Gy (per person-rad) or per 10(4) person-Gy (per 10(6) person-rad) have tended to be replaced by "differential" estimates which are age- and sex-dependent and specify both minimum induction (latency) and duration of risk expression (plateau) periods. These latter types of risk estimate must be used in conjunction with a life table in order to reduce them to integral form. In this paper, the life table has been used to effect a comparison of the organ and tissue risk estimates derived in several recent reports. In addition, a brief review of life-table methodology is presented and some features of the models used in deriving differential coefficients are discussed. While the great number of permutations possible with dose-response models, detailed risk estimates and proposed projection models precludes any unique result, the reduced integral coefficients are required to conform to the linear, absolute-risk model recommended for use with the integral risk estimates reviewed.
Impact of a financial risk-sharing scheme on budget-impact estimations: a game-theoretic approach.

PubMed

Gavious, Arieh; Greenberg, Dan; Hammerman, Ariel; Segev, Ella

2014-06-01

As part of the process of updating the National List of Health Services in Israel, health plans (the 'payers') and manufacturers each provide estimates on the expected number of patients that will utilize a new drug. Currently, payers face major financial consequences when actual utilization is higher than the allocated budget. We suggest a risk-sharing model between the two stakeholders; if the actual number of patients exceeds the manufacturer's prediction, the manufacturer will reimburse the payers by a rebate rate of α from the deficit. In case of under-utilization, payers will refund the government at a rate of γ from the surplus budget. Our study objective was to identify the optimal early estimations of both 'players' prior to and after implementation of the risk-sharing scheme. Using a game-theoretic approach, in which both players' statements are considered simultaneously, we examined the impact of risk-sharing within a given range of rebate proportions, on players' early budget estimations. When increasing manufacturer's rebate α to be over 50 %, then manufacturers will announce a larger number, and health plans will announce a lower number of patients than they would without risk sharing, thus substantially decreasing the gap between their estimates. Increasing γ changes players' estimates only slightly. In reaction to applying a substantial risk-sharing rebate α on the manufacturer, both players are expected to adjust their budget estimates toward an optimal equilibrium. Increasing α is a better vehicle for reaching the desired equilibrium rather than increasing γ, as the manufacturer's rebate α substantially influences both players, whereas γ has little effect on the players behavior.
Risk Adjustment and Primary Health Care in Chile

PubMed Central

Vargas, Veronica; Wasem, Juergen

2006-01-01

Aim To offer a capitation formula with greater capacity for guiding resource spending on population with poorer health and lower socioeconomic status in the context of financing and equity in primary health care. Methods We collected two years of data on a sample of 10 000 individuals from a region in Chile, Valdivia and Temuco and evaluated three models to estimate utilization and expenditures per capita. The first model included age and sex; the second one included age, sex, and the presence of two key diagnoses; and the third model included age, sex, and the presence of seven key diagnoses. Regression results were evaluated by R2 and predictive ratios to select the best specifications. Results Per-capita expenditures by age and sex confirmed international trends, where children under five, women, and the elderly were the main users of primary health care services. Women sought health advice twice as much as men. Clear differences by socioeconomic status were observed for the indigent population aged ≥65 years who under-utilized primary health care services. From the three models, major improvement in the predictive power occurred from the demographic (adjusted R2, 9%) to the demographic plus two diagnoses model (adjusted R2, 27%). Improvements were modest when five other diagnoses were added (adjusted R2, 28%). Conclusion The current formula that uses municipality’s financial power and geographic location of health centers to adjust capitation payments provides little incentive to appropriate care for the indigent and people with chronic conditions. A capitation payment that adjusts for age, sex, and the presence of diabetes and hypertension will better guide resource allocation to those with poorer health and lower socioeconomic status. PMID:16758525
Modelling the impact of new patient visits on risk adjusted access at 2 clinics.

PubMed

Kolber, Michael A; Rueda, Germán; Sory, John B

2018-06-01

To evaluate the effect new outpatient clinic visits has on the availability of follow-up visits for established patients when patient visit frequency is risk adjusted. Diagnosis codes for patients from 2 Internal Medicine Clinics were extracted through billing data. The HHS-HCC risk adjusted scores for each clinic were determined based upon the average of all clinic practitioners' profiles. These scores were then used to project encounter frequencies for established patients, and for new patients entering the clinic based on risk and time of entry into the clinics. A distinct mean risk frequency distribution for physicians in each clinic could be defined providing model parameters. Within the model, follow-up visit utilization at the highest risk adjusted visit frequencies would require more follow-up slots than currently available when new patient no-show rates and annual patient loss are included. Patients seen at an intermediate or lower visit risk adjusted frequency could be accommodated when new patient no-show rates and annual patient clinic loss are considered. Value-based care is driven by control of cost while maintaining quality of care. In order to control cost, there has been a drive to increase visit frequency in primary care for those patients at increased risk. Adding new patients to primary care clinics limits the availability of follow-up slots that accrue over time for those at highest risk, thereby limiting disease and, potentially, cost control. If frequency of established care visits can be reduced by improved disease control, closing the practice to new patients, hiring health care extenders, or providing non-face to face care models then quality and cost of care may be improved. © 2018 John Wiley & Sons, Ltd.
Behavioral Adjustment Moderates the Link Between Neuroticism and Biological Health Risk: A U.S.-Japan Comparison Study.

PubMed

Kitayama, Shinobu; Park, Jiyoung; Miyamoto, Yuri; Date, Heiwa; Boylan, Jennifer Morozink; Markus, Hazel R; Karasawa, Mayumi; Kawakami, Norito; Coe, Christopher L; Love, Gayle D; Ryff, Carol D

2018-06-01

Neuroticism, a broad personality trait linked to negative emotions, is consistently linked to ill health when self-report is used to assess health. However, when health risk is assessed with biomarkers, the evidence is inconsistent. Here, we tested the hypothesis that the association between neuroticism and biological health risk is moderated by behavioral adjustment, a propensity to flexibly adjust behaviors to environmental contingencies. Using a U.S.-Japan cross-cultural survey, we found that neuroticism was linked to lower biological health risk for those who are high, but not low, in behavioral adjustment. Importantly, Japanese were higher in behavioral adjustment than European Americans, and as predicted by this cultural difference, neuroticism was linked to lower biological health risk for Japanese but not for European Americans. Finally, consistent with prior evidence, neuroticism was associated with worse self-reported health regardless of behavioral adjustment or culture. Discussion focused on the significance of identifying sociocultural correlates of biological health.
Joint nonparametric correction estimator for excess relative risk regression in survival analysis with exposure measurement error

PubMed Central

Wang, Ching-Yun; Cullings, Harry; Song, Xiao; Kopecky, Kenneth J.

2017-01-01

SUMMARY Observational epidemiological studies often confront the problem of estimating exposure-disease relationships when the exposure is not measured exactly. In the paper, we investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a nonparametric correction (NPC) estimator using data from the subcohort, and further propose a joint nonparametric correction (JNPC) estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of JNPC and NPC is further developed. The proposed estimators are nonparametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses. PMID:29354018
Implications of gambling problems for family and interpersonal adjustment: results from the Quinte Longitudinal Study.

PubMed

Cowlishaw, Sean; Suomi, Aino; Rodgers, Bryan

2016-09-01

To evaluate (1) whether gambling problems predict overall trajectories of change in family or interpersonal adjustment and (2) whether annual measures of gambling problems predict time-specific decreases in family or interpersonal adjustment, concurrently and prospectively. The Quinte Longitudinal Study (QLS) involved random-digit dialling of telephone numbers around the city of Belleville, Canada to recruit 'general population' and 'at-risk' groups (the latter oversampling people likely to develop problems). Five waves of assessment were conducted (2006-10). Latent Trajectory Modelling (LTM) estimated overall trajectories of family and interpersonal adjustment, which were predicted by gambling problems, and also estimated how time-specific problems predicted deviations from these trajectories. Southeast Ontario, Canada. Community sample of Canadian adults (n = 4121). The Problem Gambling Severity Index (PGSI) defined at-risk gambling (ARG: PGSI 1-2) and moderate-risk/problem gambling (MR/PG: PGSI 3+). Outcomes included: (1) family functioning, assessed using a seven-point rating of overall functioning; (2) social support, assessed using items from the Non-support subscale of the Personality Assessment Inventory; and (3) relationship satisfaction, measured by the Kansas Marital Satisfaction Scale. Baseline measures of ARG and MR/PG did not predict rates of change in trajectories of family or interpersonal adjustment. Rather, the annual measures of MR/PG predicted time-specific decreases in family functioning (estimate: -0.11, P < 0.01), social support (estimate: -0.28, P < 0.01) and relationship satisfaction (estimate: -0.53, P < 0.01). ARG predicted concurrent levels of family functioning (estimate: -0.07, P < 0.01). There were time-lagged effects of MR/PG on subsequent levels of family functioning (estimate: -0.12, P < 0.01) and social support (estimate: -0.24, P < 0.01). In a longitudinal study of Canadian adults, moderate-risk
48 CFR 215.404-71-3 - Contract type risk and working capital adjustment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... varying contract types. The working capital adjustment is an adjustment added to the profit objective for... Base (item 20) Profit objective 24. CONTRACT type risk (1) (2) (3) Cost financed Length factor Interest... money. (3) Multiply (1) by (2). (4) Only complete this block when the prospective contract is a fixed...

48 CFR 215.404-71-3 - Contract type risk and working capital adjustment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... varying contract types. The working capital adjustment is an adjustment added to the profit objective for... Base (item 20) Profit objective 24. CONTRACT type risk (1) (2) (3) Cost financed Length factor Interest... money. (3) Multiply (1) by (2). (4) Only complete this block when the prospective contract is a fixed...
48 CFR 215.404-71-3 - Contract type risk and working capital adjustment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... varying contract types. The working capital adjustment is an adjustment added to the profit objective for... Base (item 20) Profit objective 24. CONTRACT type risk (1) (2) (3) Cost financed Length factor Interest... money. (3) Multiply (1) by (2). (4) Only complete this block when the prospective contract is a fixed...
Food-frequency questionnaire-based estimates of total antioxidant capacity and risk of non-Hodgkin lymphoma.

PubMed

Holtan, Shernan G; O'Connor, Helen M; Fredericksen, Zachary S; Liebow, Mark; Thompson, Carrie A; Macon, William R; Micallef, Ivana N; Wang, Alice H; Slager, Susan L; Habermann, Thomas M; Call, Timothy G; Cerhan, James R

2012-09-01

Antioxidants, primarily from fruits and vegetables, have been hypothesized to protect against non-Hodgkin lymphoma (NHL). The oxygen radical absorbance capacity (ORAC) assay, which measures total antioxidant capacity of individual foods and accounts for synergism, can be estimated using a food-frequency questionnaire (FFQ). We tested the hypothesis that higher intake of antioxidant nutrients from foods, supplements and FFQ-based ORAC values are associated with a lower risk of NHL in a clinic-based study of 603 incident cases and 1,007 frequency-matched controls. Diet was assessed with a 128-item FFQ. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals adjusted for age, sex, residence and total energy. Dietary intake of α-tocopherol (OR=0.50; p-trend=0.0002), β-carotene (OR=0.58; p-trend=0.0005), lutein/zeaxanthin (OR=0.62; p-trend=0.005), zinc (OR=0.54; p-trend=0.003) and chromium (OR=0.68; p-trend=0.032) was inversely associated with NHL risk. Inclusion of supplement use had little impact on these associations. Total vegetables (OR=0.52; p-trend<0.0001), particularly green leafy (OR=0.52; p-trend<0.0001) and cruciferous (OR=0.68; p-trend=0.045) vegetables, were inversely associated with NHL risk. NHL risk was inversely associated with both hydrophilic ORAC (OR=0.61, p-trend=0.003) and lipophilic ORAC (OR=0.48, p-trend=0.0002), although after simultaneous adjustment for other antioxidants or total vegetables, only the association for lipophilic ORAC remained significant. There was no striking heterogeneity in results across the common NHL subtypes. Higher antioxidant intake as estimated by the FFQ-ORAC, particularly the lipophilic component, was associated with a lower NHL risk after accounting for other antioxidant nutrients and vegetable intake, supporting this as potentially useful summary measure of total antioxidant intake. Copyright © 2011 UICC.
Impact of Race/Ethnicity and Socioeconomic Status on Risk-Adjusted Hospital Readmission Rates Following Hip and Knee Arthroplasty.

PubMed

Martsolf, Grant R; Barrett, Marguerite L; Weiss, Audrey J; Kandrack, Ryan; Washington, Raynard; Steiner, Claudia A; Mehrotra, Ateev; SooHoo, Nelson F; Coffey, Rosanna

2016-08-17

Readmission rates following total hip arthroplasty (THA) and total knee arthroplasty (TKA) are increasingly used to measure hospital performance. Readmission rates that are not adjusted for race/ethnicity and socioeconomic status, patient risk factors beyond a hospital's control, may not accurately reflect a hospital's performance. In this study, we examined the extent to which risk-adjusting for race/ethnicity and socioeconomic status affected hospital performance in terms of readmission rates following THA and TKA. We calculated 2 sets of risk-adjusted readmission rates by (1) using the Centers for Medicare & Medicaid Services standard risk-adjustment algorithm that incorporates patient age, sex, comorbidities, and hospital effects and (2) adding race/ethnicity and socioeconomic status to the model. Using data from the Healthcare Cost and Utilization Project, 2011 State Inpatient Databases, we compared the relative performances of 1,194 hospitals across the 2 methods. Addition of race/ethnicity and socioeconomic status to the risk-adjustment algorithm resulted in (1) little or no change in the risk-adjusted readmission rates at nearly all hospitals; (2) no change in the designation of the readmission rate as better, worse, or not different from the population mean at >99% of the hospitals; and (3) no change in the excess readmission ratio at >97% of the hospitals. Inclusion of race/ethnicity and socioeconomic status in the risk-adjustment algorithm led to a relative-performance change in readmission rates following THA and TKA at <3% of the hospitals. We believe that policymakers and payers should consider this result when deciding whether to include race/ethnicity and socioeconomic status in risk-adjusted THA and TKA readmission rates used for hospital accountability, payment, and public reporting. Prognostic Level III. See instructions for Authors for a complete description of levels of evidence. Copyright © 2016 by The Journal of Bone and Joint Surgery
The Effect of Complementary and Alternative Medicine Claims on Risk Adjustment

PubMed Central

Lind, Bonnie K.; Abrams, Chad; Lafferty, William E.; Kiehr, Paula K.; Grembowski, David E.

2006-01-01

Objective To assess how the inclusion of diagnoses from complementary and alternative medicine (CAM) providers affects measures of morbidity burden and expectations of health care resource use for insured patients. Methods Claims data from Washington State were used to create two versions of a case-mix index. One version included claims from all provider types; the second version omitted claims from CAM providers who are covered under commercial insurance. Expected resource use was also calculated. The distribution of expected and actual resource use was then compared for the two indices. Results Inclusion of CAM providers shifts many patients into higher morbidity categories; 54% of 61,914 CAM users had higher risk scores in the index which included CAM providers. When expected resource use categories were defined based on all providers, CAM users in the highest morbidity category had average (± s.d.) annual expenditures of $6661 (± $13,863). This was less than those in the highest morbidity category when CAM providers were not included in the index ($8562 ± $16,354), and was also lower than the highest morbidity patients who did not use any CAM services ($8419 ± $18,885). Conclusions Inclusion of services from CAM providers under third party payment increases risk scores for their patients but expectations of costs for this group are lower than expected had costs been estimated based only on services from traditional providers. Additional work is needed to validate risk adjustment indices when adding services from provider groups not included in the development of the index. PMID:17122711
Minimax estimation of qubit states with Bures risk

NASA Astrophysics Data System (ADS)

Acharya, Anirudh; Guţă, Mădălin

2018-04-01

The central problem of quantum statistics is to devise measurement schemes for the estimation of an unknown state, given an ensemble of n independent identically prepared systems. For locally quadratic loss functions, the risk of standard procedures has the usual scaling of 1/n. However, it has been noticed that for fidelity based metrics such as the Bures distance, the risk of conventional (non-adaptive) qubit tomography schemes scales as 1/\\sqrt{n} for states close to the boundary of the Bloch sphere. Several proposed estimators appear to improve this scaling, and our goal is to analyse the problem from the perspective of the maximum risk over all states. We propose qubit estimation strategies based on separate adaptive measurements, and collective measurements, that achieve 1/n scalings for the maximum Bures risk. The estimator involving local measurements uses a fixed fraction of the available resource n to estimate the Bloch vector direction; the length of the Bloch vector is then estimated from the remaining copies by measuring in the estimator eigenbasis. The estimator based on collective measurements uses local asymptotic normality techniques which allows us to derive upper and lower bounds to its maximum Bures risk. We also discuss how to construct a minimax optimal estimator in this setup. Finally, we consider quantum relative entropy and show that the risk of the estimator based on collective measurements achieves a rate O(n-1log n) under this loss function. Furthermore, we show that no estimator can achieve faster rates, in particular the ‘standard’ rate n ‑1.
Public Reporting of Primary Care Clinic Quality: Accounting for Sociodemographic Factors in Risk Adjustment and Performance Comparison.

PubMed

Wholey, Douglas R; Finch, Michael; Kreiger, Rob; Reeves, David

2018-01-03

Performance measurement and public reporting are increasingly being used to compare clinic performance. Intended consequences include quality improvement, value-based payment, and consumer choice. Unintended consequences include reducing access for riskier patients and inappropriately labeling some clinics as poor performers, resulting in tampering with stable care processes. Two analytic steps are used to maximize intended and minimize unintended consequences. First, risk adjustment is used to reduce the impact of factors outside providers' control. Second, performance categorization is used to compare clinic performance using risk-adjusted measures. This paper examines the effects of methodological choices, such as risk adjusting for sociodemographic factors in risk adjustment and accounting for patients clustering by clinics in performance categorization, on clinic performance comparison for diabetes care, vascular care, asthma, and colorectal cancer screening. The population includes all patients with commercial and public insurance served by clinics in Minnesota. Although risk adjusting for sociodemographic factors has a significant effect on quality, it does not explain much of the variation in quality. In contrast, taking into account the nesting of patients within clinics in performance categorization has a substantial effect on performance comparison.
[Do laymen understand information about hospital quality? An empirical verification using risk-adjusted mortality rates as an example].

PubMed

Sander, Uwe; Kolb, Benjamin; Taheri, Fatemeh; Patzelt, Christiane; Emmert, Martin

2017-11-01

The effect of public reporting to improve quality in healthcare is reduced by the limited intelligibility of information about the quality of healthcare providers. This may result in worse health-related choices especially for older people and those with lower levels of education. There is, as yet, little information as to whether laymen understand the concepts behind quality comparisons and if this comprehension is correlated with hospital choices. An instrument with 20 items was developed to analyze the intelligibility of five technical terms which were used in German hospital report cards to explain risk-adjusted death rates. Two online presentations of risk-adjusted death rates for five hospitals in the style of hospital report cards were developed. An online survey of 353 volunteers tested the comprehension of the risk-adjusted mortality rates and included an experimental hospital choice. The intelligibility of five technical terms was tested: risk-adjusted, actual and expected death rate, reference range and national average. The percentages of correct answers for the five technical terms were in the range of 75.0-60.2%. Between 23.8% and 5.1% of the respondents were not able to answer the question about the technical term itself. The least comprehensible technical terms were "risk-adjusted death rate" and "reference range". The intelligibility of the 20 items that were used to test the comprehension of the risk-adjusted mortality was between 89.5% and 14.2%. The two items that proved to be least comprehensible were related to the technical terms "risk-adjusted death rate" and "reference range". For all five technical terms it was found that a better comprehension correlated significantly with better hospital choices. We found a better than average intelligibility for the technical terms "actual and expected death rate" and for "national average". The least understandable were "risk-adjusted death rate" and "reference range". Since the self
PACE and the Medicare+Choice risk-adjusted payment model.

PubMed

Temkin-Greener, H; Meiners, M R; Gruenberg, L

2001-01-01

This paper investigates the impact of the Medicare principal inpatient diagnostic cost group (PIP-DCG) payment model on the Program of All-Inclusive Care for the Elderly (PACE). Currently, more than 6,000 Medicare beneficiaries who are nursing home certifiable receive care from PACE, a program poised for expansion under the Balanced Budget Act of 1997. Overall, our analysis suggests that the application of the PIP-DCG model to the PACE program would reduce Medicare payments to PACE, on average, by 38%. The PIP-DCG payment model bases its risk adjustment on inpatient diagnoses and does not capture adequately the risk of caring for a population with functional impairments.
Development and Evaluation of an Automated Machine Learning Algorithm for In-Hospital Mortality Risk Adjustment Among Critical Care Patients.

PubMed

Delahanty, Ryan J; Kaufman, David; Jones, Spencer S

2018-06-01

Risk adjustment algorithms for ICU mortality are necessary for measuring and improving ICU performance. Existing risk adjustment algorithms are not widely adopted. Key barriers to adoption include licensing and implementation costs as well as labor costs associated with human-intensive data collection. Widespread adoption of electronic health records makes automated risk adjustment feasible. Using modern machine learning methods and open source tools, we developed and evaluated a retrospective risk adjustment algorithm for in-hospital mortality among ICU patients. The Risk of Inpatient Death score can be fully automated and is reliant upon data elements that are generated in the course of usual hospital processes. One hundred thirty-one ICUs in 53 hospitals operated by Tenet Healthcare. A cohort of 237,173 ICU patients discharged between January 2014 and December 2016. The data were randomly split into training (36 hospitals), and validation (17 hospitals) data sets. Feature selection and model training were carried out using the training set while the discrimination, calibration, and accuracy of the model were assessed in the validation data set. Model discrimination was evaluated based on the area under receiver operating characteristic curve; accuracy and calibration were assessed via adjusted Brier scores and visual analysis of calibration curves. Seventeen features, including a mix of clinical and administrative data elements, were retained in the final model. The Risk of Inpatient Death score demonstrated excellent discrimination (area under receiver operating characteristic curve = 0.94) and calibration (adjusted Brier score = 52.8%) in the validation dataset; these results compare favorably to the published performance statistics for the most commonly used mortality risk adjustment algorithms. Low adoption of ICU mortality risk adjustment algorithms impedes progress toward increasing the value of the healthcare delivered in ICUs. The Risk of Inpatient Death
Solving the Value Equation: Assessing Surgeon Performance Using Risk-Adjusted Quality-Cost Diagrams and Surgical Outcomes.

PubMed

Knechtle, William S; Perez, Sebastian D; Raval, Mehul V; Sullivan, Patrick S; Duwayri, Yazan M; Fernandez, Felix; Sharma, Joe; Sweeney, John F

Quality-cost diagrams have been used previously to assess interventions and their cost-effectiveness. This study explores the use of risk-adjusted quality-cost diagrams to compare the value provided by surgeons by presenting cost and outcomes simultaneously. Colectomy cases from a single institution captured in the National Surgical Quality Improvement Program database were linked to hospital cost-accounting data to determine costs per encounter. Risk adjustment models were developed and observed average cost and complication rates per surgeon were compared to expected cost and complication rates using the diagrams. Surgeons were surveyed to determine if the diagrams could provide information that would result in practice adjustment. Of 55 surgeons surveyed on the utility of the diagrams, 92% of respondents believed the diagrams were useful. The diagrams seemed intuitive to interpret, and making risk-adjusted comparisons accounted for patient differences in the evaluation.
Adjustable Parameter-Based Distributed Fault Estimation Observer Design for Multiagent Systems With Directed Graphs.

PubMed

Zhang, Ke; Jiang, Bin; Shi, Peng

2017-02-01

In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H ∞ and H 2 with pole placement, multiconstrained design is given to calculate the gain of DFEO. Finally, simulation results are presented to illustrate the feasibility and effectiveness of the proposed DFEO design with AP.
NDVI saturation adjustment: a new approach for improving cropland performance estimates in the Greater Platte River Basin, USA

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.; Phuyal, Khem P.; Ji, Lei

2013-01-01

In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVIsat_adjust) based on RVI was developed. A 10-year (2000–2009) NDVIsat_adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CPnon_sat_adjust, CPsat_adjust) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CPsat_adjust and the NASS average corn yield data (r = 0.78, 113 samples) is stronger than the relationship between CPnon_sat_adjust and the NASS average corn yield data (r = 0.67, 113 samples), indicating that the new CPsat_adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.
Risk adjustment for comparing hospital quality with surgery: how many variables are needed?

PubMed

Dimick, Justin B; Osborne, Nicholas H; Hall, Bruce L; Ko, Clifford Y; Birkmeyer, John D

2010-04-01

The American College of Surgeons' National Surgical Quality Improvement Program (ACS NSQIP) will soon be reporting procedure-specific outcomes, and hopes to reduce the burden of data collection by collecting fewer variables. We sought to determine whether these changes threaten the robustness of the risk adjustment of hospital quality comparisons. We used prospective, clinical data from the ACS NSQIP from 2005 to 2007 (184 hospitals, 74,887 patients). For the 5 general surgery operations in the procedure-specific NSQIP, we compared the ability of the full model (21 variables), an intermediate model (12 variables), and a limited model (5 variables) to predict patient outcomes and to risk-adjust hospital outcomes. The intermediate and limited models were comparable with the full model in all analyses. In the assessment of patient risk, the limited and full models had very similar discrimination at the patient level (C-indices for all 5 procedures combined of 0.93 versus 0.91 for mortality and 0.78 versus 0.76 for morbidity) and showed good calibration across strata of patient risk. In assessing hospital-specific outcomes, results from the limited and full-risk models were highly correlated for both mortality (range 0.94 to 0.99 across the 5 operations) and morbidity (range 0.96 to 0.99). Procedure-specific hospital quality measures can be adequately risk-adjusted with a limited number of variables. In the context of the ACS NSQIP, moving to a more limited model will dramatically reduce the burden of data collection for participating hospitals. Published by Elsevier Inc.
Beyond preadoptive risk: The impact of adoptive family environment on adopted youth's psychosocial adjustment.

PubMed

Ji, Juye; Brooks, Devon; Barth, Richard P; Kim, Hansung

2010-07-01

Adopted children often are exposed to preadoptive stressors--such as prenatal substance exposure, child maltreatment, and out-of-home placements--that increase their risks for psychosocial maladjustment. Psychosocial adjustment of adopted children emerges as the product of pre- and postadoptive factors. This study builds on previous research, which fails to simultaneously assess the influences of pre- and postadoptive factors, by examining the impact of adoptive family sense of coherence on adoptee's psychosocial adjustment beyond the effects of preadoptive risks. Using a sample of adoptive families (n = 385) taking part in the California Long Range Adoption Study, structural equation modeling analyses were performed. Results indicate a significant impact of family sense of coherence on adoptees' psychosocial adjustment and a considerably less significant role of preadoptive risks. The findings suggest the importance of assessing adoptive family's ability to respond to stress and of helping families to build and maintain their capacity to cope with stress despite the sometimes fractious pressures of adoption.
Improved implementation of the risk-adjusted Bernoulli CUSUM chart to monitor surgical outcome quality.

PubMed

Keefe, Matthew J; Loda, Justin B; Elhabashy, Ahmad E; Woodall, William H

2017-06-01

The traditional implementation of the risk-adjusted Bernoulli cumulative sum (CUSUM) chart for monitoring surgical outcome quality requires waiting a pre-specified period of time after surgery before incorporating patient outcome information. We propose a simple but powerful implementation of the risk-adjusted Bernoulli CUSUM chart that incorporates outcome information as soon as it is available, rather than waiting a pre-specified period of time after surgery. A simulation study is presented that compares the performance of the traditional implementation of the risk-adjusted Bernoulli CUSUM chart to our improved implementation. We show that incorporating patient outcome information as soon as it is available leads to quicker detection of process deterioration. Deterioration of surgical performance could be detected much sooner using our proposed implementation, which could lead to the earlier identification of problems. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Using referrals and priority-setting rules to risk adjust budgets: the case of regional psychiatric centers.

PubMed

Holman, Per Arne; Grepperud, Sverre; Tanum, Lars

2011-03-01

An important objective of many health care systems is to ensure equal access to health care services. One way of achieving this is by having universal coverage (low or absent out-of-pockets payments) combined with tax-financed transfers (block grants) to providers with a catchment area responsibility. However, a precondition for equal access in such systems is that providers have similar capacities -- meaning that budgets must be perfectly adjusted for variations in treatment costs not being under the control of providers (risk adjustment). This study presents a method that can be applied to adjust global budgets for variation in health risks. The method is flexible in the sense that it takes into account the possibility that variation in needs may depend on the degree of rationing in supplying health care services. The information being available from referrals is used to risk-adjust budgets. An expert panel ranks each individual on the basis of need. The ranking is performed according to priority-setting criteria for health care services. In addition, the panel suggests an adequate treatment profile (treatment category and treatment intensity) for each referral reviewed. By coupling the treatment profiles with cost information, risk-adjusted budgets are derived. Only individuals found to have a sufficiently high ranking (degree of need) will impact the derived risk-adjusted formula. The method is applied to four Regional Psychiatric Centers (RPC) supplying (i) outpatient services, (ii) day-patient care, and (iii) inpatient treatment for adults. The budget reallocations needed (positive and negative) to achieve an equal capacity across providers range between 10% and 42% of the current budgets. Our method can identify variations across providers when it comes to actual capacity and suggests budget reallocations that make the capacities to be equal across providers. In the case of the Regional Psychiatric Centers (RPCs) considered in this analysis, significant
Risk Adjustment, Reinsurance Improved Financial Outcomes For Individual Market Insurers With The Highest Claims.

PubMed

Jacobs, Paul D; Cohen, Michael L; Keenan, Patricia

2017-04-01

The Affordable Care Act (ACA) reformed the individual health insurance market. Because insurers can no longer vary their offers of coverage based on applicants' health status, the ACA established a risk adjustment program to equalize health-related cost differences across plans. The ACA also established a temporary reinsurance program to subsidize high-cost claims. To assess the impact of these programs, we compared revenues to claims costs for insurers in the individual market during the first two years of ACA implementation (2014 and 2015), before and after the inclusion of risk adjustment and reinsurance payments. Before these payments were included, for the 30 percent of insurers with the highest claims costs, claims (not including administrative expenses) exceeded premium revenues by $90-$397 per enrollee per month. The effect was reversed after these payments were included, with revenues exceeding claims costs by $0-$49 per month. The risk adjustment and reinsurance programs were relatively well targeted in the first two years. While there is ongoing discussion regarding the future of the ACA, our findings can shed light on how risk-sharing programs can address risk selection among insurers-a pervasive issue in all health insurance markets. Project HOPE—The People-to-People Health Foundation, Inc.
Challenges in risk estimation using routinely collected clinical data: The example of estimating cervical cancer risks from electronic health-records.

PubMed

Landy, Rebecca; Cheung, Li C; Schiffman, Mark; Gage, Julia C; Hyun, Noorie; Wentzensen, Nicolas; Kinney, Walter K; Castle, Philip E; Fetterman, Barbara; Poitras, Nancy E; Lorey, Thomas; Sasieni, Peter D; Katki, Hormuzd A

2018-06-01

Electronic health-records (EHR) are increasingly used by epidemiologists studying disease following surveillance testing to provide evidence for screening intervals and referral guidelines. Although cost-effective, undiagnosed prevalent disease and interval censoring (in which asymptomatic disease is only observed at the time of testing) raise substantial analytic issues when estimating risk that cannot be addressed using Kaplan-Meier methods. Based on our experience analysing EHR from cervical cancer screening, we previously proposed the logistic-Weibull model to address these issues. Here we demonstrate how the choice of statistical method can impact risk estimates. We use observed data on 41,067 women in the cervical cancer screening program at Kaiser Permanente Northern California, 2003-2013, as well as simulations to evaluate the ability of different methods (Kaplan-Meier, Turnbull, Weibull and logistic-Weibull) to accurately estimate risk within a screening program. Cumulative risk estimates from the statistical methods varied considerably, with the largest differences occurring for prevalent disease risk when baseline disease ascertainment was random but incomplete. Kaplan-Meier underestimated risk at earlier times and overestimated risk at later times in the presence of interval censoring or undiagnosed prevalent disease. Turnbull performed well, though was inefficient and not smooth. The logistic-Weibull model performed well, except when event times didn't follow a Weibull distribution. We have demonstrated that methods for right-censored data, such as Kaplan-Meier, result in biased estimates of disease risks when applied to interval-censored data, such as screening programs using EHR data. The logistic-Weibull model is attractive, but the model fit must be checked against Turnbull non-parametric risk estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Introducing risk adjustment and free health plan choice in employer-based health insurance: Evidence from Germany.

PubMed

Pilny, Adam; Wübker, Ansgar; Ziebarth, Nicolas R

2017-12-01

To equalize differences in health plan premiums due to differences in risk pools, the German legislature introduced a simple Risk Adjustment Scheme (RAS) based on age, gender and disability status in 1994. In addition, effective 1996, consumers gained the freedom to choose among hundreds of existing health plans, across employers and state-borders. This paper (a) estimates RAS pass-through rates on premiums, financial reserves, and expenditures and assesses the overall RAS impact on market price dispersion. Moreover, it (b) characterizes health plan switchers and investigates their annual and cumulative switching rates over time. Our main findings are based on representative enrollee panel data linked to administrative RAS and health plan data. We show that sickness funds with bad risk pools and high pre-RAS premiums lowered their total premiums by 42 cents per additional euro allocated by the RAS. Consequently, post-RAS, health plan prices converged but not fully. Because switchers are more likely to be white collar, young and healthy, the new consumer choice resulted in more risk segregation and the amount of money redistributed by the RAS increased over time. Copyright © 2017 Elsevier B.V. All rights reserved.

Software risk estimation and management techniques at JPL

NASA Technical Reports Server (NTRS)

Hihn, J.; Lum, K.

2002-01-01

In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.
Estimating Radiogenic Cancer Risks

EPA Pesticide Factsheets

This document presents a revised methodology for EPA's estimation of cancer risks due to low-LET radiation exposures developed in light of information that has become available, especially new information on the Japanese atomic bomb survivors.
Reliability of risk-adjusted outcomes for profiling hospital surgical quality.

PubMed

Krell, Robert W; Hozain, Ahmed; Kao, Lillian S; Dimick, Justin B

2014-05-01

Quality improvement platforms commonly use risk-adjusted morbidity and mortality to profile hospital performance. However, given small hospital caseloads and low event rates for some procedures, it is unclear whether these outcomes reliably reflect hospital performance. To determine the reliability of risk-adjusted morbidity and mortality for hospital performance profiling using clinical registry data. A retrospective cohort study was conducted using data from the American College of Surgeons National Surgical Quality Improvement Program, 2009. Participants included all patients (N = 55,466) who underwent colon resection, pancreatic resection, laparoscopic gastric bypass, ventral hernia repair, abdominal aortic aneurysm repair, and lower extremity bypass. Outcomes included risk-adjusted overall morbidity, severe morbidity, and mortality. We assessed reliability (0-1 scale: 0, completely unreliable; and 1, perfectly reliable) for all 3 outcomes. We also quantified the number of hospitals meeting minimum acceptable reliability thresholds (>0.70, good reliability; and >0.50, fair reliability) for each outcome. For overall morbidity, the most common outcome studied, the mean reliability depended on sample size (ie, how high the hospital caseload was) and the event rate (ie, how frequently the outcome occurred). For example, mean reliability for overall morbidity was low for abdominal aortic aneurysm repair (reliability, 0.29; sample size, 25 cases per year; and event rate, 18.3%). In contrast, mean reliability for overall morbidity was higher for colon resection (reliability, 0.61; sample size, 114 cases per year; and event rate, 26.8%). Colon resection (37.7% of hospitals), pancreatic resection (7.1% of hospitals), and laparoscopic gastric bypass (11.5% of hospitals) were the only procedures for which any hospitals met a reliability threshold of 0.70 for overall morbidity. Because severe morbidity and mortality are less frequent outcomes, their mean
[Estimation of individual breast cancer risk: relevance and limits of risk estimation models].

PubMed

De Pauw, A; Stoppa-Lyonnet, D; Andrieu, N; Asselain, B

2009-10-01

Several risk estimation models for breast or ovarian cancers have been developed these last decades. All these models take into account the family history, with different levels of sophistication. Gail model was developed in 1989 taking into account the family history (0, 1 or > or = 2 affected relatives) and several environmental factors. In 1990, Claus model was the first to integrate explicit assumptions about genetic effects, assuming a single gene dominantly inherited occurring with a low frequency in the population. BRCAPRO model, posterior to the identification of BRCA1 and BRCA2, assumes a restricted transmission with only these two dominantly inherited genes. BOADICEA model adds the effect of a polygenic component to the effect of BRCA1 and BRCA2 to explain the residual clustering of breast cancer. At last, IBIS model assumes a third dominantly inherited gene to explain this residual clustering. Moreover, this model incorporates environmental factors. We applied the Claus, BRCAPRO, BOADICEA and IBIS models to four clinical situations, corresponding to more or less heavy family histories, in order to study the consistency of the risk estimates. The three more recent models (BRCAPRO, BOADICEA and IBIS) gave the closer estimations. These estimates could be useful in clinical practice in front of complex analysis of breast and/or ovarian cancers family history.
Why people do what they do to protect against earthquake risk: perceptions of hazard adjustment attributes.

PubMed

Lindell, Michael K; Arlikatti, Sudha; Prater, Carla S

2009-08-01

This study examined respondents' self-reported adoption of 16 hazard adjustments (preimpact actions to reduce danger to persons and property), their perceptions of those adjustments' attributes, and the correlations of those perceived attributes with respondents' demographic characteristics. The sample comprised 561 randomly selected residents from three cities in Southern California prone to high seismic risk and three cities from Western Washington prone to moderate seismic risks. The results show that the hazard adjustment perceptions were defined by hazard-related attributes and resource-related attributes. More significantly, the respondents had a significant degree of consensus in their ratings of those attributes and used them to differentiate among the hazard adjustments, as indicated by statistically significant differences among the hazard adjustment profiles. Finally, there were many significant correlations between respondents' demographic characteristics and the perceived characteristics of hazard adjustments, but there were few consistent patterns among these correlations.
Risk-adjusted performance evaluation in three academic thoracic surgery units using the Eurolung risk models.

PubMed

Pompili, Cecilia; Shargall, Yaron; Decaluwe, Herbert; Moons, Johnny; Chari, Madhu; Brunelli, Alessandro

2018-01-03

The objective of this study was to evaluate the performance of 3 thoracic surgery centres using the Eurolung risk models for morbidity and mortality. This was a retrospective analysis performed on data collected from 3 academic centres (2014-2016). Seven hundred and twenty-one patients in Centre 1, 857 patients in Centre 2 and 433 patients in Centre 3 who underwent anatomical lung resections were analysed. The Eurolung1 and Eurolung2 models were used to predict risk-adjusted cardiopulmonary morbidity and 30-day mortality rates. Observed and risk-adjusted outcomes were compared within each centre. The observed morbidity of Centre 1 was in line with the predicted morbidity (observed 21.1% vs predicted 22.7%, P = 0.31). Centre 2 performed better than expected (observed morbidity 20.2% vs predicted 26.7%, P < 0.001), whereas the observed morbidity of Centre 3 was higher than the predicted morbidity (observed 41.1% vs predicted 24.3%, P < 0.001). Centre 1 had higher observed mortality when compared with the predicted mortality (3.6% vs 2.1%, P = 0.005), whereas Centre 2 had an observed mortality rate significantly lower than the predicted mortality rate (1.2% vs 2.5%, P = 0.013). Centre 3 had an observed mortality rate in line with the predicted mortality rate (observed 1.4% vs predicted 2.4%, P = 0.17). The observed mortality rates in the patients with major complications were 30.8% in Centre 1 (versus predicted mortality rate 3.8%, P < 0.001), 8.2% in Centre 2 (versus predicted mortality rate 4.1%, P = 0.030) and 9.0% in Centre 3 (versus predicted mortality rate 3.5%, P = 0.014). The Eurolung models were successfully used as risk-adjusting instruments to internally audit the outcomes of 3 different centres, showing their applicability for future quality improvement initiatives. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.
UPPER BOUND RISK ESTIMATES FOR MIXTURES OF CARCINOGENS

EPA Science Inventory

The excess cancer risk that might result from exposure to a mixture of chemical carcinogens usually is estimated with data from experiments conducted on individual chemicals. An upper bound on the total excess risk is estimated commonly by summing individual upper bound risk esti...
Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR).

PubMed

Evans, Scott R; Rubin, Daniel; Follmann, Dean; Pennello, Gene; Huskins, W Charles; Powers, John H; Schoenfeld, David; Chuang-Stein, Christy; Cosgrove, Sara E; Fowler, Vance G; Lautenbach, Ebbing; Chambers, Henry F

2015-09-01

Clinical trials that compare strategies to optimize antibiotic use are of critical importance but are limited by competing risks that distort outcome interpretation, complexities of noninferiority trials, large sample sizes, and inadequate evaluation of benefits and harms at the patient level. The Antibacterial Resistance Leadership Group strives to overcome these challenges through innovative trial design. Response adjusted for duration of antibiotic risk (RADAR) is a novel methodology utilizing a superiority design and a 2-step process: (1) categorizing patients into an overall clinical outcome (based on benefits and harms), and (2) ranking patients with respect to a desirability of outcome ranking (DOOR). DOORs are constructed by assigning higher ranks to patients with (1) better overall clinical outcomes and (2) shorter durations of antibiotic use for similar overall clinical outcomes. DOOR distributions are compared between antibiotic use strategies. The probability that a randomly selected patient will have a better DOOR if assigned to the new strategy is estimated. DOOR/RADAR represents a new paradigm in assessing the risks and benefits of new strategies to optimize antibiotic use. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Projecting School Psychology Staffing Needs Using a Risk-Adjusted Model.

ERIC Educational Resources Information Center

Stellwagen, Kurt

A model is proposed to project optimal school psychology service ratios based upon the percentages of at risk students enrolled within a given school population. Using the standard 1:1,000 service ratio advocated by The National Association of School Psychologists (NASP) as a starting point, ratios are then adjusted based upon the size of three…
A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and new Zealand Intensive Care Adult Patient Data-Base, 2008-2009.

PubMed

Moran, John L; Solomon, Patricia J

2012-05-16

For the analysis of length-of-stay (LOS) data, which is characteristically right-skewed, a number of statistical estimators have been proposed as alternatives to the traditional ordinary least squares (OLS) regression with log dependent variable. Using a cohort of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 2008-2009, 12 different methods were used for estimation of intensive care (ICU) length of stay. These encompassed risk-adjusted regression analysis of firstly: log LOS using OLS, linear mixed model [LMM], treatment effects, skew-normal and skew-t models; and secondly: unmodified (raw) LOS via OLS, generalised linear models [GLMs] with log-link and 4 different distributions [Poisson, gamma, negative binomial and inverse-Gaussian], extended estimating equations [EEE] and a finite mixture model including a gamma distribution. A fixed covariate list and ICU-site clustering with robust variance were utilised for model fitting with split-sample determination (80%) and validation (20%) data sets, and model simulation was undertaken to establish over-fitting (Copas test). Indices of model specification using Bayesian information criterion [BIC: lower values preferred] and residual analysis as well as predictive performance (R2, concordance correlation coefficient (CCC), mean absolute error [MAE]) were established for each estimator. The data-set consisted of 111663 patients from 131 ICUs; with mean(SD) age 60.6(18.8) years, 43.0% were female, 40.7% were mechanically ventilated and ICU mortality was 7.8%. ICU length-of-stay was 3.4(5.1) (median 1.8, range (0.17-60)) days and demonstrated marked kurtosis and right skew (29.4 and 4.4 respectively). BIC showed considerable spread, from a maximum of 509801 (OLS-raw scale) to a minimum of 210286 (LMM). R2 ranged from 0.22 (LMM) to 0.17 and the CCC from 0.334 (LMM) to 0.149, with MAE 2.2-2.4. Superior residual behaviour was established for the log-scale estimators
Health-based risk adjustment: improving the pharmacy-based cost group model by adding diagnostic cost groups.

PubMed

Prinsze, Femmeke J; van Vliet, René C J A

Since 1991, risk-adjusted premium subsidies have existed in the Dutch social health insurance sector, which covered about two-thirds of the population until 2006. In 2002, pharmacy-based cost groups (PCGs) were included in the demographic risk adjustment model, which improved the goodness-of-fit, as measured by the R2, to 11.5%. The model's R2 reached 22.8% in 2004, when inpatient diagnostic information was added in the form of diagnostic cost groups (DCGs). PCGs and DCGs appear to be complementary in their ability to predict future costs. PCGs particularly improve the R2 for outpatient expenses, whereas DCGs improve the R2 for inpatient expenses. In 2006, this system of risk-adjusted premium subsidies was extended to cover the entire population.
Risk and Protective Factors at Age 10: Psychological Adjustment in Children With a Cleft Lip and/or Palate.

PubMed

Feragen, Kristin Billaud; Stock, Nicola Marie

2016-03-01

Objective To explore psychological functioning in children with a cleft at age 10 from a broad perspective, including cognitive, emotional, behavioral, appearance-related, and social adjustment. High-risk groups were identified within each area of adjustment to investigate whether vulnerable children were found across domains or whether risk was limited to specific areas of adjustment. Methods Retrospective chart review from psychological assessments at age 10 (N = 845). The effects of gender, cleft visibility, and the presence of an additional condition were investigated. Results were compared with large national samples. Measures Personality Inventory for Children, Child Experience Questionnaire, Strengths and Difficulties Questionnaire, Satisfaction With Appearance scale. Results The factor affecting psychological adjustment on most domains was the presence of an associated condition in addition to the cleft. As expected, no support was found for cleft visibility as a risk factor, while there were some gender differences related to emotional difficulties and attention. Correlation analyses of risk groups pointed to an association between social experiences and emotional adjustment and between social and behavioral adjustment; whereas, dissatisfaction with appearance was not related to any other domains of risk at age 10. Conclusions The results point to the importance of early screening and assessment of children born with a cleft to identify possible associated conditions and offer adapted and appropriate treatment and care. Future research should investigate how protective factors could counteract potential risk in children with a cleft.
Anthropometric measures and absolute cardiovascular risk estimates in the Australian Diabetes, Obesity and Lifestyle (AusDiab) Study.

PubMed

Chen, Lei; Peeters, Anna; Magliano, Dianna J; Shaw, Jonathan E; Welborn, Timothy A; Wolfe, Rory; Zimmet, Paul Z; Tonkin, Andrew M

2007-12-01

Framingham risk functions are widely used for prediction of future cardiovascular disease events. They do not, however, include anthropometric measures of overweight or obesity, now considered a major cardiovascular disease risk factor. We aimed to establish the most appropriate anthropometric index and its optimal cutoff point for use as an ancillary measure in clinical practice when identifying people with increased absolute cardiovascular risk estimates. Analysis of a population-based, cross-sectional survey was carried out. The 1991 Framingham prediction equations were used to compute 5 and 10-year risks of cardiovascular or coronary heart disease in 7191 participants from the Australian Diabetes, Obesity and Lifestyle Study (1999-2000). Receiver operating characteristic curve analysis was used to compare measures of body mass index (BMI), waist circumference, and waist-to-hip ratio in identifying participants estimated to be at 'high', or at 'intermediate or high' absolute risk. After adjustment for BMI and age, waist-to-hip ratio showed stronger correlation with absolute risk estimates than waist circumference. The areas under the receiver operating characteristic curve for waist-to-hip ratio (0.67-0.70 in men, 0.64-0.74 in women) were greater than those for waist circumference (0.60-0.65, 0.59-0.71) or BMI (0.52-0.59, 0.53-0.66). The optimal cutoff points of BMI, waist circumference and waist-to-hip ratio to predict people at 'high', or at 'intermediate or high' absolute risk estimates were 26 kg/m2, 95 cm and 0.90 in men, and 25-26 kg/m2, 80-85 cm and 0.80 in women, respectively. Measurement of waist-to-hip ratio is more useful than BMI or waist circumference in the identification of individuals estimated to be at increased risk for future primary cardiovascular events.
Measuring Profitability Impacts of Information Technology: Use of Risk Adjusted Measures.

ERIC Educational Resources Information Center

Singh, Anil; Harmon, Glynn

2003-01-01

Focuses on understanding how investments in information technology are reflected in the income statements and balance sheets of firms. Shows that the relationship between information technology investments and corporate profitability is much better explained by using risk-adjusted measures of corporate profitability than using the same measures…
Estimated dietary dioxin exposure and breast cancer risk among women from the French E3N prospective cohort.

PubMed

Danjou, Aurélie M N; Fervers, Béatrice; Boutron-Ruault, Marie-Christine; Philip, Thierry; Clavel-Chapelon, Françoise; Dossus, Laure

2015-03-17

Dioxins are environmental and persistent pollutants mostly emitted from combustion facilities (e.g. waste incinerators, metal and cement industries). Known to be endocrine disrupting chemicals, dioxins are suspected to increase breast cancer (BC) risk. Although diet is considered the primary source of dioxin exposure, no previous study has been published on dietary dioxin exposure in relation to BC risk. We aimed to assess dietary dioxin exposure among women from the E3N cohort and estimate BC risk associated with this exposure. The study included 63,830 women from the E3N cohort who completed a diet history questionnaire (DHQ) in 1993 and were followed until 2008. Dietary dioxin exposure was estimated by combining consumption data from the E3N DHQ and food dioxin contamination data from a French national monitoring program. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated by Cox models adjusted for BC risk factors. Mean dietary dioxin exposure was estimated at 1.3 ± 0.4 pg/kg body weight (BW)/day. A 0.4 pg/kg BW/d increase in dioxin intake was not associated with overall BC risk (HR = 1.00; 95% CI: 0.96, 1.05). A significant decrease in risk of estrogen receptor negative (ER-)/progesterone receptor negative (PR-) tumors was observed among post-menopausal women in the upper quartile of estimated dioxin intake (HR for Q4 vs. Q1: 0.65; 95% CI: 0.45, 0.96; P for trend across quartiles = 0.0463). Overall, no association between estimated dietary dioxin exposure and BC risk was found among E3N women. Further studies should include both dietary and environmental exposures to determine whether low-dose dioxin exposure is associated with BC risk.
Balancing the risks and benefits of drinking water disinfection: disability adjusted life-years on the scale.

PubMed

Havelaar, A H; De Hollander, A E; Teunis, P F; Evers, E G; Van Kranen, H J; Versteegh, J F; Van Koten, J E; Slob, W

2000-04-01

To evaluate the applicability of disability adjusted life-years (DALYs) as a measure to compare positive and negative health effects of drinking water disinfection, we conducted a case study involving a hypothetical drinking water supply from surface water. This drinking water supply is typical in The Netherlands. We compared the reduction of the risk of infection with Cryptosporidium parvum by ozonation of water to the concomitant increase in risk of renal cell cancer arising from the production of bromate. We applied clinical, epidemiologic, and toxicologic data on morbidity and mortality to calculate the net health benefit in DALYs. We estimated the median risk of infection with C. parvum as 10(-3)/person-year. Ozonation reduces the median risk in the baseline approximately 7-fold, but bromate is produced in a concentration above current guideline levels. However, the health benefits of preventing gastroenteritis in the general population and premature death in patients with acquired immunodeficiency syndrome outweigh health losses by premature death from renal cell cancer by a factor of > 10. The net benefit is approximately 1 DALY/million person-years. The application of DALYs in principle allows us to more explicitly compare the public health risks and benefits of different management options. In practice, the application of DALYs may be hampered by the substantial degree of uncertainty, as is typical for risk assessment.
HIV quality report cards: impact of case-mix adjustment and statistical methods.

PubMed

Ohl, Michael E; Richardson, Kelly K; Goto, Michihiko; Vaughan-Sarrazin, Mary; Schweizer, Marin L; Perencevich, Eli N

2014-10-15

There will be increasing pressure to publicly report and rank the performance of healthcare systems on human immunodeficiency virus (HIV) quality measures. To inform discussion of public reporting, we evaluated the influence of case-mix adjustment when ranking individual care systems on the viral control quality measure. We used data from the Veterans Health Administration (VHA) HIV Clinical Case Registry and administrative databases to estimate case-mix adjusted viral control for 91 local systems caring for 12 368 patients. We compared results using 2 adjustment methods, the observed-to-expected estimator and the risk-standardized ratio. Overall, 10 913 patients (88.2%) achieved viral control (viral load ≤400 copies/mL). Prior to case-mix adjustment, system-level viral control ranged from 51% to 100%. Seventeen (19%) systems were labeled as low outliers (performance significantly below the overall mean) and 11 (12%) as high outliers. Adjustment for case mix (patient demographics, comorbidity, CD4 nadir, time on therapy, and income from VHA administrative databases) reduced the number of low outliers by approximately one-third, but results differed by method. The adjustment model had moderate discrimination (c statistic = 0.66), suggesting potential for unadjusted risk when using administrative data to measure case mix. Case-mix adjustment affects rankings of care systems on the viral control quality measure. Given the sensitivity of rankings to selection of case-mix adjustment methods-and potential for unadjusted risk when using variables limited to current administrative databases-the HIV care community should explore optimal methods for case-mix adjustment before moving forward with public reporting. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
The New York Sepsis Severity Score: Development of a Risk-Adjusted Severity Model for Sepsis.

PubMed

Phillips, Gary S; Osborn, Tiffany M; Terry, Kathleen M; Gesten, Foster; Levy, Mitchell M; Lemeshow, Stanley

2018-05-01

In accordance with Rory's Regulations, hospitals across New York State developed and implemented protocols for sepsis recognition and treatment to reduce variations in evidence informed care and preventable mortality. The New York Department of Health sought to develop a risk assessment model for accurate and standardized hospital mortality comparisons of adult septic patients across institutions using case-mix adjustment. Retrospective evaluation of prospectively collected data. Data from 43,204 severe sepsis and septic shock patients from 179 hospitals across New York State were evaluated. Prospective data were submitted to a database from January 1, 2015, to December 31, 2015. None. Maximum likelihood logistic regression was used to estimate model coefficients used in the New York State risk model. The mortality probability was estimated using a logistic regression model. Variables to be included in the model were determined as part of the model-building process. Interactions between variables were included if they made clinical sense and if their p values were less than 0.05. Model development used a random sample of 90% of available patients and was validated using the remaining 10%. Hosmer-Lemeshow goodness of fit p values were considerably greater than 0.05, suggesting good calibration. Areas under the receiver operator curve in the developmental and validation subsets were 0.770 (95% CI, 0.765-0.775) and 0.773 (95% CI, 0.758-0.787), respectively, indicating good discrimination. Development and validation datasets had similar distributions of estimated mortality probabilities. Mortality increased with rising age, comorbidities, and lactate. The New York Sepsis Severity Score accurately estimated the probability of hospital mortality in severe sepsis and septic shock patients. It performed well with respect to calibration and discrimination. This sepsis-specific model provides an accurate, comprehensive method for standardized mortality comparison of adult
Risk estimation using probability machines

PubMed Central

2014-01-01

Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306
Risk estimation using probability machines.

PubMed

Dasgupta, Abhijit; Szymczak, Silke; Moore, Jason H; Bailey-Wilson, Joan E; Malley, James D

2014-03-01

Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a "risk machine", will share properties from the statistical machine that it is derived from.

Impact of risk factors on cardiovascular risk: a perspective on risk estimation in a Swiss population.

PubMed

Chrubasik, Sigrun A; Chrubasik, Cosima A; Piper, Jörg; Schulte-Moenting, Juergen; Erne, Paul

2015-01-01

In models and scores for estimating cardiovascular risk (CVR), the relative weightings given to blood pressure measurements (BPMs), and biometric and laboratory variables are such that even large differences in blood pressure lead to rather low differences in the resulting total risk when compared with other concurrent risk factors. We evaluated this phenomenon based on the PROCAM score, using BPMs made by volunteer subjects at home (HBPMs) and automated ambulatory BPMs (ABPMs) carried out in the same subjects. A total of 153 volunteers provided the data needed to estimate their CVR by means of the PROCAM formula. Differences (deltaCVR) between the risk estimated by entering the ABPM and that estimated with the HBPM were compared with the differences (deltaBPM) between the ABPM and the corresponding HBPM. In addition to the median values (= second quartile), the first and third quartiles of blood pressure profiles were also considered. PROCAM risk values were converted to European Society of Cardiology (ESC) risk values and all participants were assigned to the risk groups low, medium and high. Based on the PROCAM score, 132 participants had a low risk for suffering myocardial infarction, 16 a medium risk and 5 a high risk. The calculated ESC scores classified 125 participants into the low-risk group, 26 into the medium- and 2 into the high-risk group for death from a cardiovascular event. Mean ABPM tended to be higher than mean HBPM. Use of mean systolic ABPM or HBPM in the PROCAM formula had no major impact on the risk level. Our observations are in agreement with the rather low weighting of blood pressure as risk determinant in the PROCAM score. BPMs assessed with different methods had relatively little impact on estimation of cardiovascular risk in the given context of other important determinants. The risk calculations in our unselected population reflect the given classification of Switzerland as a so-called cardiovascular "low risk country".
45 CFR 153.740 - Failure to comply with HHS-operated risk adjustment and reinsurance data requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... adjustment data submission and data storage requirements set forth in §§ 153.610 through 153.630, HHS may... adjustment and reinsurance data requirements. 153.740 Section 153.740 Public Welfare Department of Health and... CORRIDORS, AND RISK ADJUSTMENT UNDER THE AFFORDABLE CARE ACT Distributed Data Collection for HHS-Operated...
Dynamically adjustable foot-ground contact model to estimate ground reaction force during walking and running.

PubMed

Jung, Yihwan; Jung, Moonki; Ryu, Jiseon; Yoon, Sukhoon; Park, Sang-Kyoon; Koo, Seungbum

2016-03-01

Human dynamic models have been used to estimate joint kinetics during various activities. Kinetics estimation is in demand in sports and clinical applications where data on external forces, such as the ground reaction force (GRF), are not available. The purpose of this study was to estimate the GRF during gait by utilizing distance- and velocity-dependent force models between the foot and ground in an inverse-dynamics-based optimization. Ten males were tested as they walked at four different speeds on a force plate-embedded treadmill system. The full-GRF model whose foot-ground reaction elements were dynamically adjusted according to vertical displacement and anterior-posterior speed between the foot and ground was implemented in a full-body skeletal model. The model estimated the vertical and shear forces of the GRF from body kinematics. The shear-GRF model with dynamically adjustable shear reaction elements according to the input vertical force was also implemented in the foot of a full-body skeletal model. Shear forces of the GRF were estimated from body kinematics, vertical GRF, and center of pressure. The estimated full GRF had the lowest root mean square (RMS) errors at the slow walking speed (1.0m/s) with 4.2, 1.3, and 5.7% BW for anterior-posterior, medial-lateral, and vertical forces, respectively. The estimated shear forces were not significantly different between the full-GRF and shear-GRF models, but the RMS errors of the estimated knee joint kinetics were significantly lower for the shear-GRF model. Providing COP and vertical GRF with sensors, such as an insole-type pressure mat, can help estimate shear forces of the GRF and increase accuracy for estimation of joint kinetics. Copyright © 2016 Elsevier B.V. All rights reserved.
Relationship between two indicators of coronary risk estimated by the Framingham Risk Score and the number of metabolic syndrome components in Japanese male manufacturing workers.

PubMed

Kawada, Tomoyuki; Otsuka, Toshiaki; Inagaki, Hirofumi; Wakayama, Yoko; Li, Qing; Katsumata, Masao

2009-10-01

The Framingham Risk Score (FRS) has frequently been used in the United States to predict the 10-year risk of coronary heart disease (CHD). Components of the metabolic syndrome and several lifestyle factors have also been evaluated to estimate the risk of CHD. To determine the relationship between the FRS and components of metabolic syndrome as coronary risk indicators, the authors conducted a cross-sectional study of 2,619 Japanese male workers, ranging in age from 40 to 64 years, at a single workplace. Although the estimation by the FRS and metabolic syndrome involved some different factors, significant association of the risk estimated by the 2 methods was observed. When logistic regression analysis was conducted with adjustment for several lifestyle factors, the FRS and serum insulin were found to be significantly associated with the risk of likelihood of metabolic syndrome. The odds ratios and 95% confidence intervals of FRS by per standard deviation increment and serum insulin by increasing 1 microIU/mL for the prediction of metabolic syndrome were 2.50 (2.17-2.88) and 1.24 (1.20-1.27), respectively. A preventive effect of abstaining from drinking every day and eating breakfast almost daily against the likelihood of metabolic syndrome was also observed. In conclusion, the FRS and insulin were found to be significantly associated with the risk of likelihood of metabolic syndrome, even after controlling for weight change.
Risk adjustment for case mix and the effect of surgeon volume on morbidity.

PubMed

Maas, Matthew B; Jaff, Michael R; Rordorf, Guy A

2013-06-01

Retrospective studies of large administrative databases have shown higher mortality for procedures performed by low-volume surgeons, but the adequacy of risk adjustment in those studies is in doubt. To determine whether the relationship between surgeon volume and outcomes is an artifact of case mix using a prospective sample of carotid endarterectomy cases. Observational cohort study from January 1, 2008, through December 31, 2010, with preoperative, immediate postoperative, and 30-day postoperative assessments acquired by independent monitors. Urban, tertiary academic medical center. All 841 patients who underwent carotid endarterectomy performed by a vascular surgeon or cerebrovascular neurosurgeon at the institution. Carotid endarterectomy without another concurrent surgery. Stroke, death, and other surgical complications occurring within 30 days of surgery along with other case data. A low-volume surgeon performed 40 or fewer cases per year. Variables used in a comparison administrative database study, as well as variables identified by our univariate analysis, were used for adjusted analyses to assess for an association between low-volume surgeons and the rate of stroke and death as well as other complications. RESULTS The rate of stroke and death was 6.9% for low-volume surgeons and 2.0% for high-volume surgeons (P = .001). Complications were similarly higher (13.4% vs 7.2%, P = .008). Low-volume surgeons performed more nonelective cases. Low-volume surgeons were significantly associated with stroke and death in the unadjusted analysis as well as after adjustment with variables used in the administrative database study (odds ratio, 3.61; 95% CI, 1.70-7.67, and odds ratio, 3.68; 95% CI, 1.72-7.89, respectively). However, adjusting for the significant disparity of American Society of Anesthesiologists Physical Status classification in case mix eliminated the effect of surgeon volume on the rate of stroke and death (odds ratio, 1.65; 95% CI, 0.59-4.64) and other
Hispanic Americans Baseline Alcohol Survey (HABLAS): Effects of Container Size Adjustments on Estimates of Alcohol Consumption Across Hispanic National Groups

PubMed Central

Mills, Britain A.; Harris, T. Robert

2012-01-01

Objective: This study was conducted to examine discrepancies in alcohol consumption estimates between a self-reported standard quantity—frequency measure and an adjusted version based on respondents’ typically used container size. Method: Using a multistage cluster sample design, 5,224 Hispanic individuals 18 years of age and older were selected from the household population in five metropolitan areas of the United States: Miami, New York, Philadelphia, Houston, and Los Angeles. The survey-weighted response rate was 76%. Personal interviews lasting an average of 1 hour were conducted in respondents’ homes in either English or Spanish. Results: The overall effect of container adjustment was to increase estimates of ethanol consumption by 68% for women (range across Hispanic groups: 17%–99%) and 30% for men (range: 14%–42%). With the exception of female Cuban American, Mexican American, and South/Central American beer drinkers and male Cuban American wine drinkers, all percentage differences between unadjusted and container-adjusted estimates were positive. Second, container adjustments produced the largest change for volume of distilled spirits, followed by wine and beer. Container size adjustments generally produced larger percentage increases in consumption estimates for the higher volume drinkers, especially the upper tertile of female drinkers. Conclusions: Self-reported alcohol consumption based on standard drinks underreports consumption when compared with reports based on the amount of alcohol poured into commonly used containers. PMID:22152669
Hispanic Americans Baseline Alcohol Survey (HABLAS): effects of container size adjustments on estimates of alcohol consumption across Hispanic national groups.

PubMed

Caetano, Raul; Mills, Britain A; Harris, T Robert

2012-01-01

This study was conducted to examine discrepancies in alcohol consumption estimates between a self-reported standard quantity-frequency measure and an adjusted version based on respondents' typically used container size. Using a multistage cluster sample design, 5,224 Hispanic individuals 18 years of age and older were selected from the household population in five metropolitan areas of the United States: Miami, New York, Philadelphia, Houston, and Los Angeles. The survey-weighted response rate was 76%. Personal interviews lasting an average of 1 hour were conducted in respondents' homes in either English or Spanish. The overall effect of container adjustment was to increase estimates of ethanol consumption by 68% for women (range across Hispanic groups: 17%-99%) and 30% for men (range: 14%-42%). With the exception of female Cuban American, Mexican American, and South/Central American beer drinkers and male Cuban American wine drinkers, all percentage differences between unadjusted and container-adjusted estimates were positive. Second, container adjustments produced the largest change for volume of distilled spirits, followed by wine and beer. Container size adjustments generally produced larger percentage increases in consumption estimates for the higher volume drinkers, especially the upper tertile of female drinkers. Self-reported alcohol consumption based on standard drinks underreports consumption when compared with reports based on the amount of alcohol poured into commonly used containers.
Graphs to estimate an individualized risk of breast cancer.

PubMed

Benichou, J; Gail, M H; Mulvihill, J J

1996-01-01

Clinicians who counsel women about their risk for developing breast cancer need a rapid method to estimate individualized risk (absolute risk), as well as the confidence limits around that point. The Breast Cancer Detection Demonstration Project (BCDDP) model (sometimes called the Gail model) assumes no genetic model and simultaneously incorporates five risk factors, but involves cumbersome calculations and interpolations. This report provides graphs to estimate the absolute risk of breast cancer from the BCDDP model. The BCDDP recruited 280,000 women from 1973 to 1980 who were monitored for 5 years. From this cohort, 2,852 white women developed breast cancer and 3,146 controls were selected, all with complete risk-factor information. The BCDDP model, previously developed from these data, was used to prepare graphs that relate a specific summary relative-risk estimate to the absolute risk of developing breast cancer over intervals of 10, 20, and 30 years. Once a summary relative risk is calculated, the appropriate graph is chosen that shows the 10-, 20-, or 30-year absolute risk of developing breast cancer. A separate graph gives the 95% confidence limits around the point estimate of absolute risk. Once a clinician rules out a single gene trait that predisposes to breast cancer and elicits information on age and four risk factors, the tables and figures permit an estimation of a women's absolute risk of developing breast cancer in the next three decades. These results are intended to be applied to women who undergo regular screening. They should be used only in a formal counseling program to maximize a woman's understanding of the estimates and the proper use of them.
Risk and Protective Factors for Psychological Adjustment and Grades among Adolescents.

ERIC Educational Resources Information Center

Voydanoff, Patricia; Donnelly, Brenda W.

1999-01-01

Examines the ways in which two risk factors: negative peer behavior and time spent without an adult, and two protective factors: adolescent resources and parental behavior influence psychological adjustment and grades among adolescents ages 10 to 17 (N=745). Results indicate that negative peer behavior is inversely related to adolescent well…
Family-oriented cardiac risk estimator: a Java web-based applet.

PubMed

Crouch, Michael A; Jadhav, Ashwin

2003-01-01

We developed a Java applet that calculates four different estimates of a person's 10-year risk for heart attack: (1) Estimate based on Framingham equation (2) Framingham equation estimate modified by C-reactive protein (CRP) level (3) Framingham estimate modified by family history of heart disease in parents or siblings (4) Framingham estimate modified by both CRP and family heart disease history. This web-based, family-oriented cardiac risk estimator uniquely considers family history and CRP while estimating risk.
Risk and Protective Factors at Age 16: Psychological Adjustment in Children With a Cleft Lip and/or Palate.

PubMed

Feragen, Kristin Billaud; Stock, Nicola Marie; Kvalem, Ingela Lundin

2015-09-01

Explore psychological functioning in adolescents with a cleft at age 16 from a broad perspective, including cognitive, emotional, behavioral, appearance-related, and psychosocial adjustment. High-risk groups were identified within each area of adjustment to investigate whether vulnerable adolescents were found across domains or whether risk was limited to specific areas of adjustment. Cross-sectional data based on psychological assessments at age 16 (N = 857). The effect of gender, cleft visibility, and the presence of an additional condition were investigated on all outcome variables. Results were compared with large national samples. Hopkins Symptom Checklist, Harter Self-Perception Scale for Adolescents, Child Experience Questionnaire, and Satisfaction With Appearance scale. The main factor influencing psychological adjustment across domains was gender, with girls in general reporting more psychological problems, as seen in reference groups. The presence of an additional condition also negatively affected some of the measures. No support was found for cleft visibility as a risk factor except for dissatisfaction with appearance. Correlation analyses of risk groups seem to point to an association between social and emotional risk and between social risk and dissatisfaction with appearance. Associations between other domains were found to be weak. The results point to areas of both risk and strength in adolescents born with a cleft lip and/or palate. Future research should investigate how protective factors could counteract potential risk in adolescents with a cleft.
Process monitoring in intensive care with the use of cumulative expected minus observed mortality and risk-adjusted P charts.

PubMed

Cockings, Jerome G L; Cook, David A; Iqbal, Rehana K

2006-02-01

A health care system is a complex adaptive system. The effect of a single intervention, incorporated into a complex clinical environment, may be different from that expected. A national database such as the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme in the UK represents a centralised monitoring, surveillance and reporting system for retrospective quality and comparative audit. This can be supplemented with real-time process monitoring at a local level for continuous process improvement, allowing early detection of the impact of both unplanned and deliberately imposed changes in the clinical environment. Demographic and UK Acute Physiology and Chronic Health Evaluation II (APACHE II) data were prospectively collected on all patients admitted to a UK regional hospital between 1 January 2003 and 30 June 2004 in accordance with the ICNARC Case Mix Programme. We present a cumulative expected minus observed (E-O) plot and the risk-adjusted p chart as methods of continuous process monitoring. We describe the construction and interpretation of these charts and show how they can be used to detect planned or unplanned organisational process changes affecting mortality outcomes. Five hundred and eighty-nine adult patients were included. The overall death rate was 0.78 of predicted. Calibration showed excess survival in ranges above 30% risk of death. The E-O plot confirmed a survival above that predicted. Small transient variations were seen in the slope that could represent random effects, or real but transient changes in the quality of care. The risk-adjusted p chart showed several observations below the 2 SD control limits of the expected mortality rate. These plots provide rapid analysis of risk-adjusted performance suitable for local application and interpretation. The E-O chart provided rapid easily visible feedback of changes in risk-adjusted mortality, while the risk-adjusted p chart allowed statistical evaluation. Local analysis of
New anthropometric indices or old ones: which perform better in estimating cardiovascular risks in Chinese adults.

PubMed

Wang, Fei; Chen, Yintao; Chang, Ye; Sun, Guozhe; Sun, Yingxian

2018-01-30

Various anthropometric indices can be used to estimate obesity, and it is important to determine which one is the best in predicting the risk of coronary heart disease (CHD) and to define the optimal cut-off point for the best index. This cross-sectional study investigated a consecutive sample of 11,247 adults, who had lived in rural areas of China and were older than 35 years of age. Eight obesity indices, including the body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), abdominal volume index (AVI), body adiposity index (BAI), body roundness index (BRI) and a body shape index (ABSI) were investigated. The risk of CHD was evaluated by the 10-year coronary event risk (Framingham risk score). Receiver operating characteristic (ROC) curve analyses were used to evaluate the predictive ability of the obesity indices for CHD risk. Of the whole population, 3636 (32.32%) participants had a risk score higher than 10%. Those who suffered medium or high CHD risk were more likely to have higher mean anthropometric indices, except for BMI in males. In the multivariate-adjusted logistic regression, all these anthropometric measurements were statistically associated with CHD risk in males. After adjusting for all the possible confounders, these anthropometric measurements, except for ABSI, remained as independent indicators of CHD risk in females. According to the ROC analyses, ABSI provided the largest area under the curve (AUC) value in males, and BMI showed the lowest AUC value, with AUC varying from 0.52 to 0.60. WHtR and BRI provided the largest AUC value in female, and similarly, BMI showed the lowest AUC value, with AUC varying from 0.59 to 0.70. The optimal cut-off values were as follows: WHtR (females: 0.54), BRI (females: 4.21), and ABSI (males: 0.078). ABSI was the best anthropometric index for estimating CHD risk in males, and WHtR and BRI were the best indicators in females. Males should maintain an ABSI of less
An Estimate of Attributable Cases of Alzheimer Disease and Vascular Dementia due to Modifiable Risk Factors: The Impact of Primary Prevention in Europe and in Italy.

PubMed

Mayer, Flavia; Di Pucchio, Alessandra; Lacorte, Eleonora; Bacigalupo, Ilaria; Marzolini, Fabrizio; Ferrante, Gianluigi; Minardi, Valentina; Masocco, Maria; Canevelli, Marco; Di Fiandra, Teresa; Vanacore, Nicola

2018-01-01

Up to 53.7% of all cases of dementia are assumed to be due to Alzheimer disease (AD), while 15.8% are considered to be due to vascular dementia (VaD). In Europe, about 3 million cases of AD could be due to 7 potentially modifiable risk factors: diabetes, midlife hypertension and/or obesity, physical inactivity, depression, smoking, and low educational level. To estimate the number of VaD cases in Europe and the number of AD and VaD cases in Italy attributable to these 7 potentially modifiable risk factors. Assuming the nonindependence of the 7 risk factors, the adjusted combined population attributable risk (PAR) was estimated for AD and VaD. In Europe, adjusted combined PAR was 31.4% for AD and 37.8% for VaD. The total number of attributable cases was 3,033,000 for AD and 873,000 for VaD. In Italy, assuming a 20% reduction of the prevalence of each risk factor, adjusted combined PAR decreased from 45.2 to 38.9% for AD and from 53.1 to 46.6% for VaD, implying a 6.4 and 6.5% reduction in the prevalence of AD and VaD, respectively. A relevant reduction of AD and VaD cases in Europe and Italy could be obtained through primary prevention.
State infant mortality: an ecologic study to determine modifiable risks and adjusted infant mortality rates.

PubMed

Paul, David A; Mackley, Amy; Locke, Robert G; Stefano, John L; Kroelinger, Charlan

2009-05-01

To determine factors contributing to state infant mortality rates (IMR) and develop an adjusted IMR in the United States for 2001 and 2002. Ecologic study of factors contributing to state IMR. State IMR for 2001 and 2002 were obtained from the United States linked death and birth certificate data from the National Center for Health Statistics. Factors investigated using multivariable linear regression included state racial demographics, ethnicity, state population, median income, education, teen birth rate, proportion of obesity, smoking during pregnancy, diabetes, hypertension, cesarean delivery, prenatal care, health insurance, self-report of mental illness, and number of in-vitro fertilization procedures. Final risk adjusted IMR's were standardized and states were compared with the United States adjusted rates. Models for IMR in individual states in 2001 (r2 = 0.66, P < 0.01) and 2002 (r2 = 0.81, P < 0.01) were tested. African-American race, teen birth rate, and smoking during pregnancy remained independently associated with state infant mortality rates for 2001 and 2002. Ninety five percent confidence intervals (CI) were calculated around the regression lines to model the expected IMR. After adjustment, some states maintained a consistent IMR; for instance, Vermont and New Hampshire remained low, while Delaware and Louisiana remained high. However, other states such as Mississippi, which have traditionally high infant mortality rates, remained within the expected 95% CI for IMR after adjustment indicating confounding affected the initial unadjusted rates. Non-modifiable demographic variables, including the percentage of non-Hispanic African-American and Hispanic populations of the state are major factors contributing to individual variation in state IMR. Race and ethnicity may confound or modify the IMR in states that shifted inside or outside the 95% CI following adjustment. Other factors including smoking during pregnancy and teen birth rate, which are
Risk-adjusted clinical outcomes in patients enrolled in a bloodless program

PubMed Central

Frank, Steven M.; Wick, Elizabeth C.; Dezern, Amy E.; Ness, Paul M.; Wasey, Jack O.; Pippa, Andrew C.; Dackiw, Elizabeth; Resar, Linda M.S.

2014-01-01

BACKGROUND Although clinical outcomes have been reported for patients who do not accept allogeneic blood transfusion (ABT), many previous studies lack a control group, fail to use risk adjustment, and focus exclusively on cardiac surgery. STUDY DESIGN AND METHODS We report a risk-adjusted, propensity score–matched, retrospective case-control study of clinical outcomes for inpatients who did not accept ABT (bloodless, n = 294) and those who did accept ABT (control, n = 1157). Multidisciplinary specialized care was rendered to the bloodless patients to conserve blood and optimize clinical outcomes. Differences in hemoglobin (Hb), mortality, five morbid outcomes, and hospital charges and costs were compared. Subgroups of medical and surgical patients were analyzed, and independent predictors of outcome were determined by multivariate analysis. RESULTS Overall, mortality was lower in the bloodless group (0.7%) than in the control group (2.7%; p = 0.046), primarily attributed to the surgical subgroup. After risk adjustment, bloodless care was not an independent predictor of the composite adverse outcome (death or any morbid event; p = 0.91; odds ratio, 1.02; 95% confidence interval, 0.68–1.53). Discharge Hb concentrations were similar in the bloodless (10.8 ± 2.7 g/dL) and control (10.9 ± 2.3 g/dL) groups (p = 0.42). Total and direct hospital costs were 12% (p = 0.02) and 18% (p = 0.02) less, respectively, in the bloodless patients, a difference attributed to the surgical subgroup. CONCLUSIONS Using appropriate blood conservation measures for patients who do not accept ABT results in similar or better outcomes and is associated with equivalent or lower costs. This specialized care may be beneficial even for those patients who accept ABT. PMID:24942198
Estimating the burden of disease attributable to four selected environmental risk factors in South Africa.

PubMed

Norman, Rosana; Bradshaw, Debbie; Lewin, Simon; Cairncross, Eugene; Nannan, Nadine; Vos, Theo

2010-01-01

The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure. The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty. Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease. This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence
Funding issues for Victorian hospitals: the risk-adjusted vision beyond casemix funding.

PubMed

Antioch, K; Walsh, M

2000-01-01

This paper discusses casemix funding issues in Victoria impacting on teaching hospitals. For casemix payments to be acceptable, the average price and cost weights must be set at an appropriate standard. The average price is based on a normative, policy basis rather than benchmarking. The 'averaging principle' inherent in cost weights has resulted in some AN-DRG weights being too low for teaching hospitals that are key State-wide providers of high complexity services such as neurosurgery and trauma. Casemix data have been analysed using international risk adjustment methodologies to successfully negotiate with the Victorian State Government for specified grants for several high complexity AN-DRGs. A risk-adjusted capitation funding model has also been developed for cystic fibrosis patients treated by The Alfred, called an Australian Health Maintenance Organisation (AHMO). This will facilitate the development of similar models by both the Victorian and Federal governments.
Risk estimates of mortality attributed to low concentrations of ambient fine particulate matter in the Canadian community health survey cohort.

PubMed

Pinault, Lauren; Tjepkema, Michael; Crouse, Daniel L; Weichenthal, Scott; van Donkelaar, Aaron; Martin, Randall V; Brauer, Michael; Chen, Hong; Burnett, Richard T

2016-02-11

Understanding the shape of the relationship between long-term exposure to ambient fine particulate matter (PM2.5) concentrations and health risks is critical for health impact and risk assessment. Studies evaluating the health risks of exposure to low concentrations of PM2.5 are limited. Further, many existing studies lack individual-level information on potentially important behavioural confounding factors. A prospective cohort study was conducted among a subset of participants in a cohort that linked respondents of the Canadian Community Health Survey to mortality (n = 299,500) with satellite-derived ambient PM2.5 estimates. Participants enrolled between 2000 and 2008 were followed to date of death or December 31, 2011. Cox proportional hazards models were used to estimate hazard ratios (HRs) for mortality attributed to PM2.5 exposure, adjusted for individual-level and contextual covariates, including smoking behaviour and body mass index (BMI). Approximately 26,300 non-accidental deaths, of which 32.5 % were due to circulatory disease and 9.1 % were due to respiratory disease, occurred during the follow-up period. Ambient PM2.5 exposures were relatively low (mean = 6.3 μg/m(3)), yet each 10 μg/m(3) increase in exposure was associated with increased risks of non-accidental (HR = 1.26; 95 % CI: 1.19-1.34), circulatory disease (HR = 1.19; 95 % CI: 1.07-1.31), and respiratory disease mortality (HR = 1.52; 95 % CI: 1.26-1.84) in fully adjusted models. Higher hazard ratios were observed for respiratory mortality among respondents who never smoked (HR = 1.97; 95 % CI: 1.24-3.13 vs. HR = 1.45; 95 % CI: 1.17-1.79 for ever smokers), and among obese (BMI ≥ 30) respondents (HR = 1.76; 95 % CI: 1.15-2.69 vs. HR = 1.41; 95 % CI: 1.04-1.91 for normal weight respondents), though differences between groups were not statistically significant. A threshold analysis for non-accidental mortality estimated a threshold concentration of 0 �
Balancing the risks and benefits of drinking water disinfection: disability adjusted life-years on the scale.

PubMed Central

Havelaar, A H; De Hollander, A E; Teunis, P F; Evers, E G; Van Kranen, H J; Versteegh, J F; Van Koten, J E; Slob, W

2000-01-01

To evaluate the applicability of disability adjusted life-years (DALYs) as a measure to compare positive and negative health effects of drinking water disinfection, we conducted a case study involving a hypothetical drinking water supply from surface water. This drinking water supply is typical in The Netherlands. We compared the reduction of the risk of infection with Cryptosporidium parvum by ozonation of water to the concomitant increase in risk of renal cell cancer arising from the production of bromate. We applied clinical, epidemiologic, and toxicologic data on morbidity and mortality to calculate the net health benefit in DALYs. We estimated the median risk of infection with C. parvum as 10(-3)/person-year. Ozonation reduces the median risk in the baseline approximately 7-fold, but bromate is produced in a concentration above current guideline levels. However, the health benefits of preventing gastroenteritis in the general population and premature death in patients with acquired immunodeficiency syndrome outweigh health losses by premature death from renal cell cancer by a factor of > 10. The net benefit is approximately 1 DALY/million person-years. The application of DALYs in principle allows us to more explicitly compare the public health risks and benefits of different management options. In practice, the application of DALYs may be hampered by the substantial degree of uncertainty, as is typical for risk assessment. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 PMID:10753089

A comparison of administrative and physiologic predictive models in determining risk adjusted mortality rates in critically ill patients.

PubMed

Enfield, Kyle B; Schafer, Katherine; Zlupko, Mike; Herasevich, Vitaly; Novicoff, Wendy M; Gajic, Ognjen; Hoke, Tracey R; Truwit, Jonathon D

2012-01-01

Hospitals are increasingly compared based on clinical outcomes adjusted for severity of illness. Multiple methods exist to adjust for differences between patients. The challenge for consumers of this information, both the public and healthcare providers, is interpreting differences in risk adjustment models particularly when models differ in their use of administrative and physiologic data. We set to examine how administrative and physiologic models compare to each when applied to critically ill patients. We prospectively abstracted variables for a physiologic and administrative model of mortality from two intensive care units in the United States. Predicted mortality was compared through the Pearsons Product coefficient and Bland-Altman analysis. A subgroup of patients admitted directly from the emergency department was analyzed to remove potential confounding changes in condition prior to ICU admission. We included 556 patients from two academic medical centers in this analysis. The administrative model and physiologic models predicted mortalities for the combined cohort were 15.3% (95% CI 13.7%, 16.8%) and 24.6% (95% CI 22.7%, 26.5%) (t-test p-value<0.001). The r(2) for these models was 0.297. The Bland-Atlman plot suggests that at low predicted mortality there was good agreement; however, as mortality increased the models diverged. Similar results were found when analyzing a subgroup of patients admitted directly from the emergency department. When comparing the two hospitals, there was a statistical difference when using the administrative model but not the physiologic model. Unexplained mortality, defined as those patients who died who had a predicted mortality less than 10%, was a rare event by either model. In conclusion, while it has been shown that administrative models provide estimates of mortality that are similar to physiologic models in non-critically ill patients with pneumonia, our results suggest this finding can not be applied globally to
Population-based absolute risk estimation with survey data

PubMed Central

Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

2013-01-01

Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614
Rural-Urban Differences in Medicare Quality Outcomes and the Impact of Risk Adjustment.

PubMed

Henning-Smith, Carrie; Kozhimannil, Katy; Casey, Michelle; Prasad, Shailendra; Moscovice, Ira

2017-09-01

There has been considerable debate in recent years about whether, and how, to risk-adjust quality measures for sociodemographic characteristics. However, geographic location, especially rurality, has been largely absent from the discussion. To examine differences by rurality in quality outcomes, and the impact of adjustment for individual and community-level sociodemographic characteristics on quality outcomes. The 2012 Medicare Current Beneficiary Survey, Access to Care module, combined with the 2012 County Health Rankings. All data used were publicly available, secondary data. We merged the 2012 Medicare Current Beneficiary Survey data with the 2012 County Health Rankings data using county of residence. We compared 6 unadjusted quality of care measures for Medicare beneficiaries (satisfaction with care, blood pressure checked, cholesterol checked, flu shot receipt, change in health status, and all-cause annual readmission) by rurality (rural noncore, micropolitan, and metropolitan). We then ran nested multivariable logistic regression models to assess the impact of adjusting for community and individual-level sociodemographic characteristics to determine whether these mediate the rurality difference in quality of care. The relationship between rurality and change in health status was mediated by the inclusion of community-level characteristics; however, adjusting for community and individual-level characteristics caused differences by rurality to emerge in 2 of the measures: blood pressure checked and cholesterol checked. For all quality scores, model fit improved after adding community and individual characteristics. Quality is multifaceted and is impacted by individual and community-level socio-demographic characteristics, as well as by geographic location. Current debates about risk-adjustment procedures should take rurality into account.
School Adjustment of Pupils with ADHD: Cognitive, Emotional and Temperament Risk Factors

ERIC Educational Resources Information Center

Sanchez-Perez, Noelia; Gonzalez-Salinas, Carmen

2013-01-01

From different research perspectives, the cognitive and emotional characteristics associated with ADHD in children have been identified as risk factors for the development of diverse adjustment problems in the school context. Research in nonclinical population can additionally help in understanding ADHD deficits, since children with specific…
A methodological approach to identify external factors for indicator-based risk adjustment illustrated by a cataract surgery register

PubMed Central

2014-01-01

Background Risk adjustment is crucial for comparison of outcome in medical care. Knowledge of the external factors that impact measured outcome but that cannot be influenced by the physician is a prerequisite for this adjustment. To date, a universal and reproducible method for identification of the relevant external factors has not been published. The selection of external factors in current quality assurance programmes is mainly based on expert opinion. We propose and demonstrate a methodology for identification of external factors requiring risk adjustment of outcome indicators and we apply it to a cataract surgery register. Methods Defined test criteria to determine the relevance for risk adjustment are “clinical relevance” and “statistical significance”. Clinical relevance of the association is presumed when observed success rates of the indicator in the presence and absence of the external factor exceed a pre-specified range of 10%. Statistical significance of the association between the external factor and outcome indicators is assessed by univariate stratification and multivariate logistic regression adjustment. The cataract surgery register was set up as part of a German multi-centre register trial for out-patient cataract surgery in three high-volume surgical sites. A total of 14,924 patient follow-ups have been documented since 2005. Eight external factors potentially relevant for risk adjustment were related to the outcome indicators “refractive accuracy” and “visual rehabilitation” 2–5 weeks after surgery. Results The clinical relevance criterion confirmed 2 (“refractive accuracy”) and 5 (“visual rehabilitation”) external factors. The significance criterion was verified in two ways. Univariate and multivariate analyses revealed almost identical external factors: 4 were related to “refractive accuracy” and 7 (6) to “visual rehabilitation”. Two (“refractive accuracy”) and 5 (“visual rehabilitation”) factors
[The concept of risk and its estimation].

PubMed

Zocchetti, C; Della Foglia, M; Colombi, A

1996-01-01

The concept of risk, in relation to human health, is a topic of primary interest for occupational health professionals. A new legislation recently established in Italy (626/94) according to European Community directives in the field of Preventive Medicine, called attention to this topic, and in particular to risk assessment and evaluation. Motivated by this context and by the impression that the concept of risk is frequently misunderstood, the present paper has two aims: the identification of the different meanings of the term "risk" in the new Italian legislation and the critical discussion of some commonly used definitions; and the proposal of a general definition, with the specification of a mathematical expression for quantitative risk estimation. The term risk (and risk estimation, assessment, or evaluation) has mainly referred to three different contexts: hazard identification, exposure assessment, and adverse health effects occurrence. Unfortunately, there are contexts in the legislation in which it is difficult to identify the true meaning of the term. This might cause equivocal interpretations and erroneous applications of the law because hazard evaluation, exposure assessment, and adverse health effects identification are completely different topics that require integrated but distinct approaches to risk management. As far as a quantitative definition of risk is of concern, we suggest an algorithm which connects the three basic risk elements (hazard, exposure, adverse health effects) by means of their probabilities of occurrence: the probability of being exposed (to a definite dose) given that a specific hazard is present (Pr(e[symbol: see text]p)), and the probability of occurrence of an adverse health effect as a consequence of that exposure (Pr(d[symbol: see text]e)). Using these quantitative components, risk can be defined as a sequence of measurable events that starts with hazard identification and terminates with disease occurrence; therefore, the
Relation of Parental Transitions to Boys' Adjustment Problems: I.A. Linear Hypothesis II. Mothers at Risk for Transitions and Unskilled Parenting.

ERIC Educational Resources Information Center

Capaldi, D. M.; Patterson, G. R.

1991-01-01

Examined the adjustment of boys from intact, single-mother, stepfather, and multiple-transition families. Boys who had experienced multiple transitions showed the poorest adjustment. The antisocial mother was most at risk for transitions and unskilled parenting practices, which in turn placed her son at risk for poor adjustment. (BC)
Coherent Risk-Adjusted Decisions Over Time: a Bilevel Programming Approach

DTIC Science & Technology

2015-03-23

AFRL-AFOSR-VA-TR-2015-0310 Coherent Risk-Adjusted Decisions Over Time: a Bilevel Programming Approach Jonathan Eckstein RUTGERS THE STATE UNIVERSITY...FA9550-11-1-0164 5b. GRANT NUMBER FA9550-11-1-0164 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Eckstein, Jonathan Ruszczynski, Andrzej 5d. PROJECT... Jonathan Eckstein a. REPORT U b. ABSTRACT U c. THIS PAGE U 19b. TELEPHONE NUMBER (Include area code) 848-445-0510 Standard Form 298 (Rev. 8/98
[Risk adjusted assessment of quality of perinatal centers - results of perinatal/neonatal quality surveillance in Saxonia].

PubMed

Koch, R; Gmyrek, D; Vogtmann, Ch

2005-12-01

The weak point of the country-wide perinatal/neonatal quality surveillance as a tool for evaluation of achievements of a distinct clinic, is the ignorance of interhospital differences in the case-mix of patients. Therefore, that approach can not result in a reliable bench marking. To adjust the results of quality assessment of different hospitals according to their risk profile of patients by multivariate analysis. The perinatal/neonatal data base of 12.783 newborns of the saxonian quality surveillance from 1998 to 2000 was analyzed. 4 relevant quality indicators of newborn outcome -- a) severe intraventricular hemorrhage in preterm infants < 1500 g, b) death in hospital of preterm infants < 1500 g, c) death in newborns with birth weight > 2500 g and d) hypoxic-ischemic encephalopathy -- were targeted to find out specific risk predictors by considering 26 risk factors. A logistic regression model was used to develop the risk predictors. Risk predictors for the 4 quality indicators could be described by 3 - 9 out of 26 analyzed risk factors. The AUC (ROC)-values for these quality indicators were 82, 89, 89 and 89 %, what signifies their reliability. Using the new specific predictors for calculation the risk adjusted incidence rates of quality indicator yielded in some remarkable changes. The apparent differences in the outcome criteria of analyzed hospitals were found to be much less pronounced. The application of the proposed method for risk adjustment of quality indicators makes it possible to perform a more objective comparison of neonatal outcome criteria between different hospitals or regions.
46 CFR 309.6 - Adjustments for condition, equipment, and other considerations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... of $50,000, an amount estimated by the Maritime Administration as the fair and reasonable value of... considerations. 309.6 Section 309.6 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION EMERGENCY OPERATIONS VALUES FOR WAR RISK INSURANCE § 309.6 Adjustments for condition, equipment, and other...
Risk-adjusted antibiotic consumption in 34 public acute hospitals in Ireland, 2006 to 2014

PubMed Central

Oza, Ajay; Donohue, Fionnuala; Johnson, Howard; Cunney, Robert

2016-01-01

As antibiotic consumption rates between hospitals can vary depending on the characteristics of the patients treated, risk-adjustment that compensates for the patient-based variation is required to assess the impact of any stewardship measures. The aim of this study was to investigate the usefulness of patient-based administrative data variables for adjusting aggregate hospital antibiotic consumption rates. Data on total inpatient antibiotics and six broad subclasses were sourced from 34 acute hospitals from 2006 to 2014. Aggregate annual patient administration data were divided into explanatory variables, including major diagnostic categories, for each hospital. Multivariable regression models were used to identify factors affecting antibiotic consumption. Coefficient of variation of the root mean squared errors (CV-RMSE) for the total antibiotic usage model was very good (11%), however, the value for two of the models was poor (> 30%). The overall inpatient antibiotic consumption increased from 82.5 defined daily doses (DDD)/100 bed-days used in 2006 to 89.2 DDD/100 bed-days used in 2014; the increase was not significant after risk-adjustment. During the same period, consumption of carbapenems increased significantly, while usage of fluoroquinolones decreased. In conclusion, patient-based administrative data variables are useful for adjusting hospital antibiotic consumption rates, although additional variables should also be employed. PMID:27541730
On the Performance of Maximum Likelihood versus Means and Variance Adjusted Weighted Least Squares Estimation in CFA

ERIC Educational Resources Information Center

Beauducel, Andre; Herzberg, Philipp Yorck

2006-01-01

This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no…
Q-adjusting technique applied to vertical deflections estimation in a single-axis rotation INS/GPS integrated system

NASA Astrophysics Data System (ADS)

Zhu, Jing; Wang, Xingshu; Wang, Jun; Dai, Dongkai; Xiong, Hao

2016-10-01

Former studies have proved that the attitude error in a single-axis rotation INS/GPS integrated system tracks the high frequency component of the deflections of the vertical (DOV) with a fixed delay and tracking error. This paper analyses the influence of the nominal process noise covariance matrix Q on the tracking error as well as the response delay, and proposed a Q-adjusting technique to obtain the attitude error which can track the DOV better. Simulation results show that different settings of Q lead to different response delay and tracking error; there exists optimal Q which leads to a minimum tracking error and a comparatively short response delay; for systems with different accuracy, different Q-adjusting strategy should be adopted. In this way, the DOV estimation accuracy of using the attitude error as the observation can be improved. According to the simulation results, the DOV estimation accuracy after using the Q-adjusting technique is improved by approximate 23% and 33% respectively compared to that of the Earth Model EGM2008 and the direct attitude difference method.
An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan.

PubMed

Chang, Hsien-Yen; Weiner, Jonathan P

2010-01-18

Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI) programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG) case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234), while those in both 2002 and 2003 were included for prospective analyses (n = 164,562). Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group) model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster). When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Given the widespread availability of claims data and the superior explanatory
Viscosity-adjusted estimation of pressure head and pump flow with quasi-pulsatile modulation of rotary blood pump for a total artificial heart.

PubMed

Yurimoto, Terumi; Hara, Shintaro; Isoyama, Takashi; Saito, Itsuro; Ono, Toshiya; Abe, Yusuke

2016-09-01

Estimation of pressure and flow has been an important subject for developing implantable artificial hearts. To realize real-time viscosity-adjusted estimation of pressure head and pump flow for a total artificial heart, we propose the table estimation method with quasi-pulsatile modulation of rotary blood pump in which systolic high flow and diastolic low flow phased are generated. The table estimation method utilizes three kinds of tables: viscosity, pressure and flow tables. Viscosity is estimated from the characteristic that differential value in motor speed between systolic and diastolic phases varies depending on viscosity. Potential of this estimation method was investigated using mock circulation system. Glycerin solution diluted with salty water was used to adjust viscosity of fluid. In verification of this method using continuous flow data, fairly good estimation could be possible when differential pulse width modulation (PWM) value of the motor between systolic and diastolic phases was high. In estimation under quasi-pulsatile condition, inertia correction was provided and fairly good estimation was possible when the differential PWM value was high, which was not different from the verification results using continuous flow data. In the experiment of real-time estimation applying moving average method to the estimated viscosity, fair estimation could be possible when the differential PWM value was high, showing that real-time viscosity-adjusted estimation of pressure head and pump flow would be possible with this novel estimation method when the differential PWM value would be set high.
Exposure Estimation and Interpretation of Occupational Risk: Enhanced Information for the Occupational Risk Manager

PubMed Central

Waters, Martha; McKernan, Lauralynn; Maier, Andrew; Jayjock, Michael; Schaeffer, Val; Brosseau, Lisa

2015-01-01

The fundamental goal of this article is to describe, define, and analyze the components of the risk characterization process for occupational exposures. Current methods are described for the probabilistic characterization of exposure, including newer techniques that have increasing applications for assessing data from occupational exposure scenarios. In addition, since the probability of health effects reflects variability in the exposure estimate as well as the dose-response curve—the integrated considerations of variability surrounding both components of the risk characterization provide greater information to the occupational hygienist. Probabilistic tools provide a more informed view of exposure as compared to use of discrete point estimates for these inputs to the risk characterization process. Active use of such tools for exposure and risk assessment will lead to a scientifically supported worker health protection program. Understanding the bases for an occupational risk assessment, focusing on important sources of variability and uncertainty enables characterizing occupational risk in terms of a probability, rather than a binary decision of acceptable risk or unacceptable risk. A critical review of existing methods highlights several conclusions: (1) exposure estimates and the dose-response are impacted by both variability and uncertainty and a well-developed risk characterization reflects and communicates this consideration; (2) occupational risk is probabilistic in nature and most accurately considered as a distribution, not a point estimate; and (3) occupational hygienists have a variety of tools available to incorporate concepts of risk characterization into occupational health and practice. PMID:26302336
An evaluation of risk estimation procedures for mixtures of carcinogens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hwang, J.S.; Chen, J.J.

1999-12-01

The estimation of health risks from exposure to a mixture of chemical carcinogens is generally based on the combination of information from several available single compound studies. The current practice of directly summing the upper bound risk estimates of individual carcinogenic components as an upper bound on the total risk of a mixture is known to be generally too conservative. Gaylor and Chen (1996, Risk Analysis) proposed a simple procedure to compute an upper bound on the total risk using only the upper confidence limits and central risk estimates of individual carcinogens. The Gaylor-Chen procedure was derived based on anmore » underlying assumption of the normality for the distributions of individual risk estimates. IN this paper the authors evaluated the Gaylor-Chen approach in terms the coverages of the upper confidence limits on the true risks of individual carcinogens. In general, if the coverage probabilities for the individual carcinogens are all approximately equal to the nominal level, then the Gaylor-Chen approach should perform well. However, the Gaylor-Chen approach can be conservative or anti-conservative if some of all individual upper confidence limit estimates are conservative or anti-conservative.« less
Global Burden of Leptospirosis: Estimated in Terms of Disability Adjusted Life Years

PubMed Central

Torgerson, Paul R.; Hagan, José E.; Costa, Federico; Calcagno, Juan; Kane, Michael; Martinez-Silveira, Martha S.; Goris, Marga G. A.; Stein, Claudia; Ko, Albert I.; Abela-Ridder, Bernadette

2015-01-01

Background Leptospirosis, a spirochaetal zoonosis, occurs in diverse epidemiological settings and affects vulnerable populations, such as rural subsistence farmers and urban slum dwellers. Although leptospirosis can cause life-threatening disease, there is no global burden of disease estimate in terms of Disability Adjusted Life Years (DALYs) available. Methodology/Principal Findings We utilised the results of a parallel publication that reported global estimates of morbidity and mortality due to leptospirosis. We estimated Years of Life Lost (YLLs) from age and gender stratified mortality rates. Years of Life with Disability (YLDs) were developed from a simple disease model indicating likely sequelae. DALYs were estimated from the sum of YLLs and YLDs. The study suggested that globally approximately 2·90 million DALYs are lost per annum (UIs 1·25–4·54 million) from the approximately annual 1·03 million cases reported previously. Males are predominantly affected with an estimated 2·33 million DALYs (UIs 0·98–3·69) or approximately 80% of the total burden. For comparison, this is over 70% of the global burden of cholera estimated by GBD 2010. Tropical regions of South and South-east Asia, Western Pacific, Central and South America, and Africa had the highest estimated leptospirosis disease burden. Conclusions/Significance Leptospirosis imparts a significant health burden worldwide, which approach or exceed those encountered for a number of other zoonotic and neglected tropical diseases. The study findings indicate that highest burden estimates occur in resource-poor tropical countries, which include regions of Africa where the burden of leptospirosis has been under-appreciated and possibly misallocated to other febrile illnesses such as malaria. PMID:26431366
Direct risk standardisation: a new method for comparing casemix adjusted event rates using complex models

PubMed Central

2013-01-01

Background Comparison of outcomes between populations or centres may be confounded by any casemix differences and standardisation is carried out to avoid this. However, when the casemix adjustment models are large and complex, direct standardisation has been described as “practically impossible”, and indirect standardisation may lead to unfair comparisons. We propose a new method of directly standardising for risk rather than standardising for casemix which overcomes these problems. Methods Using a casemix model which is the same model as would be used in indirect standardisation, the risk in individuals is estimated. Risk categories are defined, and event rates in each category for each centre to be compared are calculated. A weighted sum of the risk category specific event rates is then calculated. We have illustrated this method using data on 6 million admissions to 146 hospitals in England in 2007/8 and an existing model with over 5000 casemix combinations, and a second dataset of 18,668 adult emergency admissions to 9 centres in the UK and overseas and a published model with over 20,000 casemix combinations and a continuous covariate. Results Substantial differences between conventional directly casemix standardised rates and rates from direct risk standardisation (DRS) were found. Results based on DRS were very similar to Standardised Mortality Ratios (SMRs) obtained from indirect standardisation, with similar standard errors. Conclusions Direct risk standardisation using our proposed method is as straightforward as using conventional direct or indirect standardisation, always enables fair comparisons of performance to be made, can use continuous casemix covariates, and was found in our examples to have similar standard errors to the SMR. It should be preferred when there is a risk that conventional direct or indirect standardisation will lead to unfair comparisons. PMID:24168424
Direct risk standardisation: a new method for comparing casemix adjusted event rates using complex models.

PubMed

Nicholl, Jon; Jacques, Richard M; Campbell, Michael J

2013-10-29

Comparison of outcomes between populations or centres may be confounded by any casemix differences and standardisation is carried out to avoid this. However, when the casemix adjustment models are large and complex, direct standardisation has been described as "practically impossible", and indirect standardisation may lead to unfair comparisons. We propose a new method of directly standardising for risk rather than standardising for casemix which overcomes these problems. Using a casemix model which is the same model as would be used in indirect standardisation, the risk in individuals is estimated. Risk categories are defined, and event rates in each category for each centre to be compared are calculated. A weighted sum of the risk category specific event rates is then calculated. We have illustrated this method using data on 6 million admissions to 146 hospitals in England in 2007/8 and an existing model with over 5000 casemix combinations, and a second dataset of 18,668 adult emergency admissions to 9 centres in the UK and overseas and a published model with over 20,000 casemix combinations and a continuous covariate. Substantial differences between conventional directly casemix standardised rates and rates from direct risk standardisation (DRS) were found. Results based on DRS were very similar to Standardised Mortality Ratios (SMRs) obtained from indirect standardisation, with similar standard errors. Direct risk standardisation using our proposed method is as straightforward as using conventional direct or indirect standardisation, always enables fair comparisons of performance to be made, can use continuous casemix covariates, and was found in our examples to have similar standard errors to the SMR. It should be preferred when there is a risk that conventional direct or indirect standardisation will lead to unfair comparisons.

Procedure for estimating orbital debris risks

NASA Technical Reports Server (NTRS)

Crafts, J. L.; Lindberg, J. P.

1985-01-01

A procedure for estimating the potential orbital debris risk to the world's populace from payloads or spent stages left in orbit on future missions is presented. This approach provides a consistent, but simple, procedure to assess the risk due to random reentry with an adequate accuracy level for making programmatic decisions on planned low Earth orbit missions.
Assessment of Methods for Estimating Risk to Birds from ...

EPA Pesticide Factsheets

The U.S. EPA Ecological Risk Assessment Support Center (ERASC) announced the release of the final report entitled, Assessment of Methods for Estimating Risk to Birds from Ingestion of Contaminated Grit Particles. This report evaluates approaches for estimating the probability of ingestion by birds of contaminated particles such as pesticide granules or lead particles (i.e. shot or bullet fragments). In addition, it presents an approach for using this information to estimate the risk of mortality to birds from ingestion of lead particles. Response to ERASC Request #16
Quantile uncertainty and value-at-risk model risk.

PubMed

Alexander, Carol; Sarabia, José María

2012-08-01

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.
Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

PubMed Central

Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan

2014-01-01

Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880
Adjusting for car occupant injury liability in relation to age, speed limit, and gender-specific driver crash involvement risk.

PubMed

Keall, Michael; Frith, William

2004-12-01

It is well established that older drivers' fragility is an important factor associated with higher levels of fatal crash involvement for older drivers. There has been less research on age-related fragility with respect to the sort of minor injuries that are more common in injury crashes. This study estimates a quantity that is related to injury fragility: the probability that a driver or a passenger of that driver will be injured in crashes involving two cars. The effects of other factors apart from drivers' fragility are included in this measure, including the fragility of the passengers, the crashworthiness of cars driven, seatbelt use by the occupants, and characteristics of crashes (including configuration and impact speed). The car occupant injury liability estimates appropriately includes these factors to adjust risk curves by age, gender, and speed limit accounting for overrepresentation in crashes associated with fragility and these other factors.
Relations of Growth in Effortful Control to Family Income, Cumulative Risk, and Adjustment in Preschool-age Children

PubMed Central

Lengua, Liliana J.; Moran, Lyndsey; Zalewski, Maureen; Ruberry, Erika; Kiff, Cara; Thompson, Stephanie

2014-01-01

The study examined growth in effortful control (executive control, delay ability) in relation to income, cumulative risk (aggregate of demographic and psychosocial risk factors), and adjustment in 306 preschool-age children (50% girls, 50% boys) from families representing a range of income (29% at- or near-poverty; 28% lower-income; 25% middle-income; 18% upper-income), with 4 assessments starting at 36–40 mos. Income was directly related to levels of executive control and delay ability. Cumulative risk accounted for the effects of income on delay ability but not executive control. Higher initial executive control and slope of executive control and delay ability predicted academic readiness, whereas levels, but not growth, of executive control and delay ability predicted social competence and adjustment problems. Low income is a marker for lower effortful control, which demonstrates additive or mediating effects in the relation of income to children’s preschool adjustment. PMID:25253079
Identifying Military and Combat Specific Risk Factors for Child Adjustment: Comparing High and Low Risk Military Families and Civilian Families

DTIC Science & Technology

2016-06-01

Award Number: W81XWH-12-2-0034 TITLE: Identifying Military and Combat-Specific Risk Factors for Child Adjustment: Comparing High and Low Risk...2. REPORT TYPE Annual 3. DATES COVERED (From - To) 15 May - 2013 - 14 May 2014. Identifying Military and Combat-Specific Risk Factors for Child ...parents (N=200) whose spouse/partner is currently in a “low perceived risk” deployment and has a child between the age of 3 and 7 and comparison
Estimating the occupancy of spotted owl habitat areas by sampling and adjusting for bias

Treesearch

David L. Azuma; James A. Baldwin; Barry R. Noon

1990-01-01

A basic sampling scheme is proposed to estimate the proportion of sampled units (Spotted Owl Habitat Areas (SOHAs) or randomly sampled 1000-acre polygon areas (RSAs)) occupied by spotted owl pairs. A bias adjustment for the possibility of missing a pair given its presence on a SOHA or RSA is suggested. The sampling scheme is based on a fixed number of visits to a...
Age- and Tumor Subtype–Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers

PubMed Central

Hogervorst, Frans; van Hien, Richard; Cornelissen, Sten; Broeks, Annegien; Adank, Muriel A.; Meijers, Hanne; Waisfisz, Quinten; Hollestelle, Antoinette; Schutte, Mieke; van den Ouweland, Ans; Hooning, Maartje; Andrulis, Irene L.; Anton-Culver, Hoda; Antonenkova, Natalia N.; Antoniou, Antonis C.; Arndt, Volker; Bermisheva, Marina; Bogdanova, Natalia V.; Bolla, Manjeet K.; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Dunning, Alison M.; Fasching, Peter A.; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G.; Haeberle, Lothar; Hall, Per; Hillemanns, Peter; Hopper, John L.; Jakubowska, Anna; John, Esther M.; Jones, Michael; Khusnutdinova, Elza; Knight, Julia A.; Kosma, Veli-Matti; Kristensen, Vessela; Lee, Andrew; Lindblom, Annika; Lubinski, Jan; Mannermaa, Arto; Margolin, Sara; Meindl, Alfons; Milne, Roger L.; Muranen, Taru A.; Newcomb, Polly A.; Offit, Kenneth; Park-Simon, Tjoung-Won; Peto, Julian; Pharoah, Paul D.P.; Robson, Mark; Rudolph, Anja; Sawyer, Elinor J.; Schmutzler, Rita K.; Seynaeve, Caroline; Soens, Julie; Southey, Melissa C.; Spurdle, Amanda B.; Surowy, Harald; Swerdlow, Anthony; Tollenaar, Rob A.E.M.; Tomlinson, Ian; Trentham-Dietz, Amy; Vachon, Celine; Wang, Qin; Whittemore, Alice S.; Ziogas, Argyrios; van der Kolk, Lizet; Nevanlinna, Heli; Dörk, Thilo; Bojesen, Stig; Easton, Douglas F.

2016-01-01

Purpose CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. Patients and Methods CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. Results Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center–based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10−20). The OR was higher for estrogen receptor (ER)–positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10−21]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10−4). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. Conclusion These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into
Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers.

PubMed

Schmidt, Marjanka K; Hogervorst, Frans; van Hien, Richard; Cornelissen, Sten; Broeks, Annegien; Adank, Muriel A; Meijers, Hanne; Waisfisz, Quinten; Hollestelle, Antoinette; Schutte, Mieke; van den Ouweland, Ans; Hooning, Maartje; Andrulis, Irene L; Anton-Culver, Hoda; Antonenkova, Natalia N; Antoniou, Antonis C; Arndt, Volker; Bermisheva, Marina; Bogdanova, Natalia V; Bolla, Manjeet K; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Dunning, Alison M; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G; Haeberle, Lothar; Hall, Per; Hillemanns, Peter; Hopper, John L; Jakubowska, Anna; John, Esther M; Jones, Michael; Khusnutdinova, Elza; Knight, Julia A; Kosma, Veli-Matti; Kristensen, Vessela; Lee, Andrew; Lindblom, Annika; Lubinski, Jan; Mannermaa, Arto; Margolin, Sara; Meindl, Alfons; Milne, Roger L; Muranen, Taru A; Newcomb, Polly A; Offit, Kenneth; Park-Simon, Tjoung-Won; Peto, Julian; Pharoah, Paul D P; Robson, Mark; Rudolph, Anja; Sawyer, Elinor J; Schmutzler, Rita K; Seynaeve, Caroline; Soens, Julie; Southey, Melissa C; Spurdle, Amanda B; Surowy, Harald; Swerdlow, Anthony; Tollenaar, Rob A E M; Tomlinson, Ian; Trentham-Dietz, Amy; Vachon, Celine; Wang, Qin; Whittemore, Alice S; Ziogas, Argyrios; van der Kolk, Lizet; Nevanlinna, Heli; Dörk, Thilo; Bojesen, Stig; Easton, Douglas F

2016-08-10

CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up. © 2016
Effects of communicating DNA-based disease risk estimates on risk-reducing behaviours.

PubMed

Marteau, Theresa M; French, David P; Griffin, Simon J; Prevost, A T; Sutton, Stephen; Watkinson, Clare; Attwood, Sophie; Hollands, Gareth J

2010-10-06

There are high expectations regarding the potential for the communication of DNA-based disease risk estimates to motivate behaviour change. To assess the effects of communicating DNA-based disease risk estimates on risk-reducing behaviours and motivation to undertake such behaviours. We searched the following databases using keywords and medical subject headings: Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 4 2010), MEDLINE (1950 to April 2010), EMBASE (1980 to April 2010), PsycINFO (1985 to April 2010) using OVID SP, and CINAHL (EBSCO) (1982 to April 2010). We also searched reference lists, conducted forward citation searches of potentially eligible articles and contacted authors of relevant studies for suggestions. There were no language restrictions. Unpublished or in press articles were eligible for inclusion. Randomised or quasi-randomised controlled trials involving adults (aged 18 years and over) in which one group received actual (clinical studies) or imagined (analogue studies) personalised DNA-based disease risk estimates for diseases for which the risk could plausibly be reduced by behavioural change. Eligible studies had to include a primary outcome measure of risk-reducing behaviour or motivation (e.g. intention) to alter such behaviour. Two review authors searched for studies and independently extracted data. We assessed risk of bias according to the Cochrane Handbook for Systematic Reviews of Interventions. For continuous outcome measures, we report effect sizes as standardised mean differences (SMDs). For dichotomous outcome measures, we report effect sizes as odds ratios (ORs). We obtained pooled effect sizes with 95% confidence intervals (CIs) using the random effects model applied on the scale of standardised differences and log odds ratios. We examined 5384 abstracts and identified 21 studies as potentially eligible. Following a full text analysis, we included 14 papers reporting results of 7 clinical
41 CFR 102-80.50 - Are Federal agencies responsible for identifying/estimating risks and for appropriate risk...

Code of Federal Regulations, 2010 CFR

2010-07-01

... identify and estimate safety and environmental management risks and appropriate risk reduction strategies... responsible for identifying/estimating risks and for appropriate risk reduction strategies? 102-80.50 Section... Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for...
Household adjustment to flood risk: a survey of coastal residents in Texas and Florida, United States.

PubMed

Brody, Samuel D; Lee, Yoonjeong; Highfield, Wesley E

2017-07-01

Individual households have increasingly borne responsibility for reducing the adverse impacts of flooding on their property. Little observational research has been conducted, however, at the household level to examine the major factors contributing to the selection of a particular household adjustment. This study addresses the issue by evaluating statistically the factors influencing the adoption of various household flood hazard adjustments. The results indicate that respondents with higher-value homes or longer housing tenure are more likely to adopt structural and expensive techniques. In addition, the information source and the Community Rating System (CRS) score for the jurisdiction where the household is located have a significant bearing on household adjustment. In contrast, proximity to risk zones and risk perception yield somewhat mixed results or behave counter to assumptions in the literature. The study findings provide insights that will be of value to governments and decision-makers interested in encouraging homeowners to take protective action given increasing flood risk. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.
Risk adjustment models for short-term outcomes after surgical resection for oesophagogastric cancer.

PubMed

Fischer, C; Lingsma, H; Hardwick, R; Cromwell, D A; Steyerberg, E; Groene, O

2016-01-01

Outcomes for oesophagogastric cancer surgery are compared with the aim of benchmarking quality of care. Adjusting for patient characteristics is crucial to avoid biased comparisons between providers. The study objective was to develop a case-mix adjustment model for comparing 30- and 90-day mortality and anastomotic leakage rates after oesophagogastric cancer resections. The study reviewed existing models, considered expert opinion and examined audit data in order to select predictors that were consequently used to develop a case-mix adjustment model for the National Oesophago-Gastric Cancer Audit, covering England and Wales. Models were developed on patients undergoing surgical resection between April 2011 and March 2013 using logistic regression. Model calibration and discrimination was quantified using a bootstrap procedure. Most existing risk models for oesophagogastric resections were methodologically weak, outdated or based on detailed laboratory data that are not generally available. In 4882 patients with oesophagogastric cancer used for model development, 30- and 90-day mortality rates were 2·3 and 4·4 per cent respectively, and 6·2 per cent of patients developed an anastomotic leak. The internally validated models, based on predictors selected from the literature, showed moderate discrimination (area under the receiver operating characteristic (ROC) curve 0·646 for 30-day mortality, 0·664 for 90-day mortality and 0·587 for anastomotic leakage) and good calibration. Based on available data, three case-mix adjustment models for postoperative outcomes in patients undergoing curative surgery for oesophagogastric cancer were developed. These models should be used for risk adjustment when assessing hospital performance in the National Health Service, and tested in other large health systems. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.
[Estimation on the mortality and disease burden attributed to selected risk factors in Shandong province].

PubMed

Xu, Ai-qiang; Sun, Jian-dong; Lu, Zi-long; Ma, Ji-xiang; Fu, Zhen-tao; Guo, Xiao-lei

2008-10-01

To determine the major health related risk factors and provide evidence for policy-making, using health burden analysis on selected factors among general population from Shandong province. Based on data derived from the Third Death of Cause Sampling Survey in Shandong, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) were calculated according to the GBD methodology. Deaths and DALYs attributed to the selected risk factors were than estimated together with the PAF data from GBD 2001 study. The indirect method was employed to estimate the YLDs. 51.09% of the total deaths and 31.83% of the total DALYs from the Shandong population were resulted from the 19 selected risk factors. High blood pressure, smoking, low fruit and vegetable intake, alcohol consumption, indoor smoke from solid fuels, high cholesterol, urban air pollution, physical inactivity, overweight and obesity and unsafe injections in health care settings were identified as the top 10 risk factors for mortality which together caused 50.21% of the total deaths. Alcohol use, smoking, high blood pressure, low fruit and vegetable intake, indoor smoke from solid fuels, overweight and obesity, high cholesterol, physical inactivity, urban air pollution and iron-deficiency anemia were proved as the top 10 risk factors related to disease burden and were responsible for 29.04% of the total DALYs. Alcohol use, smoking and high blood pressure were determined as the major risk factors which influencing the health of residents in Shandong. The mortality and burden of disease could be reduced significantly if these major factors were effectively under control.
Estimated injury risk for specific injuries and body regions in frontal motor vehicle crashes.

PubMed

Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Schoell, Samantha L; Swett, Katrina R; Stitzel, Joel D

2015-01-01

Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data. Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15-105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate. Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4-4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4
Estimated urinary sodium excretion and risk of heart failure in men and women in the EPIC-Norfolk study.

PubMed

Pfister, Roman; Michels, Guido; Sharp, Stephen J; Luben, Robert; Wareham, Nick J; Khaw, Kay-Tee

2014-04-01

Interventional trials provide evidence for a beneficial effect of reduced dietary sodium intake on blood pressure. The association of sodium intake with heart failure which is a long-term complication of hypertension has not been examined. Hazard ratios [HRs, 95% confidence interval (CI)] of heart failure comparing quintiles of estimated 24 h urinary sodium excretion (USE) were calculated in apparently healthy men (9017) and women (10,840) aged 39–79 participating in the EPIC study in Norfolk. During a mean follow-up of 12.9 years, 1210 incident cases of heart failure occurred. Compared with the reference category (128 mmol/day≤USE≤148 mmol/day), the top quintile (USE≥191 mmol/day) was associated with a significantly increased hazard of heart failure (1.32, 1.07–1.62) in multivariable analysis adjusting for age, sex, body mass index, diabetes, cholesterol, social class, educational level, smoking, physical activity, and alcohol consumption, with a marked attenuation (1.21, 0.98–1.49) when further adjusting for blood pressure. The bottom quintile (USE≤127 mmol/day) was also associated with an increased hazard of heart failure (1.29, 1.04–1.60) in multivariable analysis without relevant attenuation by blood pressure adjustment (1.26, 1.02–1.56), but with substantial attenuation when adjusting for interim ischaemic heart disease and baseline C-reactive protein levels and exclusion of events during the first 2 years (1.18, 0.96–1.47). We demonstrate a U-shaped association between USE and heart failure risk in an apparently healthy middle-aged population. The risk associated with the high range of USE was attenuated after adjustment for blood pressure, whereas the risk associated with the low range of USE was attenuated after adjustment for pre-existing disease processes. © 2014 The Authors. European Journal of Heart Failure © 2014 European Society of Cardiology.
Methods of adjusting the stable estimates of fertility for the effects of mortality decline.

PubMed

Abou-Gamrah, H

1976-03-01

Summary The paper shows how stable population methods, based on the age structure and the rate of increase, may be used to estimate the demographic measures of a quasi-stable population. After a discussion of known methods for adjusting the stable estimates to allow for the effects of mortality decline two new methods are presented, the application of which requires less information. The first method does not need any supplementary information, and the second method requires an estimate of the difference between the last two five-year intercensal rates of increase, i.e. five times the annual change of the rate of increase during the last ten years. For these new methods we do not need to know the onset year of mortality decline as in the Coale-Demeny method, or a long series of rates of increase as in Zachariah's method.
Risk-adjusted payment and performance assessment for primary care.

PubMed

Ash, Arlene S; Ellis, Randall P

2012-08-01

Many wish to change incentives for primary care practices through bundled population-based payments and substantial performance feedback and bonus payments. Recognizing patient differences in costs and outcomes is crucial, but customized risk adjustment for such purposes is underdeveloped. Using MarketScan's claims-based data on 17.4 million commercially insured lives, we modeled bundled payment to support expected primary care activity levels (PCAL) and 9 patient outcomes for performance assessment. We evaluated models using 457,000 people assigned to 436 primary care physician panels, and among 13,000 people in a distinct multipayer medical home implementation with commercially insured, Medicare, and Medicaid patients. Each outcome is separately predicted from age, sex, and diagnoses. We define the PCAL outcome as a subset of all costs that proxies the bundled payment needed for comprehensive primary care. Other expected outcomes are used to establish targets against which actual performance can be fairly judged. We evaluate model performance using R(2)'s at patient and practice levels, and within policy-relevant subgroups. The PCAL model explains 67% of variation in its outcome, performing well across diverse patient ages, payers, plan types, and provider specialties; it explains 72% of practice-level variation. In 9 performance measures, the outcome-specific models explain 17%-86% of variation at the practice level, often substantially outperforming a generic score like the one used for full capitation payments in Medicare: for example, with grouped R(2)'s of 47% versus 5% for predicting "prescriptions for antibiotics of concern." Existing data can support the risk-adjusted bundled payment calculations and performance assessments needed to encourage desired transformations in primary care.
Adjusting for reverse causation to estimate the effect of obesity on mortality after incident heart failure in the Atherosclerosis Risk in Communities (ARIC) study.

PubMed

Shakiba, Maryam; Soori, Hamid; Mansournia, Mohammad Ali; Nazari, Seyed Saeed Hashemi; Salimi, Yahya

2016-01-01

The lower mortality rate of obese patients with heart failure (HF) has been partly attributed to reverse causation bias due to weight loss caused by disease. Using data about weight both before and after HF, this study aimed to adjust for reverse causation and examine the association of obesity both before and after HF with mortality. Using the Atherosclerosis Risk in Communities (ARIC) study, 308 patients with data available from before and after the incidence of HF were included. Pre-morbid and post-morbid obesity were defined based on body mass index measurements at least three months before and after incident HF. The associations of pre-morbid and post-morbid obesity and weight change with survival after HF were evaluated using a Cox proportional hazard model. Pre-morbid obesity was associated with higher mortality (hazard ratio [HR], 1.61; 95% confidence interval [CI], 1.04 to 2.49) but post-morbid obesity was associated with increased survival (HR, 0.57; 95% CI, 0.37 to 0.88). Adjusting for weight change due to disease as a confounder of the obesity-mortality relationship resulted in the absence of any significant associations between post-morbid obesity and mortality. This study demonstrated that controlling for reverse causality by adjusting for the confounder of weight change may remove or reverse the protective effect of obesity on mortality among patients with incident HF.

Toward the Development of Integrative Risk-Adjusted Measures of Quality Using Large Clinical Data Bases: The Case of Anesthesia Services.

ERIC Educational Resources Information Center

Fleming, Steven T.

1992-01-01

The concept of risk-adjusted measures of quality is discussed, and a methodology is proposed for risk-adjusting and integrating multiple adverse outcomes of anesthesia services into measures for quality assurance and quality improvement programs. Although designed for a new anesthesiology database, the methods should apply to other health…
What is the lifetime risk of developing cancer?: the effect of adjusting for multiple primaries

PubMed Central

Sasieni, P D; Shelton, J; Ormiston-Smith, N; Thomson, C S; Silcocks, P B

2011-01-01

Background: The ‘lifetime risk' of cancer is generally estimated by combining current incidence rates with current all-cause mortality (‘current probability' method) rather than by describing the experience of a birth cohort. As individuals may get more than one type of cancer, what is generally estimated is the average (mean) number of cancers over a lifetime. This is not the same as the probability of getting cancer. Methods: We describe a method for estimating lifetime risk that corrects for the inclusion of multiple primary cancers in the incidence rates routinely published by cancer registries. The new method applies cancer incidence rates to the estimated probability of being alive without a previous cancer. The new method is illustrated using data from the Scottish Cancer Registry and is compared with ‘gold-standard' estimates that use (unpublished) data on first primaries. Results: The effect of this correction is to make the estimated ‘lifetime risk' smaller. The new estimates are extremely similar to those obtained using incidence based on first primaries. The usual ‘current probability' method considerably overestimates the lifetime risk of all cancers combined, although the correction for any single cancer site is minimal. Conclusion: Estimation of the lifetime risk of cancer should either be based on first primaries or should use the new method. PMID:21772332
CubeSat mission design software tool for risk estimating relationships

NASA Astrophysics Data System (ADS)

Gamble, Katharine Brumbaugh; Lightsey, E. Glenn

2014-09-01

In an effort to make the CubeSat risk estimation and management process more scientific, a software tool has been created that enables mission designers to estimate mission risks. CubeSat mission designers are able to input mission characteristics, such as form factor, mass, development cycle, and launch information, in order to determine the mission risk root causes which historically present the highest risk for their mission. Historical data was collected from the CubeSat community and analyzed to provide a statistical background to characterize these Risk Estimating Relationships (RERs). This paper develops and validates the mathematical model based on the same cost estimating relationship methodology used by the Unmanned Spacecraft Cost Model (USCM) and the Small Satellite Cost Model (SSCM). The RER development uses general error regression models to determine the best fit relationship between root cause consequence and likelihood values and the input factors of interest. These root causes are combined into seven overall CubeSat mission risks which are then graphed on the industry-standard 5×5 Likelihood-Consequence (L-C) chart to help mission designers quickly identify areas of concern within their mission. This paper is the first to document not only the creation of a historical database of CubeSat mission risks, but, more importantly, the scientific representation of Risk Estimating Relationships.
Influence of Competing Risks on Estimating the Expected Benefit of Warfarin Among Atrial Fibrillation Patients not Currently Taking Anticoagulants: the ATRIA Study

PubMed Central

Ashburner, Jeffrey M.; Go, Alan S.; Chang, Yuchiao; Fang, Margaret C.; Fredman, Lisa; Applebaum, Katie M.; Singer, Daniel E.

2016-01-01

Background/Objectives To date, studies examining the association between warfarin therapy and incidence of ischemic stroke among patients with atrial fibrillation (AF) have not accounted for the competing risk of death. Competing risk analysis may provide greater understanding of the “real world” impact of anticoagulation on stroke risk over a multiyear time span. Design Cohort study Setting ATRIA Study community-based cohort Participants 13,559 adults with nonvalvular AF between 1996 and 2003. Measurements All events were clinician-adjudicated. We used extended Cox regression with longitudinal warfarin exposure to estimate cause-specific hazard ratios (HR) for thromboembolism (TE) and the competing risk event (all cause death). The Fine and Gray subdistribution regression approach was used to estimate this association while accounting for competing death events. As a secondary analysis, follow-up was limited to 1, 3, and 5-years. Results The rate of death was much higher in the non-warfarin group (8.1 deaths/100 person-years) compared to the warfarin group (5.5 deaths/100 person-years). The cause-specific HR indicated a large reduction in TE with warfarin use (adjusted HR: 0.57, 95% CI: 0.50–0.65). However, after accounting for competing death events, this association was substantially attenuated (adjusted HR: 0.87, 95% CI: 0.77–0.99). In analyses limited to 1-year of follow-up with fewer competing death events, the results for models that did and did not account for competing risks were similar. Conclusion Analyses accounting for competing death events may provide a more realistic estimate of the longer-term stroke prevention benefits of anticoagulants for patients with AF, particularly those who are not currently treated with anticoagulants. PMID:27861698
Overcoming bias in estimating the volume-outcome relationship.

PubMed

Tsai, Alexander C; Votruba, Mark; Bridges, John F P; Cebul, Randall D

2006-02-01

To examine the effect of hospital volume on 30-day mortality for patients with congestive heart failure (CHF) using administrative and clinical data in conventional regression and instrumental variables (IV) estimation models. The primary data consisted of longitudinal information on comorbid conditions, vital signs, clinical status, and laboratory test results for 21,555 Medicare-insured patients aged 65 years and older hospitalized for CHF in northeast Ohio in 1991-1997. The patient was the primary unit of analysis. We fit a linear probability model to the data to assess the effects of hospital volume on patient mortality within 30 days of admission. Both administrative and clinical data elements were included for risk adjustment. Linear distances between patients and hospitals were used to construct the instrument, which was then used to assess the endogeneity of hospital volume. When only administrative data elements were included in the risk adjustment model, the estimated volume-outcome effect was statistically significant (p=.029) but small in magnitude. The estimate was markedly attenuated in magnitude and statistical significance when clinical data were added to the model as risk adjusters (p=.39). IV estimation shifted the estimate in a direction consistent with selective referral, but we were unable to reject the consistency of the linear probability estimates. Use of only administrative data for volume-outcomes research may generate spurious findings. The IV analysis further suggests that conventional estimates of the volume-outcome relationship may be contaminated by selective referral effects. Taken together, our results suggest that efforts to concentrate hospital-based CHF care in high-volume hospitals may not reduce mortality among elderly patients.
[Remuneration distribution - should morbidity-dependent overall remuneration also be distributed after adjustments for morbidity?].

PubMed

Walendzik, A; Trottmann, M; Leonhardt, R; Wasem, J

2013-04-01

In the 2009 reform of the German collective remuneration system for outpatient medical care, on the level of overall remuneration, the morbidity risk was transferred to the health funds fulfilling a long-term demand of physicians. Nevertheless not transferring morbidity adjustment to the levels of physician groups and singular practices can lead to budgets not related to patient needs and to incentives for risk selection for individual doctors. The systematics of the distribution of overall remuneration in the German remuneration system for outpatient care are analysed focusing on the aspect of morbidity adjustment. Using diagnostic and pharmaceutical information of about half a million insured subjects, a risk adjustment model able to predict individual expenditures for outpatient care for different provider groups is presented. This model enables to additively split the individual care burden into several parts attributed to different physician groups. Conditions for the use of the model in the distribution of overall remuneration between physician groups are developed. A simulation of the use of diagnoses-based risk adjustment in standard service volumes then highlights the conditions for a successfull installation of standard service volumes representing a higher degree of risk adjustment. The presented estimation model is generally applicable for the distribution of overall remuneration to different physician groups. The simulation of standard service volumes using diagnosis-based risk adjustment does not provide a more accurate prediction of the expenditures on the level of physician practices than the age-related calculation currently used in the German remuneration system for outpatient medical care. Using elements of morbidity-based risk adjustment the current German collective system for outpatient medical care could be transformed towards a higher degree of distributional justice concerning medical care for patients and more appropriate incentives
Application of the Rosner-Wei Risk-Prediction Model to Estimate Sexual Orientation Patterns in Colon Cancer Risk in a Prospective Cohort of U.S. Women

PubMed Central

Austin, S. Bryn; Pazaris, Mathew J.; Wei, Esther K.; Rosner, Bernard; Kennedy, Grace A.; Bowen, Deborah; Spiegelman, Donna

2014-01-01

Purpose We examined whether lesbian and bisexual women may be at greater risk of colon cancer (CC) than heterosexual women. Methods Working with a large cohort of U.S. women ages 25-64 years, we analyzed 20 years of prospective data to estimate CC incidence, based on known risk factors by applying the Rosner-Wei CC risk-prediction model. Comparing to heterosexual women, we calculated for lesbian and bisexual women the predicted one-year incidence rate (IR) per 100,000 person-years and estimated incidence rate ratios (IRR) and 95% confidence intervals (CI), based on each woman’s comprehensive risk factor profile. Results Analyses included 1,373,817 person-years of data from 66,257 women. For each sexual orientation group, mean predicted one-year CC IR per 100,000 person-years was slightly over 12 cases for each of the sexual orientation groups. After controlling for confounders in fully adjusted models and compared to heterosexuals, no significant differences in IRR were observed for lesbians (IRR 1.01; 95% CI 0.99, 1.04) or bisexuals (IRR 1.01; 95% CI 0.98, 1.04). Conclusions CC risk is similar across all sexual orientation subgroups, with all groups comparably affected. Health professionals must ensure that prevention, screening, and treatment programs are adequately reaching each of these communities. PMID:24852207
Obesity phenotype and coronary heart disease risk as estimated by the Framingham risk score.

PubMed

Park, Yong Soon; Kim, Jun-Su

2012-03-01

There are conflicting data as to whether general or abdominal obesity is a better predictor of cardiovascular risk. This cross-sectional study involved 4,573 subjects aged 30 to 74 yr who participated in the Fourth Korea National Health and Nutrition Examination Survey conducted in 2008. Obesity phenotype was classified by means of body mass index (BMI) and waist circumference (WC), and participants were categorized into 4 groups. Individuals' 10-yr risk of coronary heart diseases (CHD) was determined from the Framingham risk score. Subjects with obese WC had a higher proportion of high risk for CHD compared to the normal WC group, irrespective of BMI level. Relative to subjects with normal BMI/normal WC, the adjusted odds ratios (ORs) of normal BMI/obese WC group (OR 2.93 [1.70, 5.04] and OR 3.10 [1.49, 6.46]) for CHD risk in male were higher than obese BMI/obese WC group (OR 1.91 [1.40, 2.61] and OR 1.70 [1.16, 2.47]), whereas the adjusted ORs of obese BMI/obese WC group (OR 1.94 [1.24, 3.04] and OR 3.92 [1.75, 8.78]) were higher than the others in female. Subjects with obese BMI/normal WC were not significantly associated with 10-yr CHD risk in men (P = 0.449 and P = 0.067) and women (P = 0.702 and P = 0.658). WC is associated with increased CHD risk regardless of the level of BMI. Men with normal BMI and obese WC tend to be associated with CHD risk than those with obese BMI and obese WC.
Beyond classic risk adjustment: Socioeconomic status and hospital performance in urologic oncology surgery.

PubMed

Odisho, Anobel Y; Etzioni, Ruth; Gore, John L

2018-06-15

Safety-net hospitals (SNHs) care for more patients of low socioeconomic status (SES) than non-SNHs and are disproportionately punished under SES-naive Medicare readmission risk-adjustment models. This study was designed to develop a risk-adjustment framework that incorporates SES and to assess the impact on readmission rates. California Office of Statewide Health Planning and Development data from 2007 to 2011 were used to identify patients undergoing radical cystectomy (RC) for bladder cancer (n = 3771) or partial nephrectomy (PN; n = 5556) or radical nephrectomy (RN; n = 13,136) for kidney cancer. Unadjusted hospital rankings and predicted rankings under models simulating the Medicare Hospital Readmissions Reduction Program were compared with predicted rankings under models incorporating SES and hospital factors. SES, derived from a multifactorial neighborhood score, was calculated from US Census data. The 30-day readmission rate was 26.1% for RC, 8.3% for RN, and 9.5% for PN. The addition of SES, geographic, and hospital factors changed hospital rankings significantly in comparison with the base model (P < .01) except for SES for RC (P = .07) and SES and rural factors for PN (P = .12). For RN and PN, the addition of SES predicted lower percentile ranks for SNHs and thus improved observed-to-expected rankings (P < .01). For RC, there were no changes in hospital rankings. SES is important for risk adjustments for complex surgical procedures such as RC. Patient SES affects overall hospital rankings across cohorts, and critically, it differentially and punitively affects rankings for SNHs for some procedures. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.
[Family characteristics, organic risk factors, psychopathological picture and premorbid adjustment of hospitalized adolescent patients].

PubMed

Małkiewicz-Borkowska, M; Namysłowska, I; Siewierska, A; Puzyńska, E; Sredniawa, H; Zechowski, C; Iwanek, A; Ruszkowska, E

1996-01-01

The relation of some family characteristics such as cohesion and adaptability with organic risk factors, developmental psychopathology, clinical picture and premorbid adjustment was assessed in the group of 100 hospitalized adolescent patients and families. We found correlation between: some of organic risk factors (pathology of neonatal period, pathology of early childhood), some of indicators of developmental psychopathology (eating disorders, conduct disorders), some of clinical signs (mannerism, grandiosity, hostility, suspciousness, disturbances of content of thinking), premorbid adjustment, and variables related to families, described before. We think that biological variables characterizing child (pathology of neonatal period, pathology of early childhood) have an influence on some family characteristics as independent variable. General system theory and circular thinking support these conclusions. In order to verify them, it is necessary to undertake further investigations, based on other methodology, using this results as preliminary findings.
Quality-of-life-adjusted hazard of death: a formulation of the quality-adjusted life-years model of use in benefit-risk assessment.

PubMed

Garcia-Hernandez, Alberto

2014-03-01

Although the quality-adjusted life-years (QALY) model is standard in health technology assessment, quantitative methods are less frequent but increasingly used for benefit-risk assessment (BRA) at earlier stages of drug development. A frequent challenge when implementing metrics for BRA is to weigh the importance of effects on a chronic condition against the risk of severe events during the trial. The lifetime component of the QALY model has a counterpart in the BRA context, namely, the risk of dying during the study. A new concept is presented, the hazard of death function that a subject is willing to accept instead of the baseline hazard to improve his or her chronic health status, which we have called the quality-of-life-adjusted hazard of death. It has been proven that if assumptions of the linear QALY model hold, the excess mortality rate tolerated by a subject for a chronic health improvement is inversely proportional to the mean residual life. This result leads to a new representation of the linear QALY model in terms of hazard rate functions and allows utilities obtained by using standard methods involving trade-offs of life duration to be translated into thresholds of tolerated mortality risk during a short period of time, thereby avoiding direct trade-offs using small probabilities of events during the study, which is known to lead to bias and variability. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Glomerular filtration rate estimated using creatinine, cystatin C or both markers and the risk of clinical events in HIV-infected individuals.

PubMed

Lucas, G M; Cozzi-Lepri, A; Wyatt, C M; Post, F A; Bormann, A M; Crum-Cianflone, N F; Ross, M J

2014-02-01

The accuracy and precision of glomerular filtration rate (GFR) estimating equations based on plasma creatinine (GFR(cr)), cystatin C (GFR(cys)) and the combination of these markers (GFR(cr-cys)) have recently been assessed in HIV-infected individuals. We assessed the associations of GFR, estimated by these three equations, with clinical events in HIV-infected individuals. We compared the associations of baseline GFR(cr), GFR(cys) and GFR(cr-cys) [using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations] with mortality, cardiovascular events (CVEs) and opportunistic diseases (ODs) in the Strategies for the Management of Antiretroviral Therapy (SMART) study. We used Cox proportional hazards models to estimate unadjusted and adjusted hazard ratios per standard deviation (SD) change in GFR. A total of 4614 subjects from the SMART trial with available baseline creatinine and cystatin C data were included in this analysis. Of these, 99 died, 111 had a CVE and 121 had an OD. GFR(cys) was weakly to moderately correlated with HIV RNA, CD4 cell count, high-sensitivity C-reactive protein, interleukin-6, and D-dimer, while GFR(cr) had little or no correlation with these factors. GFR(cys) had the strongest associations with the three clinical outcomes, followed closely by GFR(cr-cys), with GFR(cr) having the weakest associations with clinical outcomes. In a model adjusting for demographics, cardiovascular risk factors, HIV-related factors and inflammation markers, a 1-SD lower GFR(cys) was associated with a 55% [95% confidence interval (CI) 27-90%] increased risk of mortality, a 21% (95% CI 0-47%) increased risk of CVE, and a 22% (95% CI 0-48%) increased risk of OD. Of the three CKD-EPI GFR equations, GFR(cys) had the strongest associations with mortality, CVE and OD. © 2013 British HIV Association.
Aerial surveys adjusted by ground surveys to estimate area occupied by black-tailed prairie dog colonies

USGS Publications Warehouse

Sidle, John G.; Augustine, David J.; Johnson, Douglas H.; Miller, Sterling D.; Cully, Jack F.; Reading, Richard P.

2012-01-01

Aerial surveys using line-intercept methods are one approach to estimate the extent of prairie dog colonies in a large geographic area. Although black-tailed prairie dogs (Cynomys ludovicianus) construct conspicuous mounds at burrow openings, aerial observers have difficulty discriminating between areas with burrows occupied by prairie dogs (colonies) versus areas of uninhabited burrows (uninhabited colony sites). Consequently, aerial line-intercept surveys may overestimate prairie dog colony extent unless adjusted by an on-the-ground inspection of a sample of intercepts. We compared aerial line-intercept surveys conducted over 2 National Grasslands in Colorado, USA, with independent ground-mapping of known black-tailed prairie dog colonies. Aerial line-intercepts adjusted by ground surveys using a single activity category adjustment overestimated colonies by ≥94% on the Comanche National Grassland and ≥58% on the Pawnee National Grassland. We present a ground-survey technique that involves 1) visiting on the ground a subset of aerial intercepts classified as occupied colonies plus a subset of intercepts classified as uninhabited colony sites, and 2) based on these ground observations, recording the proportion of each aerial intercept that intersects a colony and the proportion that intersects an uninhabited colony site. Where line-intercept techniques are applied to aerial surveys or remotely sensed imagery, this method can provide more accurate estimates of black-tailed prairie dog abundance and trends
The relative value of metabolic syndrome and cardiovascular risk score estimates in premature acute coronary syndromes.

PubMed

Kalantzi, Kallirroi; Korantzopoulos, Panagiotis; Tzimas, Petros; Katsouras, Christos S; Goudevenos, John A; Milionis, Haralampos J

2008-03-01

To compare the relative value of metabolic syndrome (MetS) and cardiovascular risk score estimates in patients with acute coronary syndromes (ACS) aged <45 years. Two hundred consecutive patients (183 men, mean age 40.8 +/- 3.5 years) presented with a first-ever ACS, and 200 age-and sex-matched controls were evaluated. Metabolic syndrome diagnostic criteria, European Risk SCORE estimation function, and the Framingham Risk Score (FRS) were assessed in all participants. The prevalence of the MetS was significantly higher in the patients' group compared with the control group (51.5% vs 26.0%, P < .001). No subjects with a SCORE >1.0% were identified. The mean 10-year FRS for patients and controls was 13.03% +/- 7.96% and 10.02 +/- 8.10%, respectively (P < .001), whereas only 22.5% of ACS patients had a 10-year risk >20.0% compared with 14.5% of controls (P = .04). After controlling for potential confounders, MetS was associated with 1.93 (95% CI 1.13-3.28, P = .01) higher odds of having an ACS. Moreover, the odds had a positive association with the increasing cumulative number of MetS components. Crude and adjusted ORs for the FRS were 1.05 (95% CI 1.029-1.08, P = .001) and 0.98 (95% CI 0.92-1.05, P = NS), respectively. Metabolic syndrome is highly associated with ACS in subjects <45 years of age and seems to be more valuable than established cardiovascular risk calculators.
Outcomes for youth residential treatment programs using administrative data from the child welfare system: a risk-adjustment application.

PubMed

McMillen, J Curtis; Lee, Bethany R; Jonson-Reid, Melissa

2008-05-01

This study assessed whether administrative data from the public child welfare system could be used to develop risk-adjusted performance reports for residential mental health programs for adolescents. Regression methods were used with 3,759 residential treatment spells for 2,784 children and youth to determine which outcomes could be adequately risk adjusted for case mix. Expected outcomes were created for each residential program given its case mix; then, expected and achieved outcomes were compared. For most programs, achieved results did not differ significantly from expected results for individual outcomes. Overall, outcomes achieved were not impressive. Only one quarter of spells resulted in a youth being maintained in a single less restrictive setting in the year following discharge. Methodological implications of this study suggest further refinements are needed for child welfare administrative data in order to develop risk-adjusted report cards of program performance.
Evaluating diagnosis-based risk-adjustment methods in a population with spinal cord dysfunction.

PubMed

Warner, Grace; Hoenig, Helen; Montez, Maria; Wang, Fei; Rosen, Amy

2004-02-01

To examine performance of models in predicting health care utilization for individuals with spinal cord dysfunction. Regression models compared 2 diagnosis-based risk-adjustment methods, the adjusted clinical groups (ACGs) and diagnostic cost groups (DCGs). To improve prediction, we added to our model: (1) spinal cord dysfunction-specific diagnostic information, (2) limitations in self-care function, and (3) both 1 and 2. Models were replicated in 3 populations. Samples from 3 populations: (1) 40% of veterans using Veterans Health Administration services in fiscal year 1997 (FY97) (N=1,046,803), (2) veteran sample with spinal cord dysfunction identified by codes from the International Statistical Classification of Diseases, 9th Revision, Clinical Modifications (N=7666), and (3) veteran sample identified in Veterans Affairs Spinal Cord Dysfunction Registry (N=5888). Not applicable. Inpatient, outpatient, and total days of care in FY97. The DCG models (R(2) range,.22-.38) performed better than ACG models (R(2) range,.04-.34) for all outcomes. Spinal cord dysfunction-specific diagnostic information improved prediction more in the ACG model than in the DCG model (R(2) range for ACG,.14-.34; R(2) range for DCG,.24-.38). Information on self-care function slightly improved performance (R(2) range increased from 0 to.04). The DCG risk-adjustment models predicted health care utilization better than ACG models. ACG model prediction was improved by adding information.
On cancer risk estimation of urban air pollution.

PubMed Central

Törnqvist, M; Ehrenberg, L

1994-01-01

The usefulness of data from various sources for a cancer risk estimation of urban air pollution is discussed. Considering the irreversibility of initiations, a multiplicative model is preferred for solid tumors. As has been concluded for exposure to ionizing radiation, the multiplicative model, in comparison with the additive model, predicts a relatively larger number of cases at high ages, with enhanced underestimation of risks by short follow-up times in disease-epidemiological studies. For related reasons, the extrapolation of risk from animal tests on the basis of daily absorbed dose per kilogram body weight or per square meter surface area without considering differences in life span may lead to an underestimation, and agreements with epidemiologically determined values may be fortuitous. Considering these possibilities, the most likely lifetime risks of cancer death at the average exposure levels in Sweden were estimated for certain pollution fractions or indicator compounds in urban air. The risks amount to approximately 50 deaths per 100,000 for inhaled particulate organic material (POM), with a contribution from ingested POM about three times larger, and alkenes, and butadiene cause 20 deaths, respectively, per 100,000 individuals. Also, benzene and formaldehyde are expected to be associated with considerable risk increments. Comparative potency methods were applied for POM and alkenes. Due to incompleteness of the list of compounds considered and the uncertainties of the above estimates, the total risk calculation from urban air has not been attempted here. PMID:7821292
Estimated effect of ventilation and filtration on chronic health risks in U.S. offices, schools, and retail stores.

PubMed

Chan, W R; Parthasarathy, S; Fisk, W J; McKone, T E

2016-04-01

We assessed the chronic health risks from inhalation exposure to volatile organic compounds (VOCs) and particulate matter (PM2.5) in U.S. offices, schools, grocery, and other retail stores and evaluated how chronic health risks were affected by changes in ventilation rates and air filtration efficiency. Representative concentrations of VOCs and PM2.5 were obtained from available data. Using a mass balance model, changes in exposure to VOCs and PM2.5 were predicted if ventilation rate were to increase or decrease by a factor of two, and if higher efficiency air filters were used. Indoor concentrations were compared to health guidelines to estimate percentage exceedances. The estimated chronic health risks associated with VOC and PM2.5 exposures in these buildings were low relative to the risks from exposures in homes. Chronic health risks were driven primarily by exposures to PM2.5 that were evaluated using disease incidence of mortality, chronic bronchitis, and non-fatal stroke. The leading cancer risk factor was exposure to formaldehyde. Using disability-adjusted life years (DALYs) to account for both cancer and non-cancer effects, results suggest that increasing ventilation alone is ineffective at reducing chronic health burdens. Other strategies, such as pollutant source control and the use of particle filtration, should also be considered. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Do Adjusting-Amount and Adjusting-Delay Procedures Produce Equivalent Estimates of Subjective Value in Pigeons?

ERIC Educational Resources Information Center

Green, Leonard; Myerson, Joel; Shah, Anuj K.; Estle, Sara J.; Holt, Daniel D.

2007-01-01

The current experiment examined whether adjusting-amount and adjusting-delay procedures provide equivalent measures of discounting. Pigeons' discounting on the two procedures was compared using a within-subject yoking technique in which the indifference point (number of pellets or time until reinforcement) obtained with one procedure determined…
Case complexity scores in congenital heart surgery: a comparative study of the Aristotle Basic Complexity score and the Risk Adjustment in Congenital Heart Surgery (RACHS-1) system.

PubMed

Al-Radi, Osman O; Harrell, Frank E; Caldarone, Christopher A; McCrindle, Brian W; Jacobs, Jeffrey P; Williams, M Gail; Van Arsdell, Glen S; Williams, William G

2007-04-01

The Aristotle Basic Complexity score and the Risk Adjustment in Congenital Heart Surgery system were developed by consensus to compare outcomes of congenital cardiac surgery. We compared the predictive value of the 2 systems. Of all index congenital cardiac operations at our institution from 1982 to 2004 (n = 13,675), we were able to assign an Aristotle Basic Complexity score, a Risk Adjustment in Congenital Heart Surgery score, and both scores to 13,138 (96%), 11,533 (84%), and 11,438 (84%) operations, respectively. Models of in-hospital mortality and length of stay were generated for Aristotle Basic Complexity and Risk Adjustment in Congenital Heart Surgery using an identical data set in which both Aristotle Basic Complexity and Risk Adjustment in Congenital Heart Surgery scores were assigned. The likelihood ratio test for nested models and paired concordance statistics were used. After adjustment for year of operation, the odds ratios for Aristotle Basic Complexity score 3 versus 6, 9 versus 6, 12 versus 6, and 15 versus 6 were 0.29, 2.22, 7.62, and 26.54 (P < .0001). Similarly, odds ratios for Risk Adjustment in Congenital Heart Surgery categories 1 versus 2, 3 versus 2, 4 versus 2, and 5/6 versus 2 were 0.23, 1.98, 5.80, and 20.71 (P < .0001). Risk Adjustment in Congenital Heart Surgery added significant predictive value over Aristotle Basic Complexity (likelihood ratio chi2 = 162, P < .0001), whereas Aristotle Basic Complexity contributed much less predictive value over Risk Adjustment in Congenital Heart Surgery (likelihood ratio chi2 = 13.4, P = .009). Neither system fully adjusted for the child's age. The Risk Adjustment in Congenital Heart Surgery scores were more concordant with length of stay compared with Aristotle Basic Complexity scores (P < .0001). The predictive value of Risk Adjustment in Congenital Heart Surgery is higher than that of Aristotle Basic Complexity. The use of Aristotle Basic Complexity or Risk Adjustment in Congenital Heart Surgery

Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1 censored data

USGS Publications Warehouse

Cohn, Timothy A.

2005-01-01

This paper presents an adjusted maximum likelihood estimator (AMLE) that can be used to estimate fluvial transport of contaminants, like phosphorus, that are subject to censoring because of analytical detection limits. The AMLE is a generalization of the widely accepted minimum variance unbiased estimator (MVUE), and Monte Carlo experiments confirm that it shares essentially all of the MVUE's desirable properties, including high efficiency and negligible bias. In particular, the AMLE exhibits substantially less bias than alternative censored‐data estimators such as the MLE (Tobit) or the MLE followed by a jackknife. As with the MLE and the MVUE the AMLE comes close to achieving the theoretical Frechet‐Cramér‐Rao bounds on its variance. This paper also presents a statistical framework, applicable to both censored and complete data, for understanding and estimating the components of uncertainty associated with load estimates. This can serve to lower the cost and improve the efficiency of both traditional and real‐time water quality monitoring.
Estimating the lifetime risk of cancer associated with multiple CT scans.

PubMed

Ivanov, V K; Kashcheev, V V; Chekin, S Yu; Menyaylo, A N; Pryakhin, E A; Tsyb, A F; Mettler, F A

2014-12-01

Multiple CT scans are often done on the same patient resulting in an increased risk of cancer. Prior publications have estimated risks on a population basis and often using an effective dose. Simply adding up the risks from single scans does not correctly account for the survival function. A methodology for estimating personal radiation risks attributed to multiple CT imaging using organ doses is presented in this article. The estimated magnitude of the attributable risk fraction for the possible development of radiation-induced cancer indicates the necessity for strong clinical justification when ordering multiple CT scans.
Risk adjustment model of credit life insurance using a genetic algorithm

NASA Astrophysics Data System (ADS)

Saputra, A.; Sukono; Rusyaman, E.

2018-03-01

In managing the risk of credit life insurance, insurance company should acknowledge the character of the risks to predict future losses. Risk characteristics can be learned in a claim distribution model. There are two standard approaches in designing the distribution model of claims over the insurance period i.e, collective risk model and individual risk model. In the collective risk model, the claim arises when risk occurs is called individual claim, accumulation of individual claim during a period of insurance is called an aggregate claim. The aggregate claim model may be formed by large model and a number of individual claims. How the measurement of insurance risk with the premium model approach and whether this approach is appropriate for estimating the potential losses occur in the future. In order to solve the problem Genetic Algorithm with Roulette Wheel Selection is used.
Psychosocial Adjustment and Sibling Relationships in Siblings of Children with Autism Spectrum Disorder: Risk and Protective Factors

ERIC Educational Resources Information Center

Walton, Katherine M.; Ingersoll, Brooke R.

2015-01-01

This study compared sibling adjustment and relationships in siblings of children with Autism Spectrum Disorder (ASD-Sibs; n = 69) and siblings of children with typical development (TD-Sibs; n = 93). ASD-Sibs and TD-Sibs demonstrated similar emotional/behavioral adjustment. Older male ASD-Sibs were at increased risk for difficulties. Sibling…
Russia-specific relative risks and their effects on the estimated alcohol-attributable burden of disease.

PubMed

Shield, Kevin D; Rehm, Jürgen

2015-05-10

Alcohol consumption is a major risk factor for the burden of disease globally. This burden is estimated using Relative Risk (RR) functions for alcohol from meta-analyses that use data from all countries; however, for Russia and surrounding countries, country-specific risk data may need to be used. The objective of this paper is to compare the estimated burden of alcohol consumption calculated using Russia-specific alcohol RRs with the estimated burden of alcohol consumption calculated using alcohol RRs from meta-analyses. Data for 2012 on drinking indicators were calculated based on the Global Information System on Alcohol and Health. Data for 2012 on mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years (DALYs) lost by cause were obtained by country from the World Health Organization. Alcohol Population-Attributable Fractions (PAFs) were calculated based on a risk modelling methodology from Russia. These PAFs were compared to PAFs calculated using methods applied for all other countries. The 95% Uncertainty Intervals (UIs) for the alcohol PAFs were calculated using a Monte Carlo-like method. Using Russia-specific alcohol RR functions, in Russia in 2012 alcohol caused an estimated 231,900 deaths (95% UI: 185,600 to 278,200) (70,800 deaths among women and 161,100 deaths among men) and 13,295,000 DALYs lost (95% UI: 11,242,000 to 15,348,000) (3,670,000 DALYs lost among women and 9,625,000 DALYs lost among men) among people 0 to 64 years of age. This compares to an estimated 165,600 deaths (95% UI: 97,200 to 228,100) (29,700 deaths among women and 135,900 deaths among men) and 10,623,000 DALYs lost (95% UI: 7,265,000 to 13,754,000) (1,783,000 DALYs lost among women and 8,840,000 DALYs lost among men) among people 0 to 64 years of age caused by alcohol when non-Russia-specific alcohol RRs were used. Results indicate that if the Russia-specific RRs are used when estimating the health burden attributable to alcohol consumption in
Proteinuria and Reduced Estimated Glomerular Filtration Rate Independently Predict Risk for Acute Myocardial Infarction: Findings from a Population-Based Study in Keelung, Taiwan.

PubMed

Chang, Shu-Hsuan; Tsai, Chia-Ti; Yen, Amy Ming-Fang; Lei, Meng-Huan; Chen, Hsiu-Hsi; Tseng, Chuen-Den

2015-03-01

The aim of this study was to evaluate the independent roles of proteinuria and reduced estimated glomerular filtration rate (GFR) in the development of acute myocardial infarction in a northern Taiwanese population. We conducted a community-based prospective cohort study in Keelung, the northernmost county of Taiwan. A total of 63,129 subjects (63% women) ≥ 20 years of age who had no history of coronary heart disease were recruited and followed-up. Univariate and multivariate proportional hazards regression analysis was performed to assess the association between proteinuria and estimated GFR and the risk of acute myocardial infarction. There were 305 new cases of acute myocardial infarction (114 women and 191 men) documented during a four-year follow-up period. After adjustment of potential confounding covariates, heavier proteinuria (dipstick urinalysis reading 3+) and estimated GFR of less than 60 ml/min/1.73 m(2) independently predicted increased risk of developing acute myocardial infarction. The adjusted hazard ratio (aHR) of heavier proteinuria for occurrence of acute myocardial infarction was 1.85 [95% confidence intervals (CI), 1.17-2.91, p < 0.01] (vs. the reference group: negative dipstick proteinuria). The aHR of estimated GFR of 30-59 ml/min/1.73 m(2) for occurrence of acute myocardial infarction was 2.4 (95% CI, 1.31-4.38, p < 0.01) (vs. the reference group: estimated GFR ≥ 90 ml/ min/1.73 m(2)), and that of estimated GFR of 15-29 ml/min/1.73 m(2) was 5.26 (95% CI, 2.26-12.26, p < 0.01). We demonstrated that both heavier proteinuria and lower estimated GFR are significant independent predictors of developing future acute myocardial infarction in a northern Taiwanese population. Acute myocardial infarction; Estimated glomerular filtration rate; Proteinuria.
Psychosocial Adjustment and Perceived Risk Among Adolescent Girls From Families With BRCA1/2 or Breast Cancer History

PubMed Central

Patrick-Miller, Linda; Schwartz, Lisa A.; Egleston, Brian L.; Henry-Moss, Dare; Domchek, Susan M.; Daly, Mary B.; Tuchman, Lisa; Moore, Cynthia; Rauch, Paula K.; Shorter, Rebecca; Karpink, Kelsey; Sands, Colleen Burke

2016-01-01

Purpose To evaluate the impact of breast cancer family history and maternal BRCA1/2 mutation on the psychosocial adjustment and perceived risk in girls age 11 to 19 years old. Materials and Methods Girls age 11 to 19 years old with one or more relatives with breast cancer or a familial BRCA1/2 mutation (breast cancer family history [BCFH] positive, n = 208; n = 69 with BRCA1/2-positive mother), peers (BCFH negative, n = 112), and their mothers completed assessments of psychosocial adjustment, breast cancer–specific distress, and perceived risk of breast cancer. Results General psychosocial adjustment did not differ significantly between BCFH-positive and BCFH-negative girls, either by self-report or mother report, except for higher self-esteem among BCFH-positive girls (P = .01). BCFH-positive girls had higher breast cancer–specific distress than BCFH-negative girls (P < .001), but girls from BRCA1/2-positive families did not differ from other BCFH-positive peers. BCFH-positive girls were more likely to report themselves at increased self-risk for breast cancer in adulthood than BCFH-negative peers (74% v 33%, respectively; P ≤ .001). Girls from BRCA1/2-positive families were more likely than other BCFH-positive and BCFH-negative peers to report themselves at increased risk (P < .001). In all groups, perceived risk of breast cancer was associated with older age. Higher breast cancer–specific distress among adolescent girls was associated with higher self-perceived risk of breast cancer and higher maternal breast cancer–specific distress. Conclusion Adolescent girls from BRCA1/2-positive and breast cancer families have higher self-esteem and do not have poorer psychosocial adjustment than peers. However, they do experience greater breast cancer–specific distress and perceived risk of breast cancer, particularly among older girls. Understanding the impact is important to optimize responses to growing up in families at familial and genetic risk for breast
Impact of work-related cancers in Taiwan-Estimation with QALY (quality-adjusted life year) and healthcare costs.

PubMed

Lee, Lukas Jyuhn-Hsiarn; Lin, Cheng-Kuan; Hung, Mei-Chuan; Wang, Jung-Der

2016-12-01

This study estimates the annual numbers of eight work-related cancers, total losses of quality-adjusted life years (QALYs), and lifetime healthcare expenditures that possibly could be saved by improving occupational health in Taiwan. Three databases were interlinked: the Taiwan Cancer Registry, the National Mortality Registry, and the National Health Insurance Research Database. Annual numbers of work-related cancers were estimated based on attributable fractions (AFs) abstracted from a literature review. The survival functions for eight cancers were estimated and extrapolated to lifetime using a semi-parametric method. A convenience sample of 8846 measurements of patients' quality of life with EQ-5D was collected for utility values and multiplied by survival functions to estimate quality-adjusted life expectancies (QALEs). The loss-of-QALE was obtained by subtracting the QALE of cancer from age- and sex-matched referents simulated from national vital statistics. The lifetime healthcare expenditures were estimated by multiplying the survival probability with mean monthly costs paid by the National Health Insurance for cancer diagnosis and treatment and summing this for the expected lifetime. A total of 3010 males and 726 females with eight work-related cancers were estimated in 2010. Among them, lung cancer ranked first in terms of QALY loss, with an annual total loss-of-QALE of 28,463 QALYs and total lifetime healthcare expenditures of US$36.6 million. Successful prevention of eight work-related cancers would not only avoid the occurrence of 3736 cases of cancer, but would also save more than US$70 million in healthcare costs and 46,750 QALYs for the Taiwan society in 2010.
Adjustments of the Pesticide Risk Index Used in Environmental Policy in Flanders

PubMed Central

Fevery, Davina; Peeters, Bob; Lenders, Sonia; Spanoghe, Pieter

2015-01-01

Indicators are used to quantify the pressure of pesticides on the environment. Pesticide risk indicators typically require weighting environmental exposure by a no effect concentration. An indicator based on spread equivalents (ΣSeq) is used in environmental policy in Flanders (Belgium). The pesticide risk for aquatic life is estimated by weighting active ingredient usage by the ratio of their maximum allowable concentration and their soil halflife. Accurate estimates of total pesticide usage in the region are essential in such calculations. Up to 2012, the environmental impact of pesticides was estimated on sales figures provided by the Federal Government. Since 2013, pesticide use is calculated based on results from the Farm Accountancy Data Network (FADN). The estimation of pesticide use was supplemented with data for non-agricultural use based on sales figures of amateur use provided by industry and data obtained from public services. The Seq-indicator was modified to better reflect reality. This method was applied for the period 2009-2012 and showed differences between estimated use and sales figures of pesticides. The estimated use of pesticides based on accountancy data is more accurate compared to sales figures. This approach resulted in a better view on pesticide use and its respective environmental impact in Flanders. PMID:26046655
Adjustments of the Pesticide Risk Index Used in Environmental Policy in Flanders.

PubMed

Fevery, Davina; Peeters, Bob; Lenders, Sonia; Spanoghe, Pieter

2015-01-01

Indicators are used to quantify the pressure of pesticides on the environment. Pesticide risk indicators typically require weighting environmental exposure by a no effect concentration. An indicator based on spread equivalents (ΣSeq) is used in environmental policy in Flanders (Belgium). The pesticide risk for aquatic life is estimated by weighting active ingredient usage by the ratio of their maximum allowable concentration and their soil halflife. Accurate estimates of total pesticide usage in the region are essential in such calculations. Up to 2012, the environmental impact of pesticides was estimated on sales figures provided by the Federal Government. Since 2013, pesticide use is calculated based on results from the Farm Accountancy Data Network (FADN). The estimation of pesticide use was supplemented with data for non-agricultural use based on sales figures of amateur use provided by industry and data obtained from public services. The Seq-indicator was modified to better reflect reality. This method was applied for the period 2009-2012 and showed differences between estimated use and sales figures of pesticides. The estimated use of pesticides based on accountancy data is more accurate compared to sales figures. This approach resulted in a better view on pesticide use and its respective environmental impact in Flanders.
Refining Risk Adjustment for the Proposed CMS Surgical Hip and Femur Fracture Treatment Bundled Payment Program.

PubMed

Cairns, Mark A; Ostrum, Robert F; Clement, R Carter

2018-02-21

The U.S. Centers for Medicare & Medicaid Services (CMS) has been considering the implementation of a mandatory bundled payment program, the Surgical Hip and Femur Fracture Treatment (SHFFT) model. However, bundled payments without appropriate risk adjustment may be inequitable to providers and may restrict access to care for certain patients. The SHFFT proposal includes adjustment using the Diagnosis-Related Group (DRG) and geographic location. The goal of the current study was to identify and quantify patient factors that could improve risk adjustment for SHFFT bundled payments. We retrospectively reviewed a 5% random sample of Medicare data from 2008 to 2012. A total of 27,898 patients were identified who met SHFFT inclusion criteria (DRG 480, 481, and 482). Reimbursement was determined for each patient over the bundle period (the surgical hospitalization and 90 days of post-discharge care). Multivariable regression was performed to test demographic factors, comorbidities, geographic location, and specific surgical procedures for associations with reimbursement. The average reimbursement was $23,632 ± $17,587. On average, reimbursements for male patients were $1,213 higher than for female patients (p < 0.01). Younger age was also associated with higher payments; e.g., reimbursement for those ≥85 years of age averaged $2,282 ± $389 less than for those aged 65 to 69 (p < 0.01). Most comorbidities were associated with higher reimbursement, but dementia was associated with lower payments, by an average of $2,354 ± $243 (p < 0.01). Twenty-two procedure codes are included in the bundle, and patients with the 3 most common codes accounted for 98% of the cases, with average reimbursement ranging from $22,527 to $24,033. Less common procedures varied by >$20,000 in average reimbursement (p < 0.01). DRGs also showed significant differences in reimbursement (p < 0.01); e.g., DRG 480 was reimbursed by an average of $10,421 ± $543 more than DRG 482. Payments varied
Methods to assess performance of models estimating risk of death in intensive care patients: a review.

PubMed

Cook, D A

2006-04-01

Models that estimate the probability of death of intensive care unit patients can be used to stratify patients according to the severity of their condition and to control for casemix and severity of illness. These models have been used for risk adjustment in quality monitoring, administration, management and research and as an aid to clinical decision making. Models such as the Mortality Prediction Model family, SAPS II, APACHE II, APACHE III and the organ system failure models provide estimates of the probability of in-hospital death of ICU patients. This review examines methods to assess the performance of these models. The key attributes of a model are discrimination (the accuracy of the ranking in order of probability of death) and calibration (the extent to which the model's prediction of probability of death reflects the true risk of death). These attributes should be assessed in existing models that predict the probability of patient mortality, and in any subsequent model that is developed for the purposes of estimating these probabilities. The literature contains a range of approaches for assessment which are reviewed and a survey of the methodologies used in studies of intensive care mortality models is presented. The systematic approach used by Standards for Reporting Diagnostic Accuracy provides a framework to incorporate these theoretical considerations of model assessment and recommendations are made for evaluation and presentation of the performance of models that estimate the probability of death of intensive care patients.
Estimating and mapping the population at risk of sleeping sickness.

PubMed

Simarro, Pere P; Cecchi, Giuliano; Franco, José R; Paone, Massimo; Diarra, Abdoulaye; Ruiz-Postigo, José Antonio; Fèvre, Eric M; Mattioli, Raffaele C; Jannin, Jean G

2012-01-01

Human African trypanosomiasis (HAT), also known as sleeping sickness, persists as a public health problem in several sub-Saharan countries. Evidence-based, spatially explicit estimates of population at risk are needed to inform planning and implementation of field interventions, monitor disease trends, raise awareness and support advocacy. Comprehensive, geo-referenced epidemiological records from HAT-affected countries were combined with human population layers to map five categories of risk, ranging from "very high" to "very low," and to estimate the corresponding at-risk population. Approximately 70 million people distributed over a surface of 1.55 million km(2) are estimated to be at different levels of risk of contracting HAT. Trypanosoma brucei gambiense accounts for 82.2% of the population at risk, the remaining 17.8% being at risk of infection from T. b. rhodesiense. Twenty-one million people live in areas classified as moderate to very high risk, where more than 1 HAT case per 10,000 inhabitants per annum is reported. Updated estimates of the population at risk of sleeping sickness were made, based on quantitative information on the reported cases and the geographic distribution of human population. Due to substantial methodological differences, it is not possible to make direct comparisons with previous figures for at-risk population. By contrast, it will be possible to explore trends in the future. The presented maps of different HAT risk levels will help to develop site-specific strategies for control and surveillance, and to monitor progress achieved by ongoing efforts aimed at the elimination of sleeping sickness.
The relationship between the C-statistic of a risk-adjustment model and the accuracy of hospital report cards: a Monte Carlo Study.

PubMed

Austin, Peter C; Reeves, Mathew J

2013-03-01

Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards. To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards. Monte Carlo simulations were used to examine this issue. We examined the influence of 3 factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada. The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact. The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card.
The relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards: A Monte Carlo study

PubMed Central

Austin, Peter C.; Reeves, Mathew J.

2015-01-01

Background Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk-adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards. Objectives To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards. Research Design Monte Carlo simulations were used to examine this issue. We examined the influence of three factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk-adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada. Results The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact. Conclusions The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card. PMID:23295579
Mate guarding in the Seychelles warbler is energetically costly and adjusted to paternity risk.

PubMed

Komdeur, J

2001-10-22

Males may increase their fitness through extra-pair copulations (copulations outside the pair bond) that result in extra-pair fertilizations, but also risk lost paternity when they leave their own mate unguarded. The fitness costs of cuckoldry for Seychelles warblers (Acrocephalus sechellensis) are considerable because warblers have a single-egg clutch and, given the short breeding season, no time for a successful replacement clutch. Neighbouring males are the primary threat to a male's genetic paternity. Males minimize their loss of paternity by guarding their mates to prevent them from having extra-pair copulations during their fertile period. Here, I provide experimental evidence that mate-guarding behaviour is energetically costly and that the expression of this trade-off is adjusted to paternity risk (local male density). Free-living males that were induced to reduce mate guarding spent significantly more time foraging and gained significantly better body condition than control males. The larger the reduction in mate guarding, the more pronounced was the increase in foraging and body condition (accounting for food availability). An experimental increase in paternity risk resulted in an increase in mate-guarding intensity and a decrease in foraging and body condition, and vice versa. This is examined using both cross-sectional and longitudinal data. This study on the Seychelles warbler offers experimental evidence that mate guarding is energetically costly and adjusted to paternity risk.
Adjusted Hospital Outcomes of Abdominal Aortic Aneurysm Surgery Reported in the Dutch Surgical Aneurysm Audit.

PubMed

Lijftogt, N; Vahl, A C; Wilschut, E D; Elsman, B H P; Amodio, S; van Zwet, E W; Leijdekkers, V J; Wouters, M W J M; Hamming, J F

2017-04-01

The Dutch Surgical Aneurysm Audit (DSAA) is mandatory for all patients with primary abdominal aortic aneurysms (AAAs) in the Netherlands. The aims are to present the observed outcomes of AAA surgery against the predicted outcomes by means of V-POSSUM (Vascular-Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity). Adjusted mortality was calculated by the original and re-estimated V(physiology)-POSSUM for hospital comparisons. All patients operated on from January 2013 to December 2014 were included for analysis. Calibration and discrimination of V-POSSUM and V(p)-POSSUM was analysed. Mortality was benchmarked by means of the original V(p)-POSSUM formula and risk-adjusted by the re-estimated V(p)-POSSUM on the DSAA. In total, 5898 patients were included for analysis: 4579 with elective AAA (EAAA) and 1319 with acute abdominal aortic aneurysm (AAAA), acute symptomatic (SAAA; n = 371) or ruptured (RAAA; n = 948). The percentage of endovascular aneurysm repair (EVAR) varied between hospitals but showed no relation to hospital volume (EAAA: p = .12; AAAA: p = .07). EAAA, SAAA, and RAAA mortality was, respectively, 1.9%, 7.5%, and 28.7%. Elective mortality was 0.9% after EVAR and 5.0% after open surgical repair versus 15.6% and 27.4%, respectively, after AAAA. V-POSSUM overestimated mortality in most EAAA risk groups (p < .01). The discriminative ability of V-POSSUM in EAAA was moderate (C-statistic: .719) and poor for V(p)-POSSUM (C-statistic: .665). V-POSSUM in AAAA repair overestimated in high risk groups, and underestimated in low risk groups (p < .01). The discriminative ability in AAAA of V-POSSUM was moderate (.713) and of V(p)-POSSUM poor (.688). Risk adjustment by the re-estimated V(p)-POSSUM did not have any effect on hospital variation in EAAA but did in AAAA. Mortality in the DSAA was in line with the literature but is not discriminative for hospital comparisons in EAAA. Adjusting for V(p)-POSSUM, revealed no
A bias-adjusted evidence synthesis of RCT and observational data: the case of total hip replacement.

PubMed

Schnell-Inderst, Petra; Iglesias, Cynthia P; Arvandi, Marjan; Ciani, Oriana; Matteucci Gothe, Raffaella; Peters, Jaime; Blom, Ashley W; Taylor, Rod S; Siebert, Uwe

2017-02-01

Evaluation of clinical effectiveness of medical devices differs in some aspects from the evaluation of pharmaceuticals. One of the main challenges identified is lack of robust evidence and a will to make use of experimental and observational studies (OSs) in quantitative evidence synthesis accounting for internal and external biases. Using a case study of total hip replacement to compare the risk of revision of cemented and uncemented implant fixation modalities, we pooled treatment effect estimates from OS and RCTs, and simplified existing methods for bias-adjusted evidence synthesis to enhance practical application. We performed an elicitation exercise using methodological and clinical experts to determine the strength of beliefs about the magnitude of internal and external bias affecting estimates of treatment effect. We incorporated the bias-adjusted treatment effects into a generalized evidence synthesis, calculating both frequentist and Bayesian statistical models. We estimated relative risks as summary effect estimates with 95% confidence/credibility intervals to capture uncertainty. When we compared alternative approaches to synthesizing evidence, we found that the pooled effect size strongly depended on the inclusion of observational data as well as on the use bias-adjusted estimates. We demonstrated the feasibility of using observational studies in meta-analyses to complement RCTs and incorporate evidence from a wider spectrum of clinically relevant studies and healthcare settings. To ensure internal validity, OS data require sufficient correction for confounding and selection bias, either through study design and primary analysis, or by applying post-hoc bias adjustments to the results. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.
Sample size re-estimation and other midcourse adjustments with sequential parallel comparison design.

PubMed

Silverman, Rachel K; Ivanova, Anastasia

2017-01-01

Sequential parallel comparison design (SPCD) was proposed to reduce placebo response in a randomized trial with placebo comparator. Subjects are randomized between placebo and drug in stage 1 of the trial, and then, placebo non-responders are re-randomized in stage 2. Efficacy analysis includes all data from stage 1 and all placebo non-responding subjects from stage 2. This article investigates the possibility to re-estimate the sample size and adjust the design parameters, allocation proportion to placebo in stage 1 of SPCD, and weight of stage 1 data in the overall efficacy test statistic during an interim analysis.
Development and Validation of Perioperative Risk-Adjustment Models for Hip Fracture Repair, Total Hip Arthroplasty, and Total Knee Arthroplasty.

PubMed

Schilling, Peter L; Bozic, Kevin J

2016-01-06

Comparing outcomes across providers requires risk-adjustment models that account for differences in case mix. The burden of data collection from the clinical record can make risk-adjusted outcomes difficult to measure. The purpose of this study was to develop risk-adjustment models for hip fracture repair (HFR), total hip arthroplasty (THA), and total knee arthroplasty (TKA) that weigh adequacy of risk adjustment against data-collection burden. We used data from the American College of Surgeons National Surgical Quality Improvement Program to create derivation cohorts for HFR (n = 7000), THA (n = 17,336), and TKA (n = 28,661). We developed logistic regression models for each procedure using age, sex, American Society of Anesthesiologists (ASA) physical status classification, comorbidities, laboratory values, and vital signs-based comorbidities as covariates, and validated the models with use of data from 2012. The derivation models' C-statistics for mortality were 80%, 81%, 75%, and 92% and for adverse events were 68%, 68%, 60%, and 70% for HFR, THA, TKA, and combined procedure cohorts. Age, sex, and ASA classification accounted for a large share of the explained variation in mortality (50%, 58%, 70%, and 67%) and adverse events (43%, 45%, 46%, and 68%). For THA and TKA, these three variables were nearly as predictive as models utilizing all covariates. HFR model discrimination improved with the addition of comorbidities and laboratory values; among the important covariates were functional status, low albumin, high creatinine, disseminated cancer, dyspnea, and body mass index. Model performance was similar in validation cohorts. Risk-adjustment models using data from health records demonstrated good discrimination and calibration for HFR, THA, and TKA. It is possible to provide adequate risk adjustment using only the most predictive variables commonly available within the clinical record. This finding helps to inform the trade-off between model performance and data

Comparison of crude and adjusted mortality rates from leading causes of death in northeastern Brazil.

PubMed

França, Elisabeth; Rao, Chalapati; Abreu, Daisy Maria Xavier de; Souza, Maria de Fátima Marinho de; Lopez, Alan D

2012-04-01

To present how the adjustment of incompleteness and misclassification of causes of death in the vital registration (VR) system can contribute to more accurate estimates of the risk of mortality from leading causes of death in northeastern Brazil. After estimating the total numbers of deaths by age and sex in Brazil's Northeast region in 2002-2004 by correcting for undercount in the VR data, adjustment algorithms were applied to the reported cause-of-death structure. Average annual age-standardized mortality rates were computed by cause, with and without the corrections, and compared to death rates for Brazil's South region after adjustments for potential misdiagnosis. Death rates from ischemic heart disease, lower respiratory infections, chronic obstructive pulmonary disease, and perinatal conditions were more than 100% higher for both sexes than what was suggested by the routine VR data. Corrected cause-specific mortality rates were higher in the Northeast region versus the South region for the majority of causes of death, including several noncommunicable conditions. Failure to adjust VR data for undercount of cases reported and misdiagnoses will cause underestimation of mortality risks for the populations of the Northeast region, which are more vulnerable than those in other regions of the country. In order to more reliably understand the pattern of disease, all cause-specific mortality rates in poor populations should be adjusted.
Performance evaluation of inpatient service in Beijing: a horizontal comparison with risk adjustment based on Diagnosis Related Groups

PubMed Central

Jian, Weiyan; Huang, Yinmin; Hu, Mu; Zhang, Xiumei

2009-01-01

Background The medical performance evaluation, which provides a basis for rational decision-making, is an important part of medical service research. Current progress with health services reform in China is far from satisfactory, without sufficient regulation. To achieve better progress, an effective tool for evaluating medical performance needs to be established. In view of this, this study attempted to develop such a tool appropriate for the Chinese context. Methods Data was collected from the front pages of medical records (FPMR) of all large general public hospitals (21 hospitals) in the third and fourth quarter of 2007. Locally developed Diagnosis Related Groups (DRGs) were introduced as a tool for risk adjustment and performance evaluation indicators were established: Charge Efficiency Index (CEI), Time Efficiency Index (TEI) and inpatient mortality of low-risk group cases (IMLRG), to reflect respectively work efficiency and medical service quality. Using these indicators, the inpatient services' performance was horizontally compared among hospitals. Case-mix Index (CMI) was used to adjust efficiency indices and then produce adjusted CEI (aCEI) and adjusted TEI (aTEI). Poisson distribution analysis was used to test the statistical significance of the IMLRG differences between different hospitals. Results Using the aCEI, aTEI and IMLRG scores for the 21 hospitals, Hospital A and C had relatively good overall performance because their medical charges were lower, LOS shorter and IMLRG smaller. The performance of Hospital P and Q was the worst due to their relatively high charge level, long LOS and high IMLRG. Various performance problems also existed in the other hospitals. Conclusion It is possible to develop an accurate and easy to run performance evaluation system using Case-Mix as the tool for risk adjustment, choosing indicators close to consumers and managers, and utilizing routine report forms as the basic information source. To keep such a system running
Performance evaluation of inpatient service in Beijing: a horizontal comparison with risk adjustment based on Diagnosis Related Groups.

PubMed

Jian, Weiyan; Huang, Yinmin; Hu, Mu; Zhang, Xiumei

2009-04-30

The medical performance evaluation, which provides a basis for rational decision-making, is an important part of medical service research. Current progress with health services reform in China is far from satisfactory, without sufficient regulation. To achieve better progress, an effective tool for evaluating medical performance needs to be established. In view of this, this study attempted to develop such a tool appropriate for the Chinese context. Data was collected from the front pages of medical records (FPMR) of all large general public hospitals (21 hospitals) in the third and fourth quarter of 2007. Locally developed Diagnosis Related Groups (DRGs) were introduced as a tool for risk adjustment and performance evaluation indicators were established: Charge Efficiency Index (CEI), Time Efficiency Index (TEI) and inpatient mortality of low-risk group cases (IMLRG), to reflect respectively work efficiency and medical service quality. Using these indicators, the inpatient services' performance was horizontally compared among hospitals. Case-mix Index (CMI) was used to adjust efficiency indices and then produce adjusted CEI (aCEI) and adjusted TEI (aTEI). Poisson distribution analysis was used to test the statistical significance of the IMLRG differences between different hospitals. Using the aCEI, aTEI and IMLRG scores for the 21 hospitals, Hospital A and C had relatively good overall performance because their medical charges were lower, LOS shorter and IMLRG smaller. The performance of Hospital P and Q was the worst due to their relatively high charge level, long LOS and high IMLRG. Various performance problems also existed in the other hospitals. It is possible to develop an accurate and easy to run performance evaluation system using Case-Mix as the tool for risk adjustment, choosing indicators close to consumers and managers, and utilizing routine report forms as the basic information source. To keep such a system running effectively, it is necessary to
Minimum Expected Risk Estimation for Near-neighbor Classification

DTIC Science & Technology

2006-04-01

We consider the problems of class probability estimation and classification when using near-neighbor classifiers, such as k-nearest neighbors ( kNN ...estimate for weighted kNN classifiers with different prior information, for a broad class of risk functions. Theory and simulations show how significant...the difference is compared to the standard maximum likelihood weighted kNN estimates. Comparisons are made with uniform weights, symmetric weights
Estimation of norovirus infection risks to consumers of wastewater-irrigated food crops eaten raw.

PubMed

Mara, Duncan; Sleigh, Andrew

2010-03-01

A quantitative microbial risk analysis-Monte Carlo method was used to estimate norovirus infection risks to consumers of wastewater-irrigated lettuce. Using the same assumptions as used in the 2006 WHO guidelines for the safe use of wastewater in agriculture, a norovirus reduction of 6 log units was required to achieve a norovirus infection risk of approximately 10(-3) per person per year (pppy), but for a lower consumption of lettuce (40-48 g per week vs. 350 g per week) the required reduction was 5 log units. If the tolerable additional disease burden is increased from a DALY (disability-adjusted life year) loss of 10(-6) pppy (the value used in the WHO guidelines) to 10(-5) pppy, the required pathogen reduction is one order of magnitude lower. Reductions of 4-6 log units can be achieved by very simple partial treatment (principally settling to achieve a 1-log unit reduction) supplemented by very reliable post-treatment health-protection control measures such as pathogen die-off (1-2 log units), produce washing in cold water (1 log unit) and produce disinfection (3 log units).
How are flood risk estimates affected by the choice of return-periods?

NASA Astrophysics Data System (ADS)

Ward, P. J.; de Moel, H.; Aerts, J. C. J. H.

2011-12-01

Flood management is more and more adopting a risk based approach, whereby flood risk is the product of the probability and consequences of flooding. One of the most common approaches in flood risk assessment is to estimate the damage that would occur for floods of several exceedance probabilities (or return periods), to plot these on an exceedance probability-loss curve (risk curve) and to estimate risk as the area under the curve. However, there is little insight into how the selection of the return-periods (which ones and how many) used to calculate risk actually affects the final risk calculation. To gain such insights, we developed and validated an inundation model capable of rapidly simulating inundation extent and depth, and dynamically coupled this to an existing damage model. The method was applied to a section of the River Meuse in the southeast of the Netherlands. Firstly, we estimated risk based on a risk curve using yearly return periods from 2 to 10 000 yr (€ 34 million p.a.). We found that the overall risk is greatly affected by the number of return periods used to construct the risk curve, with over-estimations of annual risk between 33% and 100% when only three return periods are used. In addition, binary assumptions on dike failure can have a large effect (a factor two difference) on risk estimates. Also, the minimum and maximum return period considered in the curve affects the risk estimate considerably. The results suggest that more research is needed to develop relatively simple inundation models that can be used to produce large numbers of inundation maps, complementary to more complex 2-D-3-D hydrodynamic models. It also suggests that research into flood risk could benefit by paying more attention to the damage caused by relatively high probability floods.
Biomechanical Indices for Rupture Risk Estimation in Abdominal Aortic Aneurysms.

PubMed

Leemans, Eva L; Willems, Tineke P; van der Laan, Maarten J; Slump, Cornelis H; Zeebregts, Clark J

2017-04-01

To review the use of biomechanical indices for the estimation of abdominal aortic aneurysm (AAA) rupture risk, emphasizing their potential use in a clinical setting. A search of the PubMed, Embase, Scopus, and Compendex databases was made up to June 2015 to identify articles involving biomechanical analysis of AAA rupture risk. Outcome variables [aneurysm diameter, peak wall stress (PWS), peak wall shear stress (PWSS), wall strain, peak wall rupture index (PWRI), and wall stiffness] were compared for asymptomatic intact AAAs vs symptomatic or ruptured AAAs. For quantitative analysis of the pooled data, a random effects model was used to calculate the standard mean differences (SMDs) with the 95% confidence interval (CI) for the biomechanical indices. The initial database searches yielded 1894 independent articles of which 19 were included in the analysis. The PWS was significantly higher in the symptomatic/ruptured group, with a SMD of 1.11 (95% CI 0.93 to 1.26, p<0.001). Likewise, the PWRI was significantly higher in the ruptured or symptomatic group, with a SMD of 1.15 (95% CI 0.30 to 2.01, p=0.008). After adjustment for the aneurysm diameter, the PWS remained higher in the ruptured or symptomatic group, with a SMD of 0.85 (95% CI 0.46 to 1.23, p<0.001). Less is known of the wall shear stress and wall strain indices, as too few studies were available for analysis. Biomechanical indices are a promising tool in the assessment of AAA rupture risk as they incorporate several factors, including geometry, tissue properties, and patient-specific risk factors. However, clinical implementation of biomechanical AAA assessment remains a challenge owing to a lack of standardization.
A new methodological approach to adjust alcohol exposure distributions to improve the estimation of alcohol-attributable fractions.

PubMed

Parish, William J; Aldridge, Arnie; Allaire, Benjamin; Ekwueme, Donatus U; Poehler, Diana; Guy, Gery P; Thomas, Cheryll C; Trogdon, Justin G

2017-11-01

To assess the burden of excessive alcohol use, researchers estimate alcohol-attributable fractions (AAFs) routinely. However, under-reporting in survey data can bias these estimates. We present an approach that adjusts for under-reporting in the estimation of AAFs, particularly within subgroups. This framework is a refinement of a previous method conducted by Rehm et al. We use a measurement error model to derive the 'true' alcohol distribution from a 'reported' alcohol distribution. The 'true' distribution leverages per-capita sales data to identify the distribution average and then identifies the shape of the distribution with self-reported survey data. Data are from the National Alcohol Survey (NAS), the National Household Survey on Drug Abuse (NHSDA) and the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). We compared our approach with previous approaches by estimating the AAF of female breast cancer cases. Compared with Rehm et al.'s approach, our refinement performs similarly under a gamma assumption. For example, among females aged 18-25 years, the two approaches produce estimates from NHSDA that are within a percentage point. However, relaxing the gamma assumption generally produces more conservative evidence. For example, among females aged 18-25 years, estimates from NHSDA based on the best-fitting distribution are only 19.33% of breast cancer cases, which is a much smaller proportion than the gamma-based estimates of approximately 28%. A refinement of Rehm et al.'s approach to adjusting for underreporting in the estimation of alcohol-attributable fractions provides more flexibility. This flexibility can avoid biases associated with failing to account for the underlying differences in alcohol consumption patterns across different study populations. Comparisons of our refinement with Rehm et al.'s approach show that results are similar when a gamma distribution is assumed. However, results are appreciably lower when the best
The Effect of Adding Comorbidities to Current Centers for Disease Control and Prevention Central-Line-Associated Bloodstream Infection Risk-Adjustment Methodology.

PubMed

Jackson, Sarah S; Leekha, Surbhi; Magder, Laurence S; Pineles, Lisa; Anderson, Deverick J; Trick, William E; Woeltje, Keith F; Kaye, Keith S; Stafford, Kristen; Thom, Kerri; Lowe, Timothy J; Harris, Anthony D

2017-09-01

BACKGROUND Risk adjustment is needed to fairly compare central-line-associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes. METHODS Using a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank. RESULTS Overall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51-0.59) for the ICU-type model and 0.64 (95% CI, 0.60-0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model. CONCLUSIONS Our risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals. Infect Control Hosp Epidemiol 2017;38:1019-1024.
Using risk adjustment approaches in child welfare performance measurement: Applications and insights from health and mental health settings

PubMed Central

Raghavan, Ramesh

2014-01-01

Federal policymaking in the last decade has dramatically expanded performance measurement within child welfare systems, and states are currently being fiscally penalized for poor performance on defined outcomes. However, in contrast to performance measurement in health settings, current policy holds child welfare systems solely responsible for meeting outcomes, largely without taking into account the effects of factors at the level of the child, and his or her social ecology, that might undermine the performance of child welfare agencies. Appropriate measurement of performance is predicated upon the ability to disentangle individual, as opposed to organizational, determinants of outcomes, which is the goal of risk adjustment methodologies. This review briefly conceptualizes and examines risk adjustment approaches in health and child welfare, suggests approaches to expanding its use to appropriately measure the performance of child welfare agencies, and highlights research gaps that diminish the appropriate use of risk adjustment approaches – and which consequently suggest the need for caution – in policymaking around performance measurement of child welfare agencies. PMID:25253917
Screening Mammography: Patient Perceptions and Preferences Regarding Communication of Estimated Breast Cancer Risk.

PubMed

Amornsiripanitch, Nita; Mangano, Mark; Niell, Bethany L

2017-05-01

Many models exist to estimate a woman's risk of development of breast cancer. At screening mammography, many imaging centers collect data required for these models to identify women who may benefit from supplemental screening and referral for cancer risk assessment. The purpose of this study was to discern perceptions and preferences of screening mammography patients regarding communication of estimated breast cancer risk. An anonymous survey was distributed to screening and surveillance mammography patients between April and June 2015. Survey questions were designed to assess patient preferences regarding the receipt and complexity of risk estimate communication, including hypothetical scenarios with and without > 20% estimated risk of breast cancer. The McNemar test and the Wilcoxon signed rank test were used with p ≤ 0.05 considered statistically significant. The survey was distributed to 1061 screening and surveillance mammography patients, and 503 patients responded (response rate, 47%). Although 86% (431/503) of patients expressed interest in learning their estimated risk, only 8% (38/503) had undergone formal risk assessment. The preferred method (241 respondents [26%]) of communication of risk < 20% was a mailed letter accompanying annual mammogram results. For risk > 20%, patients preferred oral communication and were 10-fold as likely to choose only oral communication (p < 0.000001). For risk < 20% and > 20%, patients preferred to learn their estimated risk in great detail (69% and 85%), although women were significantly more likely to choose greater detail for risk > 20% (p < 0.00001). Screening mammography patients expressed interest in learning their estimated risk of breast cancer regardless of their level of hypothetical risk.
Nonparametric estimation of benchmark doses in environmental risk assessment

PubMed Central

Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

2013-01-01

Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133
Metabolic factors and genetic risk mediate familial type 2 diabetes risk in the Framingham Heart Study

PubMed Central

Raghavan, Sridharan; Porneala, Bianca; McKeown, Nicola; Fox, Caroline S.; Dupuis, Josée; Meigs, James B.

2015-01-01

Aims/hypothesis Type 2 diabetes mellitus in parents is a strong determinant of diabetes risk in their offspring. We hypothesise that offspring diabetes risk associated with parental diabetes is mediated by metabolic risk factors. Methods We studied initially non-diabetic participants of the Framingham Offspring Study. Metabolic risk was estimated using beta cell corrected insulin response (CIR), HOMA-IR or a count of metabolic syndrome components (metabolic syndrome score [MSS]). Dietary risk and physical activity were estimated using questionnaire responses. Genetic risk score (GRS) was estimated as the count of 62 type 2 diabetes risk alleles. The outcome of incident diabetes in offspring was examined across levels of parental diabetes exposure, accounting for sibling correlation and adjusting for age, sex and putative mediators. The proportion mediated was estimated by comparing regression coefficients for parental diabetes with (βadj) and without (βunadj) adjustments for CIR, HOMA-IR, MSS and GRS (percentage mediated = 1 – βadj / βunadj). Results Metabolic factors mediated 11% of offspring diabetes risk associated with parental diabetes, corresponding to a reduction in OR per diabetic parent from 2.13 to 1.96. GRS mediated 9% of risk, corresponding to a reduction in OR per diabetic parent from 2.13 to 1.99. Conclusions/interpretation Metabolic risk factors partially mediated offspring type 2 diabetes risk conferred by parental diabetes to a similar magnitude as genetic risk. However, a substantial proportion of offspring diabetes risk associated with parental diabetes remains unexplained by metabolic factors, genetic risk, diet and physical activity, suggesting that important familial influences on diabetes risk remain undiscovered. PMID:25619168
Comparison of prospective risk estimates for postoperative complications: human vs computer model.

PubMed

Glasgow, Robert E; Hawn, Mary T; Hosokawa, Patrick W; Henderson, William G; Min, Sung-Joon; Richman, Joshua S; Tomeh, Majed G; Campbell, Darrell; Neumayer, Leigh A

2014-02-01

Surgical quality improvement tools such as NSQIP are limited in their ability to prospectively affect individual patient care by the retrospective audit and feedback nature of their design. We hypothesized that statistical models using patient preoperative characteristics could prospectively provide risk estimates of postoperative adverse events comparable to risk estimates provided by experienced surgeons, and could be useful for stratifying preoperative assessment of patient risk. This was a prospective observational cohort. Using previously developed models for 30-day postoperative mortality, overall morbidity, cardiac, thromboembolic, pulmonary, renal, and surgical site infection (SSI) complications, model and surgeon estimates of risk were compared with each other and with actual 30-day outcomes. The study cohort included 1,791 general surgery patients operated on between June 2010 and January 2012. Observed outcomes were mortality (0.2%), overall morbidity (8.2%), and pulmonary (1.3%), cardiac (0.3%), thromboembolism (0.2%), renal (0.4%), and SSI (3.8%) complications. Model and surgeon risk estimates showed significant correlation (p < 0.0001) for each outcome category. When surgeons perceived patient risk for overall morbidity to be low, the model-predicted risk and observed morbidity rates were 2.8% and 4.1%, respectively, compared with 10% and 18% in perceived high risk patients. Patients in the highest quartile of model-predicted risk accounted for 75% of observed mortality and 52% of morbidity. Across a broad range of general surgical operations, we confirmed that the model risk estimates are in fairly good agreement with risk estimates of experienced surgeons. Using these models prospectively can identify patients at high risk for morbidity and mortality, who could then be targeted for intervention to reduce postoperative complications. Published by Elsevier Inc.
Cumulative Socioeconomic Status Risk, Allostatic Load, and Adjustment: A Prospective Latent Profile Analysis With Contextual and Genetic Protective Factors

PubMed Central

Brody, Gene H.; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M.; Evans, Gary W.; Beach, Steven R. H.; Windle, Michael; Simons, Ronald L.; Gerrard, Meg; Gibbons, Frederick X.; Philibert, Robert A.

2012-01-01

The health disparities literature identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative SES risk. The current study was designed to test hypotheses about the developmental precursors to this pattern. Hypotheses were tested with a representative sample of 443 African American youths living in the rural South. Cumulative SES risk and protective processes were assessed at 11-13 years; psychological adjustment was assessed at ages 14-18 years; genotyping at the 5-HTTLPR was conducted at age 16 years; and allostatic load (AL) was assessed at age 19 years. A Latent Profile Analysis identified 5 profiles that evinced distinct patterns of SES risk, AL, and psychological adjustment, with 2 relatively large profiles designated as focal profiles: a physical health vulnerability profile characterized by high SES risk/high AL/low adjustment problems, and a resilient profile characterized by high SES risk/low AL/low adjustment problems. The physical health vulnerability profile mirrored the pattern found in the adult health disparities literature. Multinomial logistic regression analyses indicated that carrying an s allele at the 5-HTTLPR and receiving less peer support distinguished the physical health vulnerability profile from the resilient profile. Protective parenting and planful self-regulation distinguished both focal profiles from the other 3 profiles. The results suggest the public health importance of preventive interventions that enhance coping and reduce the effects of stress across childhood and adolescence. PMID:22709130
Cumulative socioeconomic status risk, allostatic load, and adjustment: a prospective latent profile analysis with contextual and genetic protective factors.

PubMed

Brody, Gene H; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M; Evans, Gary W; Beach, Steven R H; Windle, Michael; Simons, Ronald L; Gerrard, Meg; Gibbons, Frederick X; Philibert, Robert A

2013-05-01

The health disparities literature has identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative socioeconomic status (SES) risk. The current study was designed to test hypotheses about the developmental precursors to this pattern. Hypotheses were tested with a representative sample of 443 African American youths living in the rural South. Cumulative SES risk and protective processes were assessed at ages 11-13 years; psychological adjustment was assessed at ages 14-18 years; genotyping at the 5-HTTLPR was conducted at age 16 years; and allostatic load (AL) was assessed at age 19 years. A latent profile analysis identified 5 profiles that evinced distinct patterns of SES risk, AL, and psychological adjustment, with 2 relatively large profiles designated as focal profiles: a physical health vulnerability profile characterized by high SES risk/high AL/low adjustment problems, and a resilient profile characterized by high SES risk/low AL/low adjustment problems. The physical health vulnerability profile mirrored the pattern found in the adult health disparities literature. Multinomial logistic regression analyses indicated that carrying an s allele at the 5-HTTLPR and receiving less peer support distinguished the physical health vulnerability profile from the resilient profile. Protective parenting and planful self-regulation distinguished both focal profiles from the other 3 profiles. The results suggest the public health importance of preventive interventions that enhance coping and reduce the effects of stress across childhood and adolescence.
Risk adjusted surgical audit in gynaecological oncology: P-POSSUM does not predict outcome.

PubMed

Das, N; Talaat, A S; Naik, R; Lopes, A D; Godfrey, K A; Hatem, M H; Edmondson, R J

2006-12-01

To assess the Physiological and Operative Severity Score for the enumeration of mortality and morbidity (POSSUM) and its validity for use in gynaecological oncology surgery. All patients undergoing gynaecological oncology surgery at the Northern Gynaecological Oncology Centre (NGOC) Gateshead, UK over a period of 12months (2002-2003) were assessed prospectively. Mortality and morbidity predictions using the Portsmouth modification of the POSSUM algorithm (P-POSSUM) were compared to the actual outcomes. Performance of the model was also evaluated using the Hosmer and Lemeshow Chi square statistic (testing the goodness of fit). During this period 468 patients were assessed. The P-POSSUM appeared to over predict mortality rates for our patients. It predicted a 7% mortality rate for our patients compared to an observed rate of 2% (35 predicted deaths in comparison to 10 observed deaths), a difference that was statistically significant (H&L chi(2)=542.9, d.f. 8, p<0.05). The P-POSSUM algorithm overestimates the risk of mortality for gynaecological oncology patients undergoing surgery. The P-POSSUM algorithm will require further adjustments prior to adoption for gynaecological cancer surgery as a risk adjusted surgical audit tool.
Measuring the Value of Mortality Risk Reductions in Turkey

PubMed Central

Tekeşin, Cem; Ara, Shihomi

2014-01-01

The willingness to pay (WTP) for mortality risk reduction from four causes (lung cancer, other type of cancer, respiratory disease, traffic accident) are estimated using random parameter logit model with data from choice experiment for three regions in Turkey. The value of statistical life (VSL) estimated for Afsin-Elbistan, Kutahya-Tavsanli, Ankara and the pooled case are found as 0.56, 0.35, 0.46 and 0.49 million Purchasing Power Parity (PPP) adjusted 2012 US dollars (USD). Different types of risk cause different VSL estimates and we found the lung cancer premium of 213% against traffic accident. The effects of one-year-delayed provision of risk-reduction service are the reduction of WTP by 482 TL ($318 in PPP adjusted USD) per person on average, and the disutility from status-quo (zero risk reduction) against alternative is found to be 891 TL ($589 in PPP adjusted USD) per person on average. Senior discounts of VSL are partially determined by status-quo preference and the amount of discount decreases once the status-quo bias is removed. The peak VSL is found to be for the age group 30–39 and the average VSL for the age group is 0.8 million PPP adjusted USD). Turkey’s compliance to European Union (EU) air quality standard will cause welfare gains of total 373 million PPP adjusted USD for our study areas in terms of reduced number of premature mortality. PMID:25000150
Toxoplasma gondii infection in Kyrgyzstan: seroprevalence, risk factor analysis, and estimate of congenital and AIDS-related toxoplasmosis.

PubMed

Minbaeva, Gulnara; Schweiger, Alexander; Bodosheva, Aigerim; Kuttubaev, Omurbek; Hehl, Adrian B; Tanner, Isabelle; Ziadinov, Iskender; Torgerson, Paul R; Deplazes, Peter

2013-01-01

HIV-prevalence, as well as incidence of zoonotic parasitic diseases like cystic echinococcosis, has increased in the Kyrgyz Republic due to fundamental socio-economic changes after the breakdown of the Soviet Union. The possible impact on morbidity and mortality caused by Toxoplasma gondii infection in congenital toxoplasmosis or as an opportunistic infection in the emerging AIDS pandemic has not been reported from Kyrgyzstan. We screened 1,061 rural and 899 urban people to determine the seroprevalence of T. gondii infection in 2 representative but epidemiologically distinct populations in Kyrgyzstan. The rural population was from a typical agricultural district where sheep husbandry is a major occupation. The urban population was selected in collaboration with several diagnostic laboratories in Bishkek, the largest city in Kyrgyzstan. We designed a questionnaire that was used on all rural subjects so a risk-factor analysis could be undertaken. The samples from the urban population were anonymous and only data with regard to age and gender was available. Estimates of putative cases of congenital and AIDS-related toxoplasmosis in the whole country were made from the results of the serology. Specific antibodies (IgG) against Triton X-100 extracted antigens of T. gondii tachyzoites from in vitro cultures were determined by ELISA. Overall seroprevalence of infection with T. gondii in people living in rural vs. urban areas was 6.2% (95%CI: 4.8-7.8) (adjusted seroprevalence based on census figures 5.1%, 95% CI 3.9-6.5), and 19.0% (95%CI: 16.5-21.7) (adjusted 16.4%, 95% CI 14.1-19.3), respectively, without significant gender-specific differences. The seroprevalence increased with age. Independently low social status increased the risk of Toxoplasma seropositivity while increasing numbers of sheep owned decreased the risk of seropositivity. Water supply, consumption of unpasteurized milk products or undercooked meat, as well as cat ownership, had no significant influence
Significance of adjusting salt intake by body weight in the evaluation of dietary salt and blood pressure.

PubMed

Hashimoto, Tomomi; Takase, Hiroyuki; Okado, Tateo; Sugiura, Tomonori; Yamashita, Sumiyo; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

2016-08-01

The close association between dietary salt and hypertension is well established. However, previous studies generally assessed salt intake without adjustment for body weight. Herein, we investigated the significance of body weight-adjusted salt intake in the general population. The present cross-sectional study included 7629 participants from our yearly physical checkup program, and their salt intake was assessed using a spot urine test to estimate 24-hour urinary salt excretion. Total salt intake increased with increasing body weight. Body weight-adjusted salt intake was greater in participants with hypertension than in those without hypertension. Systolic blood pressure, estimated glomerular filtration rate, and urinary albumin were independently correlated with body weight-adjusted salt intake after adjustment for possible cardiovascular risk factors. Excessive body weight-adjusted salt intake could be related to an increase in blood pressure and hypertensive organ damage. Adjustment for body weight might therefore provide clinically important information when assessing individual salt intake. Copyright © 2016 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.

Comparing risk estimates following diagnostic CT radiation exposures employing different methodological approaches.

PubMed

Kashcheev, Valery V; Pryakhin, Evgeny A; Menyaylo, Alexander N; Chekin, Sergey Yu; Ivanov, Viktor K

2014-06-01

The current study has two aims: the first is to quantify the difference between radiation risks estimated with the use of organ or effective doses, particularly when planning pediatric and adult computed tomography (CT) examinations. The second aim is to determine the method of calculating organ doses and cancer risk using dose-length product (DLP) for typical routine CT examinations. In both cases, the radiation-induced cancer risks from medical CT examinations were evaluated as a function of gender and age. Lifetime attributable risk values from CT scanning were estimated with the use of ICRP (Publication 103) risk models and Russian national medical statistics data. For populations under the age of 50 y, the risk estimates based on organ doses usually are 30% higher than estimates based on effective doses. In older populations, the difference can be up to a factor of 2.5. The typical distributions of organ doses were defined for Chest Routine, Abdominal Routine, and Head Routine examinations. The distributions of organ doses were dependent on the anatomical region of scanning. The most exposed organs/tissues were thyroid, breast, esophagus, and lungs in cases of Chest Routine examination; liver, stomach, colon, ovaries, and bladder in cases of Abdominal Routine examination; and brain for Head Routine examinations. The conversion factors for calculation of typical organ doses or tissues at risk using DLP were determined. Lifetime attributable risk of cancer estimated with organ doses calculated from DLP was compared with the risk estimated on the basis of organ doses measured with the use of silicon photodiode dosimeters. The estimated difference in LAR is less than 29%.
Estimating Counterfactual Risk Under Hypothetical Interventions in the Presence of Competing Events: Crystalline Silica Exposure and Mortality From two Causes of Death.

PubMed

Neophytou, Andreas M; Picciotto, Sally; Brown, Daniel M; Gallagher, Lisa E; Checkoway, Harvey; Eisen, Ellen A; Costello, Sadie

2018-04-03

Exposure to silica has been linked to excess risk of lung cancer and non-malignant respiratory disease mortality. In this study we estimated risk for both these outcomes in relation to occupational silica exposure as well as the reduction in risk that would result from hypothetical interventions on exposure in a cohort of exposed workers. Analyses were carried out in an all-male study population consisting of 2342 California diatomaceous earth workers regularly exposed to crystalline silica, followed between 1942 and 2011. We estimated subdistribution risk for each event under the natural course and interventions of interest using the parametric g-formula to adjust for healthy worker survivor bias. The risk ratio for lung cancer mortality comparing an intervention in which a theoretical maximum exposure limit was set at 0.05 mg/m3 (the current U.S. regulatory limit) to the observed exposure concentrations was 0.86 (95% confidence interval: 0.63, 1.22). The corresponding risk ratio for non-malignant respiratory disease mortality was 0.69 (95% confidence interval: 0.52, 0.93). Our findings suggest that risks from both outcomes would have been considerably lower if historical silica exposures in this cohort had not exceeded current regulatory limits.
Characterization and risk estimate of cancer in patients with primary Sjögren syndrome.

PubMed

Brito-Zerón, Pilar; Kostov, Belchin; Fraile, Guadalupe; Caravia-Durán, Daniel; Maure, Brenda; Rascón, Francisco-Javier; Zamora, Mónica; Casanovas, Arnau; Lopez-Dupla, Miguel; Ripoll, Mar; Pinilla, Blanca; Fonseca, Eva; Akasbi, Miriam; de la Red, Gloria; Duarte-Millán, Miguel-Angel; Fanlo, Patricia; Guisado-Vasco, Pablo; Pérez-Alvarez, Roberto; Chamorro, Antonio J; Morcillo, César; Jiménez-Heredia, Iratxe; Sánchez-Berná, Isabel; López-Guillermo, Armando; Ramos-Casals, Manuel

2017-04-17

The purpose of this study is to characterize the risk of cancer in a large cohort of patients with primary Sjögren syndrome (SjS). We had analyzed the development of cancer in 1300 consecutive patients fulfilling the 2002 SjS classification criteria. The baseline clinical and immunological characteristics and systemic activity (ESSDAI scores) were assessed at diagnosis as predictors of cancer using Cox proportional hazards regression analysis adjusted for age at diagnosis and gender. The sex-and age-specific standardized incidence ratios (SIR) of cancer were estimated from 2012 Spanish mortality data. After a mean follow-up of 91 months, 127 (9.8%) patients developed 133 cancers. The most frequent type of cancer was B-cell lymphoma (including 27 MALT and 19 non-MALT B-cell lymphomas). Systemic activity at diagnosis of primary SjS correlated with the risk of hematological neoplasia and cryoglobulins with a high risk of either B-cell or non-B-cell lymphoma subtypes. Patients with cytopenias had a high risk of non-MALT B-cell and non-B-cell cancer, while those with low C3 levels had a high risk of MALT lymphomas and those with monoclonal gammopathy and low C4 levels had a high risk of non-MALT lymphomas. The estimated SIR for solid cancer was 1.13 and 11.02 for hematological cancer. SIRs for specific cancers were 36.17 for multiple myeloma and immunoproliferative diseases, 19.41 for Hodgkin lymphoma, 6.04 for other non-Hodgkin lymphomas, 5.17 for thyroid cancer, 4.81 for cancers of the lip and oral cavity, and 2.53 for stomach cancer. One third of cancers developed by patients with primary SjS are B-cell lymphomas. The prognostic factors identified at SjS diagnosis differed according to the subtype of B-cell lymphoma developed. Primary SjS is also associated with the development of some non-hematological cancers (thyroid, oral cavity, and stomach).
One idea of portfolio risk control for absolute return strategy risk adjustments by signals from correlation behavior

NASA Astrophysics Data System (ADS)

Nishiyama, N.

2001-12-01

Absolute return strategy provided from fund of funds (FOFs) investment schemes is the focus in Japanese Financial Community. FOFs investment mainly consists of hedge fund investment and it has two major characteristics which are low correlation against benchmark index and little impact from various external changes in the environment given maximizing return. According to the historical track record of survival hedge funds in this business world, they maintain a stable high return and low risk. However, one must keep in mind that low risk would not be equal to risk free. The failure of Long-term capital management (LTCM) that took place in the summer of 1998 was a symbolized phenomenon. The summer of 1998 exhibited a certain limitation of traditional value at risk (VaR) and some possibility that traditional VaR could be ineffectual to the nonlinear type of fluctuation in the market. In this paper, I try to bring self-organized criticality (SOC) into portfolio risk control. SOC would be well known as a model of decay in the natural world. I analyzed nonlinear type of fluctuation in the market as SOC and applied SOC to capture complicated market movement using threshold point of SOC and risk adjustments by scenario correlation as implicit signals. Threshold becomes the control parameter of risk exposure to set downside floor and forecast extreme nonlinear type of fluctuation under a certain probability. Simulation results would show synergy effect of portfolio risk control between SOC and absolute return strategy.
The Pennsylvania Trauma Outcomes Study Risk-Adjusted Mortality Model: Results of a Statewide Benchmarking Program

PubMed Central

WIEBE, DOUGLAS J.; HOLENA, DANIEL N.; DELGADO, M. KIT; McWILLIAMS, NATHAN; ALTENBURG, JULIET; CARR, BRENDAN G.

2018-01-01

Trauma centers need objective feedback on performance to inform quality improvement efforts. The Trauma Quality Improvement Program recently published recommended methodology for case mix adjustment and benchmarking performance. We tested the feasibility of applying this methodology to develop risk-adjusted mortality models for a statewide trauma system. We performed a retrospective cohort study of patients ≥16 years old at Pennsylvania trauma centers from 2011 to 2013 (n = 100,278). Our main outcome measure was observed-to-expected mortality ratios (overall and within blunt, penetrating, multisystem, isolated head, and geriatric subgroups). Patient demographic variables, physiology, mechanism of injury, transfer status, injury severity, and pre-existing conditions were included as predictor variables. The statistical model had excellent discrimination (area under the curve = 0.94). Funnel plots of observed-to-expected identified five centers with lower than expected mortality and two centers with higher than expected mortality. No centers were outliers for management of penetrating trauma, but five centers had lower and three had higher than expected mortality for blunt trauma. It is feasible to use Trauma Quality Improvement Program methodology to develop risk-adjusted models for statewide trauma systems. Even with smaller numbers of trauma centers that are available in national datasets, it is possible to identify high and low outliers in performance. PMID:28541852
The Pennsylvania Trauma Outcomes Study Risk-Adjusted Mortality Model: Results of a Statewide Benchmarking Program.

PubMed

Wiebe, Douglas J; Holena, Daniel N; Delgado, M Kit; McWilliams, Nathan; Altenburg, Juliet; Carr, Brendan G

2017-05-01

Trauma centers need objective feedback on performance to inform quality improvement efforts. The Trauma Quality Improvement Program recently published recommended methodology for case mix adjustment and benchmarking performance. We tested the feasibility of applying this methodology to develop risk-adjusted mortality models for a statewide trauma system. We performed a retrospective cohort study of patients ≥16 years old at Pennsylvania trauma centers from 2011 to 2013 (n = 100,278). Our main outcome measure was observed-to-expected mortality ratios (overall and within blunt, penetrating, multisystem, isolated head, and geriatric subgroups). Patient demographic variables, physiology, mechanism of injury, transfer status, injury severity, and pre-existing conditions were included as predictor variables. The statistical model had excellent discrimination (area under the curve = 0.94). Funnel plots of observed-to-expected identified five centers with lower than expected mortality and two centers with higher than expected mortality. No centers were outliers for management of penetrating trauma, but five centers had lower and three had higher than expected mortality for blunt trauma. It is feasible to use Trauma Quality Improvement Program methodology to develop risk-adjusted models for statewide trauma systems. Even with smaller numbers of trauma centers that are available in national datasets, it is possible to identify high and low outliers in performance.
[Evaluation of the adjusted amino acid score by digestibility for estimating the protein quality and protein available in food and diets].

PubMed

Pak, N; Vera, G; Araya, H

1985-03-01

The purpose of the present study was to evaluate the amino acid score adjusted by digestibility to estimate protein quality and utilizable protein in foods and diets, considering net protein utilization (NPU) as a biological reference method. Ten foods of vegetable origin and ten of animal origin, as well as eight mixtures of foods of vegetable and animal origin were studied. When all the foods were considered, a positive (r = 0.83) and highly significant correlation (p less than 0.001) between NPU and the amino acid score adjusted by digestibility was found. When the foods were separated according to their origin, this correlation was positive only for the foods of vegetable origin (r = 0.93) and statistically significant (p less than 0.001). Also, only in those foods were similar values found between NPU and amino acid score adjusted by digestibility, as well as in utilizable protein estimated considering both methods. Caution is required to interpret protein quality and utilizable protein values of foods of animal origin and mixtures of foods of vegetable and animal origin when the amino acid score method adjusted by digestibility, or NPU, are utilized.
Spatio-temporal population estimates for risk management

NASA Astrophysics Data System (ADS)

Cockings, Samantha; Martin, David; Smith, Alan; Martin, Rebecca

2013-04-01

Accurate estimation of population at risk from hazards and effective emergency management of events require not just appropriate spatio-temporal modelling of hazards but also of population. While much recent effort has been focused on improving the modelling and predictions of hazards (both natural and anthropogenic), there has been little parallel advance in the measurement or modelling of population statistics. Different hazard types occur over diverse temporal cycles, are of varying duration and differ significantly in their spatial extent. Even events of the same hazard type, such as flood events, vary markedly in their spatial and temporal characteristics. Conceptually and pragmatically then, population estimates should also be available for similarly varying spatio-temporal scales. Routine population statistics derived from traditional censuses or surveys are usually static representations in both space and time, recording people at their place of usual residence on census/survey night and presenting data for administratively defined areas. Such representations effectively fix the scale of population estimates in both space and time, which is unhelpful for meaningful risk management. Over recent years, the Pop24/7 programme of research, based at the University of Southampton (UK), has developed a framework for spatio-temporal modelling of population, based on gridded population surfaces. Based on a data model which is fully flexible in terms of space and time, the framework allows population estimates to be produced for any time slice relevant to the data contained in the model. It is based around a set of origin and destination centroids, which have capacities, spatial extents and catchment areas, all of which can vary temporally, such as by time of day, day of week, season. A background layer, containing information on features such as transport networks and landuse, provides information on the likelihood of people being in certain places at specific times
Health-adjusted premium subsidies in the Netherlands.

PubMed

van de Ven, Wynand P M M; van Vliet, René C J A; Lamers, Leida M

2004-01-01

The Dutch government has decided to proceed with managed competition in health care. In this paper we report on progress made with health-based risk adjustment, a key issue in managed competition. In 2004 both Diagnostic Cost Groups (DCGs) computed from hospital diagnoses only and Pharmacy-based Cost Groups (PCGs) computed from out-patient prescription drugs are used to set the premium subsidies for competing risk-bearing sickness funds. These health-based risk adjusters appear to be effective and complementary. Risk selection is not a major problem in the Netherlands. Despite the progress made, we are still faced with a full research agenda for risk adjustment in the coming years.
Factors predicting high estimated 10-year stroke risk: thai epidemiologic stroke study.

PubMed

Hanchaiphiboolkul, Suchat; Puthkhao, Pimchanok; Towanabut, Somchai; Tantirittisak, Tasanee; Wangphonphatthanasiri, Khwanrat; Termglinchan, Thanes; Nidhinandana, Samart; Suwanwela, Nijasri Charnnarong; Poungvarin, Niphon

2014-08-01

The purpose of the study was to determine the factors predicting high estimated 10-year stroke risk based on a risk score, and among the risk factors comprising the risk score, which factors had a greater impact on the estimated risk. Thai Epidemiologic Stroke study was a community-based cohort study, which recruited participants from the general population from 5 regions of Thailand. Cross-sectional baseline data of 16,611 participants aged 45-69 years who had no history of stroke were included in this analysis. Multiple logistic regression analysis was used to identify the predictors of high estimated 10-year stroke risk based on the risk score of the Japan Public Health Center Study, which estimated the projected 10-year risk of incident stroke. Educational level, low personal income, occupation, geographic area, alcohol consumption, and hypercholesterolemia were significantly associated with high estimated 10-year stroke risk. Among these factors, unemployed/house work class had the highest odds ratio (OR, 3.75; 95% confidence interval [CI], 2.47-5.69) followed by illiterate class (OR, 2.30; 95% CI, 1.44-3.66). Among risk factors comprising the risk score, the greatest impact as a stroke risk factor corresponded to age, followed by male sex, diabetes mellitus, systolic blood pressure, and current smoking. Socioeconomic status, in particular, unemployed/house work and illiterate class, might be good proxy to identify the individuals at higher risk of stroke. The most powerful risk factors were older age, male sex, diabetes mellitus, systolic blood pressure, and current smoking. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Risk-adjusted sequential probability ratio tests: applications to Bristol, Shipman and adult cardiac surgery.

PubMed

Spiegelhalter, David; Grigg, Olivia; Kinsman, Robin; Treasure, Tom

2003-02-01

To investigate the use of the risk-adjusted sequential probability ratio test in monitoring the cumulative occurrence of adverse clinical outcomes. Retrospective analysis of three longitudinal datasets. Patients aged 65 years and over under the care of Harold Shipman between 1979 and 1997, patients under 1 year of age undergoing paediatric heart surgery in Bristol Royal Infirmary between 1984 and 1995, adult patients receiving cardiac surgery from a team of cardiac surgeons in London,UK. Annual and 30-day mortality rates. Using reasonable boundaries, the procedure could have indicated an 'alarm' in Bristol after publication of the 1991 Cardiac Surgical Register, and in 1985 or 1997 for Harold Shipman depending on the data source and the comparator. The cardiac surgeons showed no significant deviation from expected performance. The risk-adjusted sequential probability test is simple to implement, can be applied in a variety of contexts, and might have been useful to detect specific instances of past divergent performance. The use of this and related techniques deserves further attention in the context of prospectively monitoring adverse clinical outcomes.
Mobile Applications for Type 2 Diabetes Risk Estimation: a Systematic Review.

PubMed

Fijacko, Nino; Brzan, Petra Povalej; Stiglic, Gregor

2015-10-01

Screening for chronical diseases like type 2 diabetes can be done using different methods and various risk tests. This study present a review of type 2 diabetes risk estimation mobile applications focusing on their functionality and availability of information on the underlying risk calculators. Only 9 out of 31 reviewed mobile applications, featured in three major mobile application stores, disclosed the name of risk calculator used for assessing the risk of type 2 diabetes. Even more concerning, none of the reviewed applications mentioned that they are collecting the data from users to improve the performance of their risk estimation calculators or offer users the descriptive statistics of the results from users that already used the application. For that purpose the questionnaires used for calculation of risk should be upgraded by including the information on the most recent blood sugar level measurements from users. Although mobile applications represent a great future potential for health applications, developers still do not put enough emphasis on informing the user of the underlying methods used to estimate the risk for a specific clinical condition.
Consistently estimating absolute risk difference when translating evidence to jurisdictions of interest.

PubMed

Eckermann, Simon; Coory, Michael; Willan, Andrew R

2011-02-01

Economic analysis and assessment of net clinical benefit often requires estimation of absolute risk difference (ARD) for binary outcomes (e.g. survival, response, disease progression) given baseline epidemiological risk in a jurisdiction of interest and trial evidence of treatment effects. Typically, the assumption is made that relative treatment effects are constant across baseline risk, in which case relative risk (RR) or odds ratios (OR) could be applied to estimate ARD. The objective of this article is to establish whether such use of RR or OR allows consistent estimates of ARD. ARD is calculated from alternative framing of effects (e.g. mortality vs survival) applying standard methods for translating evidence with RR and OR. For RR, the RR is applied to baseline risk in the jurisdiction to estimate treatment risk; for OR, the baseline risk is converted to odds, the OR applied and the resulting treatment odds converted back to risk. ARD is shown to be consistently estimated with OR but changes with framing of effects using RR wherever there is a treatment effect and epidemiological risk differs from trial risk. Additionally, in indirect comparisons, ARD is shown to be consistently estimated with OR, while calculation with RR allows inconsistency, with alternative framing of effects in the direction, let alone the extent, of ARD. OR ensures consistent calculation of ARD in translating evidence from trial settings and across trials in direct and indirect comparisons, avoiding inconsistencies from RR with alternative outcome framing and associated biases. These findings are critical for consistently translating evidence to inform economic analysis and assessment of net clinical benefit, as translation of evidence is proposed precisely where the advantages of OR over RR arise.
Empirical estimation of present-day Antarctic glacial isostatic adjustment and ice mass change

NASA Astrophysics Data System (ADS)

Gunter, B. C.; Didova, O.; Riva, R. E. M.; Ligtenberg, S. R. M.; Lenaerts, J. T. M.; King, M. A.; van den Broeke, M. R.; Urban, T.

2014-04-01

This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating a firn densification model to account for firn compaction and surface processes as well as reprocessed data sets over a slightly longer period of time. A range of different Gravity Recovery and Climate Experiment (GRACE) gravity models were evaluated and a new Ice, Cloud, and Land Elevation Satellite (ICESat) surface height trend map computed using an overlapping footprint approach. When the GIA models created from the combination approach were compared to in situ GPS ground station displacements, the vertical rates estimated showed consistently better agreement than recent conventional GIA models. The new empirically derived GIA rates suggest the presence of strong uplift in the Amundsen Sea sector in West Antarctica (WA) and the Philippi/Denman sectors, as well as subsidence in large parts of East Antarctica (EA). The total GIA-related mass change estimates for the entire Antarctic ice sheet ranged from 53 to 103 Gt yr-1, depending on the GRACE solution used, with an estimated uncertainty of ±40 Gt yr-1. Over the time frame February 2003-October 2009, the corresponding ice mass change showed an average value of -100 ± 44 Gt yr-1 (EA: 5 ± 38, WA: -105 ± 22), consistent with other recent estimates in the literature, with regional mass loss mostly concentrated in WA. The refined approach presented in this study shows the contribution that such data combinations can make towards improving estimates of present-day GIA and ice mass change, particularly with respect to determining more reliable uncertainties.
Inclusion of Highest Glasgow Coma Scale Motor Component Score in Mortality Risk Adjustment for Benchmarking of Trauma Center Performance.

PubMed

Gomez, David; Byrne, James P; Alali, Aziz S; Xiong, Wei; Hoeft, Chris; Neal, Melanie; Subacius, Harris; Nathens, Avery B

2017-12-01

The Glasgow Coma Scale (GCS) is the most widely used measure of traumatic brain injury (TBI) severity. Currently, the arrival GCS motor component (mGCS) score is used in risk-adjustment models for external benchmarking of mortality. However, there is evidence that the highest mGCS score in the first 24 hours after injury might be a better predictor of death. Our objective was to evaluate the impact of including the highest mGCS score on the performance of risk-adjustment models and subsequent external benchmarking results. Data were derived from the Trauma Quality Improvement Program analytic dataset (January 2014 through March 2015) and were limited to the severe TBI cohort (16 years or older, isolated head injury, GCS ≤8). Risk-adjustment models were created that varied in the mGCS covariates only (initial score, highest score, or both initial and highest mGCS scores). Model performance and fit, as well as external benchmarking results, were compared. There were 6,553 patients with severe TBI across 231 trauma centers included. Initial and highest mGCS scores were different in 47% of patients (n = 3,097). Model performance and fit improved when both initial and highest mGCS scores were included, as evidenced by improved C-statistic, Akaike Information Criterion, and adjusted R-squared values. Three-quarters of centers changed their adjusted odds ratio decile, 2.6% of centers changed outlier status, and 45% of centers exhibited a ≥0.5-SD change in the odds ratio of death after including highest mGCS score in the model. This study supports the concept that additional clinical information has the potential to not only improve the performance of current risk-adjustment models, but can also have a meaningful impact on external benchmarking strategies. Highest mGCS score is a good potential candidate for inclusion in additional models. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
Estimating the Roles of Genetic Risk, Perinatal Risk, and Marital Hostility on Early Childhood Adjustment: Medical Records and Self-Reports

PubMed Central

Neiderhiser, Jenae M.; Marceau, Kristine; De Araujo-Greecher, Marielena; Ganiban, Jody M.; Mayes, Linda C.; Shaw, Daniel S.; Reiss, David; Leve, Leslie D.

2016-01-01

A wide variety of perinatal risk factors have been linked to later developmental outcomes in children. Much of this work has relied on either birth/medical records or mothers’ self-reports collected after delivery, and there has been an ongoing debate about which strategy provides the most accurate and reliable data. This report uses a parent-offspring adoption design (N = 561 families) to (1) examine the correspondence between medical record data and self-report data, (2) examine how perinatal risk factors may influence child internalizing and externalizing behavior at age 4.5 years, and (3) explore interactions among genetic, perinatal risk, and rearing environment on child internalizing and externalizing behavior during early childhood. The agreement of self-reports and medical records data was relatively high (51–100%), although there was some variation based on the construct. There were few main effects of perinatal risk on child outcomes; however, there were several 2- and 3-way interactions suggesting that the combined influences of genetic, perinatal, and rearing environmental risks are important, particularly for predicting whether children exhibit internalizing versus externalizing symptoms at age 4.5 years. PMID:27075497
The effect of accuracy motivation on anchoring and adjustment: do people adjust from provided anchors?

PubMed

Simmons, Joseph P; LeBoeuf, Robyn A; Nelson, Leif D

2010-12-01

Increasing accuracy motivation (e.g., by providing monetary incentives for accuracy) often fails to increase adjustment away from provided anchors, a result that has led researchers to conclude that people do not effortfully adjust away from such anchors. We challenge this conclusion. First, we show that people are typically uncertain about which way to adjust from provided anchors and that this uncertainty often causes people to believe that they have initially adjusted too far away from such anchors (Studies 1a and 1b). Then, we show that although accuracy motivation fails to increase the gap between anchors and final estimates when people are uncertain about the direction of adjustment, accuracy motivation does increase anchor-estimate gaps when people are certain about the direction of adjustment, and that this is true regardless of whether the anchors are provided or self-generated (Studies 2, 3a, 3b, and 5). These results suggest that people do effortfully adjust away from provided anchors but that uncertainty about the direction of adjustment makes that adjustment harder to detect than previously assumed. This conclusion has important theoretical implications, suggesting that currently emphasized distinctions between anchor types (self-generated vs. provided) are not fundamental and that ostensibly competing theories of anchoring (selective accessibility and anchoring-and-adjustment) are complementary. PsycINFO Database Record (c) 2010 APA, all rights reserved.
Assessing At-Risk Youth Using the Reynolds Adolescent Adjustment Screening Inventory with a Latino Population

ERIC Educational Resources Information Center

Balkin, Richard S.; Cavazos, Javier, Jr.; Hernandez, Arthur E.; Garcia, Roberto; Dominguez, Denise L.; Valarezo, Alexandra

2013-01-01

Factor analyses were conducted on scores from the Reynolds Adolescent Adjustment Screening Inventory (RAASI; Reynolds, 2001) representing at-risk Latino youth. The 4-factor model of the RAASI did not exhibit a good fit. However, evidence of generalizability for Latino youth was noted. (Contains 3 tables.)
Reconstruction of financial networks for robust estimation of systemic risk

NASA Astrophysics Data System (ADS)

Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo

2012-03-01

In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks.
The necessity of sociodemographic status adjustment in hospital value rankings for perforated appendicitis in children.

PubMed

Tian, Yao; Sweeney, John F; Wulkan, Mark L; Heiss, Kurt F; Raval, Mehul V

2016-06-01

Hospitals are increasingly focused on demonstration of high-value care for common surgical procedures. Although sociodemographic status (SDS) factors have been tied to various surgical outcomes, the impact of SDS factors on hospital value rankings has not been well explored. Our objective was to examine effects of SDS factors on high-value surgical care at the patient level, and to illustrate the importance of SDS adjustment when evaluating hospital-level performance. Perforated appendicitis hospitalizations were identified from the 2012 Kids' Inpatient Database. The primary outcome of interest was high-value care as defined by evaluation of duration of stay and cost. SDS factors included race, health insurance type, median household income, and patient location. The impact of SDS on high-value care was estimated using regression models after accounting for hospital-level variation. Risk-adjusted value rankings were compared before and after adjustment for SDS. From 9,986 hospitalizations, 998 high-value encounters were identified. African Americans were less likely to experience high-value care compared with white patients after adjusting for all SDS variables. Although private insurance and living in nonmetro counties were associated independently with high-value care, the effects were attenuated in the fully adjusted models. For the 136 hospitals ranked according to risk-adjusted value status, 59 hospitals' rankings improved after adjustment and 53 hospitals' rankings declined. After adjustment for patient and hospital factors, SDS has a small but significant impact on risk-adjusted hospital performance ranking for pediatric appendicitis. Adjustment for SDS should be considered in future comparative performance assessment. Copyright © 2016 Elsevier Inc. All rights reserved.

Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

PubMed

Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

2017-01-01

Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Comparison of risk estimates for selected diseases and causes of death.

PubMed

Merrill, R M; Kessler, L G; Udler, J M; Rasband, G C; Feuer, E J

1999-02-01

Lifetime risk estimates of disease are limited by long-term data extrapolations and are less relevant to individuals who have already lived a period of time without the disease, but are approaching the age at which the disease risk becomes common. In contrast, short-term age-conditional risk estimates, such as the risk of developing a disease in the next 10 years among those alive and free of the disease at a given age, are less restricted by long-term extrapolation of current rates and can present patients with risk information tailored to their age. This study focuses on short-term age-conditional risk estimates for a broad set of important chronic diseases and nondisease causes of death among white and black men and women. The Feuer et al. (1993, Journal of the National Cancer Institute) [15] method was applied to data from a variety of sources to obtain risk estimates for select cancers, myocardial infarction, diabetes mellitus, multiple sclerosis, Alzheimer's, and death from motor vehicle accidents, homicide or legal intervention, and suicide. Acute deaths from suicide, homicide or legal intervention, and fatal motor vehicle accidents dominate the risk picture for persons in their 20s, with only diabetes mellitus and end-stage renal disease therapy (for blacks only) having similar levels of risk in this age range. Late in life, cancer, acute myocardial infarction, Alzheimer's, and stroke become most common. The chronic diseases affecting the population later in life present the most likely diseases someone will face. Several interesting differences in disease and death risks were derived and reported among age-specific race and gender subgroups of the population. Presentation of risk estimates for a broad set of chronic diseases and nondisease causes of death within short-term age ranges among population subgroups provides tailored information that may lead to better educated prevention, screening, and control behaviors and more efficient allocation of health
Estimation of value at risk and conditional value at risk using normal mixture distributions model

NASA Astrophysics Data System (ADS)

Kamaruzzaman, Zetty Ain; Isa, Zaidi

2013-04-01

Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.
Comparative coronary risks of apixaban, rivaroxaban and dabigatran: a meta-analysis and adjusted indirect comparison

PubMed Central

Loke, Yoon K; Pradhan, Shiva; Yeong, Jessica Ka-yan; Kwok, Chun Shing

2014-01-01

Aims There are concerns regarding increased risk of acute coronary syndrome with dabigatran. We aimed to assess whether alternative treatment options such as rivaroxaban or apixaban carry a similar risk as compared with dabigatran. Methods We searched MEDLINE and EMBASE for randomized controlled trials of apixaban, dabigatran or rivaroxaban against control (placebo, heparin or vitamin K antagonist). We pooled odds ratios (OR) for adverse coronary events (acute coronary syndrome or myocardial infarction) using fixed effect meta-analysis and assessed heterogeneity with I2. We conducted adjusted indirect comparisons to compare risk of adverse coronary events with apixaban or rivaroxaban vs. dabigatran. Results Twenty-seven randomized controlled trials met the inclusion criteria. Dabigatran was associated with a significantly increased risk of adverse coronary events in pooled analysis of nine trials (OR 1.45, 95% CI 1.14, 1.86). There was no signal for coronary risk with apixaban from nine trials (pooled OR 0.89, 95% CI 0.78, 1.03) or rivaroxaban from nine trials (pooled OR 0.81, 95% CI 0.72, 0.93). Overall, adjusted indirect comparison suggested that both apixaban (OR 0.61, 95% CI 0.44, 0.85) and rivaroxaban (OR 0.54; 95% CI 0.39, 0.76) were associated with lower coronary risk than dabigatran. Restricting the indirect comparison to a vitamin K antagonist as a common control, yielded similar findings, OR 0.57 (95% CI 0.39, 0.85) for apixaban vs. dabigatran and 0.53 (95% CI 0.37, 0.77) for rivaroxaban vs. dabigatran. Conclusions There are significant differences in the comparative safety of apixaban, rivaroxaban and dabigatran with regards to acute coronary adverse events. PMID:24617578
Risk factors for UK Plasmodium falciparum cases.

PubMed

Pinsent, Amy; Read, Jonathan M; Griffin, Jamie T; Smith, Valerie; Gething, Peter W; Ghani, Azra C; Pasvol, Geoffrey; Hollingsworth, T Déirdre

2014-08-04

An increasing proportion of malaria cases diagnosed in UK residents with a history of travel to malaria endemic areas are due to Plasmodium falciparum. In order to identify travellers at most risk of acquiring malaria a proportional hazards model was used to estimate the risk of acquiring malaria stratified by purpose of travel and age whilst adjusting for entomological inoculation rate (EIR) and duration of stay in endemic countries. Travellers visiting friends and relatives and business travellers were found to have significantly higher hazard of acquiring malaria (adjusted hazard ratio (HR) relative to that of holiday makers 7.4, 95% CI 6.4-8.5, p < 0. 0001 and HR 3.4, 95% CI 2.9-3.8, p < 0. 0001, respectively). All age-groups were at lower risk than children aged 0-15 years. These estimates of the increased risk for business travellers and those visiting friends and relatives should be used to inform programmes to improve awareness of the risks of malaria when travelling.
Development of a risk-adjustment model for antimicrobial utilization data in 21 public hospitals in Queensland, Australia (2006-11).

PubMed

Rajmokan, M; Morton, A; Marquess, J; Playford, E G; Jones, M

2013-10-01

Making valid comparisons of antimicrobial utilization between hospitals requires risk adjustment for each hospital's case mix. Data on individual patients may be unavailable or difficult to process. Therefore, risk adjustment for antimicrobial usage frequently needs to be based on a hospital's services. This study evaluated such a strategy for hospital antimicrobial utilization. Data were obtained on five broad subclasses of antibiotics [carbapenems, β-lactam/β-lactamase inhibitor combinations (BLBLIs), fluoroquinolones, glycopeptides and third-generation cephalosporins] from the Queensland pharmacy database (MedTrx) for 21 acute public hospitals (2006-11). Eleven clinical services and a variable for hospitals from the tropical region were employed for risk adjustment. Multivariable regression models were used to identify risk and protective services for these antibiotics. Funnel plots were used to display hospitals' antimicrobial utilization. Total inpatient antibiotic utilization for these antibiotics increased from 130.6 defined daily doses (DDDs)/1000 patient-days in 2006 to 155.8 DDDs/1000 patient-days in 2011 (P < 0.0001). Except for third-generation cephalosporins, the average utilization rate was higher for intensive care, renal/nephrology, cardiac, burns/plastic surgery, neurosurgery, transplant and acute spinal services than for the respective reference group (no service). In addition, oncology, high-activity infectious disease and coronary care services were associated with higher utilization of carbapenems, BLBLIs and glycopeptides. Our model predicted antimicrobial utilization rates by hospital services. The funnel plots displayed hospital utilization data after adjustment for variation among the hospitals. However, the methodology needs to be validated in other populations, ideally using a larger group of hospitals.
Ryegrass cv. Lema and guava cv. Paluma biomonitoring suitability for estimating nutritional contamination risks under seasonal climate in Southeastern Brazil.

PubMed

Bulbovas, Patricia; Camargo, Carla Z S; Domingos, Marisa

2015-08-01

The risks posed by nutrient deposition due to air pollution on ecosystems and their respective services to human beings can be appropriately estimated by bioindicator plants when they are well acclimated to the study region environmental conditions. This assumption encouraged us to comparatively evaluate the accumulation potential of ryegrass cv. Lema and guava cv. Paluma macro and micronutrients. We also indicated the most appropriate species for biomonitoring nutrient contamination risks in tropical areas of Southeastern Brazil, which are characterized by marked dry and wet seasons and complex mixtures of air pollutants from different sources (industries, vehicle traffic and agriculture). The study was conducted in 14 sites with different neighboring land uses, within the Metropolitan Region of Campinas, central-eastern region of São Paulo State. The exposure experiments with ryegrass and guava were consecutively repeated 40 (28 days each) and 12 (84 days each) times, respectively, from Oct/2010 to Sept/2013. Macro and micronutrients were analyzed and background concentrations and enrichment ratios (ER) were estimated to classify the contamination risk within the study region. Significantly higher ER suggested that ryegrass were the most appropriate accumulator species for N, S, Mg, Fe, Mn, Cu and Zn deposition and guava for K, Ca, P and B deposition. Based on these biomonitoring adjustments, we concluded that the nutrient deposition was spatially homogeneous in the study area, but clear seasonality in the contamination risk by nutritional inputs was evidenced. Significantly higher contamination risk by S, Fe, K and B occurred during the dry season and enhanced contamination risk by Mn, Cu and Zn were highlighted during the wet season. Distinctly high contamination risk was estimated for S, Fe and Mn in several exposure experiments. Copyright © 2015 Elsevier Inc. All rights reserved.
Estimating Risk from Ambient Concentrations of Acrolein across the United States

PubMed Central

Woodruff, Tracey J.; Wells, Ellen M.; Holt, Elizabeth W.; Burgin, Deborah E.; Axelrad, Daniel A.

2007-01-01

Background Estimated ambient concentrations of acrolein, a hazardous air pollutant, are greater than the U.S. Environmental Protection Agency (EPA) reference concentration throughout the United States, making it a concern for human health. However, there is no method for assessing the extent of risk under the U.S. EPA noncancer risk assessment framework. Objectives We estimated excess risks from ambient concentrations of acrolein based on dose–response modeling of a study in rats with a relationship between acrolein and residual volume/total lung capacity ratio (RV/TLC) and specific compliance (sCL), markers for altered lung function. Methods Based on existing literature, we defined values above the 90th percentile for controls as “adverse.” We estimated the increase over baseline response that would occur in the human population from estimated ambient concentrations of acrolein, taken from the U.S. EPA’s National-Scale Air Toxics Assessment for 1999, after standard animal-to-human conversions and extrapolating to doses below the experimental data. Results The estimated median additional number of adverse sCL outcomes across the United States was approximately 2.5 cases per 1,000 people. The estimated range of additional outcomes from the 5th to the 95th percentile of acrolein concentration levels across census tracts was 0.28–14 cases per 1,000. For RV/TLC, the median additional outcome was 0.002 per 1,000, and the additional outcome at the 95th percentile was 0.13 per 1,000. Conclusions Although there are uncertainties in estimating human risks from animal data, this analysis demonstrates a method for estimating health risks for noncancer effects and suggests that acrolein could be associated with decreased respiratory function in the United States. PMID:17431491
Probability based models for estimation of wildfire risk

Treesearch

Haiganoush Preisler; D. R. Brillinger; R. E. Burgan; John Benoit

2004-01-01

We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 kmÂ²-day cell level. We fit a spatially and temporally explicit non-...
Value-at-Risk analysis using ARMAX GARCHX approach for estimating risk of banking subsector stock return’s

NASA Astrophysics Data System (ADS)

Dewi Ratih, Iis; Sutijo Supri Ulama, Brodjol; Prastuti, Mike

2018-03-01

Value at Risk (VaR) is one of the statistical methods used to measure market risk by estimating the worst losses in a given time period and level of confidence. The accuracy of this measuring tool is very important in determining the amount of capital that must be provided by the company to cope with possible losses. Because there is a greater losses to be faced with a certain degree of probability by the greater risk. Based on this, VaR calculation analysis is of particular concern to researchers and practitioners of the stock market to be developed, thus getting more accurate measurement estimates. In this research, risk analysis of stocks in four banking sub-sector, Bank Rakyat Indonesia, Bank Mandiri, Bank Central Asia and Bank Negara Indonesia will be done. Stock returns are expected to be influenced by exogenous variables, namely ICI and exchange rate. Therefore, in this research, stock risk estimation are done by using VaR ARMAX-GARCHX method. Calculating the VaR value with the ARMAX-GARCHX approach using window 500 gives more accurate results. Overall, Bank Central Asia is the only bank had the estimated maximum loss in the 5% quantile.
Communication of uncertainty regarding individualized cancer risk estimates: effects and influential factors.

PubMed

Han, Paul K J; Klein, William M P; Lehman, Tom; Killam, Bill; Massett, Holly; Freedman, Andrew N

2011-01-01

To examine the effects of communicating uncertainty regarding individualized colorectal cancer risk estimates and to identify factors that influence these effects. Two Web-based experiments were conducted, in which adults aged 40 years and older were provided with hypothetical individualized colorectal cancer risk estimates differing in the extent and representation of expressed uncertainty. The uncertainty consisted of imprecision (otherwise known as "ambiguity") of the risk estimates and was communicated using different representations of confidence intervals. Experiment 1 (n = 240) tested the effects of ambiguity (confidence interval v. point estimate) and representational format (textual v. visual) on cancer risk perceptions and worry. Potential effect modifiers, including personality type (optimism), numeracy, and the information's perceived credibility, were examined, along with the influence of communicating uncertainty on responses to comparative risk information. Experiment 2 (n = 135) tested enhanced representations of ambiguity that incorporated supplemental textual and visual depictions. Communicating uncertainty led to heightened cancer-related worry in participants, exemplifying the phenomenon of "ambiguity aversion." This effect was moderated by representational format and dispositional optimism; textual (v. visual) format and low (v. high) optimism were associated with greater ambiguity aversion. However, when enhanced representations were used to communicate uncertainty, textual and visual formats showed similar effects. Both the communication of uncertainty and use of the visual format diminished the influence of comparative risk information on risk perceptions. The communication of uncertainty regarding cancer risk estimates has complex effects, which include heightening cancer-related worry-consistent with ambiguity aversion-and diminishing the influence of comparative risk information on risk perceptions. These responses are influenced by
Estimating relative risks for common outcome using PROC NLP.

PubMed

Yu, Binbing; Wang, Zhuoqiao

2008-05-01

In cross-sectional or cohort studies with binary outcomes, it is biologically interpretable and of interest to estimate the relative risk or prevalence ratio, especially when the response rates are not rare. Several methods have been used to estimate the relative risk, among which the log-binomial models yield the maximum likelihood estimate (MLE) of the parameters. Because of restrictions on the parameter space, the log-binomial models often run into convergence problems. Some remedies, e.g., the Poisson and Cox regressions, have been proposed. However, these methods may give out-of-bound predicted response probabilities. In this paper, a new computation method using the SAS Nonlinear Programming (NLP) procedure is proposed to find the MLEs. The proposed NLP method was compared to the COPY method, a modified method to fit the log-binomial model. Issues in the implementation are discussed. For illustration, both methods were applied to data on the prevalence of microalbuminuria (micro-protein leakage into urine) for kidney disease patients from the Diabetes Control and Complications Trial. The sample SAS macro for calculating relative risk is provided in the appendix.
Pre-Bombing Population Density in Hiroshima and Nagasaki: Its Measurement and Impact on Radiation Risk Estimates in the Life Span Study of Atomic Bomb Survivors.

PubMed

French, Benjamin; Funamoto, Sachiyo; Sugiyama, Hiromi; Sakata, Ritsu; Cologne, John; Cullings, Harry M; Mabuchi, Kiyohiko; Preston, Dale L

2018-03-29

In the Life Span Study of atomic bomb survivors, differences in urbanicity between high-dose and low-dose survivors could confound the association between radiation dose and adverse outcomes. We obtained data on the pre-bombing population distribution in Hiroshima and Nagasaki, and quantified the impact of adjustment for population density on radiation risk estimates for mortality (1950-2003) and incident solid cancer (1958-2009). Population density ranged from 4,671-14,378 and 5,748-19,149 people/km2 in urban regions of Hiroshima and Nagasaki, respectively. Radiation risk estimates for solid cancer mortality were attenuated by 5.1%, but those for all-cause mortality and incident solid cancer were unchanged. There was no overall association between population density and adverse outcomes, but there was evidence that the association between density and mortality differed by age at exposure. Among survivors 10-14 years old in 1945, there was a positive association between population density and risk of all-cause mortality (relative risk, 1.053 per 5,000 people/km2 increase, 95% confidence interval: 1.027, 1.079) and solid cancer mortality (relative risk, 1.069 per 5,000 people/km2 increase, 95% confidence interval: 1.025, 1.115). Our results suggest that radiation risk estimates from the Life Span Study are not sensitive to unmeasured confounding by urban-rural differences.
R2 TRI facilities with 1999-2011 risk related estimates throughout the census blockgroup

EPA Pesticide Factsheets

This dataset delineates the distribution of estimate risk from the TRI facilities for 1999 - 2011 throughout the census blockgroup of the region using Office of Pollution, Prevention & Toxics (OPPT)'s Risk-Screening Environmental Indicators model (RSEI). The model uses the reported quantities of TRI releases of chemicals to estimate the impacts associated with each type of air release or transfer by every TRI facility.The RSEI was run to generate the estimate risk for each TRI facility in the region. The result from the model is joined to the TRI spatial data. Estimate risk values for each census block group were calculated based on the inverse distance of all the facilities which are within a 50 km radius of the census block group centroid. The estimate risk value for each census block group thus is an aggregated value that takes into account the estimate potential risk of all the facilities within the searching radius (50km).
Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality

PubMed Central

Matsushita, Kunihiro; Sang, Yingying; Ballew, Shoshana H; Appel, Lawrence J.; Arima, Hisatomi; Chadban, Steven J.; Cirillo, Massimo; Djurdjev, Ognjenka; Green, Jamie A; Heine, Gunnar H; Inker, Lesley A; Irie, Fujiko; Ishani, Areef; Ix, Joachim H.; Kovesdy, Csaba P.; Marks, Angharad; Ohkubo, Takayoshi; Shalev, Varda; Shankar, Anoop; Wen, Chi Pang; de Jong, Paul E.; Iseki, Kunitoshi; Stengel, Benedicte

2014-01-01

Importance The established chronic kidney disease (CKD) progression endpoint, end-stage renal disease (ESRD) or doubling of serum creatinine (corresponding to a change in estimated glomerular filtration rate (eGFR) of −57% or greater) is a late event, limiting feasibility of nephrology clinical trials. Objective To characterize the association of decline in eGFR with subsequent progression to ESRD, with implications for using lesser declines in eGFR as potential alternative endpoints for CKD progression. Since most people with CKD die before reaching ESRD, we also investigated mortality risk. Data Sources Individual meta-analysis of up to 1.7 million participants with 12,344 ESRD events and 223,944 deaths from 35 cohorts. Study Selection Cohorts in the CKD Prognosis Consortium with a repeated measure of serum creatinine over 1-3 years and outcome data. Data Extraction and Synthesis Transfer of individual participant data or standardized analysis of outputs for random effects meta-analysis took place between July 2012 and September 2013 with baseline eGFRs during 1975-2012. Main Outcomes and Measures ESRD (initiation of dialysis or transplantation) or all-cause mortality risk related to percent change in eGFR over 2 years adjusted for potential confounders and first eGFR. Results The adjusted hazard ratios (HR) of ESRD and mortality were exponentially higher with larger eGFR decline. Among participants with baseline eGFR <60 ml/min/1.73m2, the adjusted HRs for ESRD were 32.1 (95% CI 22.3-46.3) and 5.4 (4.5-6.4) for −57% and −30% eGFR changes, respectively. However, changes of −30% or greater were much more common than changes of −57% (6.9% (6.4-7.4%) vs. 0.79% (0.52-1.06%) in the whole consortium). This association was strong and consistent across length of baseline (1 or 3 years), baseline eGFR, age, diabetes status, or albuminuria. Average adjusted 10-year risk of ESRD for eGFR changes of −57%, −40%, −30% and 0% were 99% (95-100%), 83% (71-93%), 64
MEASUREMENT OF PERSONAL RISK BEHAVI-OR IN OCCUPATIONAL RISK STUDIES AMONG HEALTH CARE WORKERS.

PubMed

Butsashvili, M; Kamkamidze, G; Kajaia, M; Nelson, K; Triner, W; McNutt, L A

2018-01-01

Risky behaviours, particularly illegal and heavily stigmatized behaviours, are difficult to measure through self-report in both high risk groups and the general population. Underreporting can result in substantially biased estimates of non-injection drug use (IDU) risk of hepatitis C virus (HCV) infection. We hypothesized that asking about the existence of social networks injection drug use may be a useful marker of IDU. A cross-sectional survey of physicians and nurses was conducted in seven hospitals in Georgia. Based on survey responses participants were categorized into three IDU risk groups: ever used injecting drugs (Self IDU), reported a friend, family member or colleague used injecting drugs (Associate IDU), or reported neither (No IDU). Testing on anti-HCV was done using third generation ELISA methods. Both unadjusted and adjusted prevalence ratios between IDU risk groups and HCV prevalence were estimated. Of the 1312 (82.2%) participants, 10 (0.8%), 75 (5.7%), and 1227 (93.5%) were categorized as Self IDU, Associate IDU and No IDU, respectively; with HCV prevalence of 20%, 9.3% and 4.6%, respectively (p=0.016). The association was due primarily to women's reports. Those who reported some IDU risk were more likely to report other personal risk behaviors (e.g., multiple sex partners) and occupational risk behaviors (e.g., frequent exposure to blood and body fluids). This study represents a start of measurement development by assessing the potential usefulness of a marker to measure of IDU. Improved measurement of stigmatized behaviors is needed for confounding adjustment to improve estimates of occupational risks of blood-borne infections.
Estimation of risk of cancers before occurrence of acquired immunodeficiency syndrome in persons infected with human immunodeficiency virus.

PubMed

Li, Yueming; Law, Matthew; McDonald, Ann; Correll, Patty; Kaldor, John M; Grulich, Andrew E

2002-01-15

There is methodological debate as to whether cohorts defined by acquired immunodeficiency syndrome (AIDS) diagnosis can be used to estimate risks of cancer in persons with human immunodeficiency virus (HIV) before AIDS. The authors compared risks of non-AIDS-defining cancers before AIDS in persons with HIV using a cohort based on AIDS diagnosis and a second cohort based on HIV diagnosis. National population-based registries of AIDS and HIV diagnoses to August 1999 were matched separately with the National Cancer Registry in Australia. Four analyses were performed. In analysis 1, follow-up was from 5 years before AIDS registration in 8,118 persons with AIDS. Analysis 2 was similar but adjusted expected numbers of cancers for decreased survival. Analysis 3 was based on 7,061 persons registered with HIV, with follow-up from the reported date of diagnosis. Analysis 4 was based on 2,112 AIDS cases previously reported with HIV, with follow-up from 5 years before AIDS diagnosis. In all analyses, follow-up ended at cancer diagnosis, death, 6 months before AIDS, or the end of available cancer data, whichever occurred first. For 10 types of cancer there were at least three cases in any one of the analyses. For these cancers there was no systematic pattern such that one analysis produced consistently higher or lower estimates than the others. These analyses suggest that cancer risk in persons with HIV before AIDS diagnosis may be estimated reliably based on cancer experience 5 years before AIDS.
Toxoplasma gondii Infection in Kyrgyzstan: Seroprevalence, Risk Factor Analysis, and Estimate of Congenital and AIDS-Related Toxoplasmosis

PubMed Central

Bodosheva, Aigerim; Kuttubaev, Omurbek; Hehl, Adrian B.; Tanner, Isabelle; Ziadinov, Iskender; Torgerson, Paul R.; Deplazes, Peter

2013-01-01

Background HIV-prevalence, as well as incidence of zoonotic parasitic diseases like cystic echinococcosis, has increased in the Kyrgyz Republic due to fundamental socio-economic changes after the breakdown of the Soviet Union. The possible impact on morbidity and mortality caused by Toxoplasma gondii infection in congenital toxoplasmosis or as an opportunistic infection in the emerging AIDS pandemic has not been reported from Kyrgyzstan. Methodology/Principal Findings We screened 1,061 rural and 899 urban people to determine the seroprevalence of T. gondii infection in 2 representative but epidemiologically distinct populations in Kyrgyzstan. The rural population was from a typical agricultural district where sheep husbandry is a major occupation. The urban population was selected in collaboration with several diagnostic laboratories in Bishkek, the largest city in Kyrgyzstan. We designed a questionnaire that was used on all rural subjects so a risk-factor analysis could be undertaken. The samples from the urban population were anonymous and only data with regard to age and gender was available. Estimates of putative cases of congenital and AIDS-related toxoplasmosis in the whole country were made from the results of the serology. Specific antibodies (IgG) against Triton X-100 extracted antigens of T. gondii tachyzoites from in vitro cultures were determined by ELISA. Overall seroprevalence of infection with T. gondii in people living in rural vs. urban areas was 6.2% (95%CI: 4.8–7.8) (adjusted seroprevalence based on census figures 5.1%, 95% CI 3.9–6.5), and 19.0% (95%CI: 16.5–21.7) (adjusted 16.4%, 95% CI 14.1–19.3), respectively, without significant gender-specific differences. The seroprevalence increased with age. Independently low social status increased the risk of Toxoplasma seropositivity while increasing numbers of sheep owned decreased the risk of seropositivity. Water supply, consumption of unpasteurized milk products or undercooked meat, as
Estimating relative risks in multicenter studies with a small number of centers - which methods to use? A simulation study.

PubMed

Pedroza, Claudia; Truong, Van Thi Thanh

2017-11-02

Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios. We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions. All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs. For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors.
Vascular disease, ESRD, and death: interpreting competing risk analyses.

PubMed

Grams, Morgan E; Coresh, Josef; Segev, Dorry L; Kucirka, Lauren M; Tighiouart, Hocine; Sarnak, Mark J

2012-10-01

Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989-1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20-2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15-2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors.

Evaluation and adjustment of altimeter measurement and numerical hindcast in wave height trend estimation in China's coastal seas

NASA Astrophysics Data System (ADS)

Li, Shuiqing; Guan, Shoude; Hou, Yijun; Liu, Yahao; Bi, Fan

2018-05-01

A long-term trend of significant wave height (SWH) in China's coastal seas was examined based on three datasets derived from satellite measurements and numerical hindcasts. One set of altimeter data were obtained from the GlobWave, while the other two datasets of numerical hindcasts were obtained from the third-generation wind wave model, WAVEWATCH III, forced by wind fields from the Cross-Calibrated Multi-Platform (CCMP) and NCEP's Climate Forecast System Reanalysis (CFSR). The mean and extreme wave trends were estimated for the period 1992-2010 with respect to the annual mean and the 99th-percentile values of SWH, respectively. The altimeter wave trend estimates feature considerable uncertainties owing to the sparse sampling rate. Furthermore, the extreme wave trend tends to be overestimated because of the increasing sampling rate over time. Numerical wave trends strongly depend on the quality of the wind fields, as the CCMP waves significantly overestimate the wave trend, whereas the CFSR waves tend to underestimate the trend. Corresponding adjustments were applied which effectively improved the trend estimates from the altimeter and numerical data. The adjusted results show generally increasing mean wave trends, while the extreme wave trends are more spatially-varied, from decreasing trends prevailing in the South China Sea to significant increasing trends mainly in the East China Sea.
Space Radiation Heart Disease Risk Estimates for Lunar and Mars Missions

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Chappell, Lori; Kim, Myung-Hee

2010-01-01

The NASA Space Radiation Program performs research on the risks of late effects from space radiation for cancer, neurological disorders, cataracts, and heart disease. For mortality risks, an aggregate over all risks should be considered as well as projection of the life loss per radiation induced death. We report on a triple detriment life-table approach to combine cancer and heart disease risks. Epidemiology results show extensive heterogeneity between populations for distinct components of the overall heart disease risks including hypertension, ischaemic heart disease, stroke, and cerebrovascular diseases. We report on an update to our previous heart disease estimates for Heart disease (ICD9 390-429) and Stroke (ICD9 430-438), and other sub-groups using recent meta-analysis results for various exposed radiation cohorts to low LET radiation. Results for multiplicative and additive risk transfer models are considered using baseline rates for US males and female. Uncertainty analysis indicated heart mortality risks as low as zero, assuming a threshold dose for deterministic effects, and projections approaching one-third of the overall cancer risk. Medan life-loss per death estimates were significantly less than that of solid cancer and leukemias. Critical research questions to improve risks estimates for heart disease are distinctions in mechanisms at high doses (>2 Gy) and low to moderate doses (<2 Gy), and data and basic understanding of radiation doserate and quality effects, and individual sensitivity.
Estimated risks and optimistic self-perception of breast cancer risk in Korean women.

PubMed

Chung, ChaeWeon; Lee, Suk Jeong

2013-11-01

To determine women's perceived personal and comparative risks of breast cancer, and to examine the relationships with risk factors. Despite the increasing incidence of breast cancer in younger women and the availability of screening, women's health behaviors have not advanced accordingly. A cross-sectional survey design utilized a convenience sample of 222 women in their 30s and 40s recruited from community settings in Seoul. Self-administered questionnaire data were analyzed by descriptive statistics, the chi-squared test, and ANOVA. Risk perception levels differed significantly by breast cancer risk factors. Half of the women were optimistic about their breast cancer risk, while perceived personal risk did not reflect women's own risk factors and comparative risk differed only by the practice of clinical breast exam. Women's knowledge and awareness of their breast cancer risk factors need to be improved for appropriate risk perception and health behaviors, and accurate risk estimation could be utilized to educate them in clinical settings. © 2013.
Competing risk bias was common in Kaplan-Meier risk estimates published in prominent medical journals.

PubMed

van Walraven, Carl; McAlister, Finlay A

2016-01-01

Risk estimates from Kaplan-Meier curves are well known to medical researchers, reviewers, and editors. In this study, we determined the proportion of Kaplan-Meier analyses published in prominent medical journals that are potentially biased because of competing events ("competing risk bias"). We randomly selected 100 studies that had at least one Kaplan-Meier analysis and were recently published in prominent medical journals. Susceptibility to competing risk bias was determined by examining the outcome and potential competing events. In susceptible studies, bias was quantified using a previously validated prediction model when the number of outcomes and competing events were given. Forty-six studies (46%) contained Kaplan-Meier analyses susceptible to competing risk bias. Sixteen studies (34.8%) susceptible to competing risk cited the number of outcomes and competing events; in six of these studies (6/16, 37.5%), the outcome risk from the Kaplan-Meier estimate (relative to the true risk) was biased upward by 10% or more. Almost half of Kaplan-Meier analyses published in medical journals are susceptible to competing risk bias and may overestimate event risk. This bias was found to be quantitatively important in a third of such studies. Copyright © 2016 Elsevier Inc. All rights reserved.
The Impact of Ecological Risk and Perceived Discrimination on the Psychological Adjustment of African American and European American Youth

ERIC Educational Resources Information Center

Prelow, Hazel M.; Danoff-Burg, Sharon; Swenson, Rebecca R.; Pulgiano, Dana

2004-01-01

The purpose of the present study was to examine the role of cumulative ecological risk (i.e., neighborhood disadvantage and ecologically salient stressful events) and perceived discrimination on the psychological adjustment of urban African American and European American youth. Findings indicated that both cumulative ecological risk and perceived…
The Role Behavioral Adjustment Plays in Placing Middle School Students "At Risk" of Academic Failure.

ERIC Educational Resources Information Center

Flynn, Timothy M.

The role of behavioral adjustment in placing middle school students at risk academically is examined using 23 middle school teachers' and 378 parents' ratings of 389 children (53 percent blacks and 47 percent whites) on Conner's Parent Rating Scale and Conner's Teacher Rating Scale. The average rating on the scales for both sets of ratings is…
Using the Violence Risk Scale-Sexual Offense version in sexual violence risk assessments: Updated risk categories and recidivism estimates from a multisite sample of treated sexual offenders.

PubMed

Olver, Mark E; Mundt, James C; Thornton, David; Beggs Christofferson, Sarah M; Kingston, Drew A; Sowden, Justina N; Nicholaichuk, Terry P; Gordon, Audrey; Wong, Stephen C P

2018-04-30

The present study sought to develop updated risk categories and recidivism estimates for the Violence Risk Scale-Sexual Offense version (VRS-SO; Wong, Olver, Nicholaichuk, & Gordon, 2003-2017), a sexual offender risk assessment and treatment planning tool. The overarching purpose was to increase the clarity and accuracy of communicating risk assessment information that includes a systematic incorporation of new information (i.e., change) to modify risk estimates. Four treated samples of sexual offenders with VRS-SO pretreatment, posttreatment, and Static-99R ratings were combined with a minimum follow-up period of 10-years postrelease (N = 913). Logistic regression was used to model 5- and 10-year sexual and violent (including sexual) recidivism estimates across 6 different regression models employing specific risk and change score information from the VRS-SO and/or Static-99R. A rationale is presented for clinical applications of select models and the necessity of controlling for baseline risk when utilizing change information across repeated assessments. Information concerning relative risk (percentiles) and absolute risk (recidivism estimates) is integrated with common risk assessment language guidelines to generate new risk categories for the VRS-SO. Guidelines for model selection and forensic clinical application of the risk estimates are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Contemporary group estimates adjusted for climatic effects provide a finer definition of the unknown environmental challenges experienced by growing pigs.

PubMed

Guy, S Z Y; Li, L; Thomson, P C; Hermesch, S

2017-12-01

Environmental descriptors derived from mean performances of contemporary groups (CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia (n = 31,230). Firstly, CG estimates of average daily gain (ADG) and backfat (BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model (p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a
Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence.

PubMed

Evers, Eric G; Bouwknegt, Martijn

2016-10-01

The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose-infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion. © 2016 Society for Risk Analysis.
Alternative Payment Models Should Risk-Adjust for Conversion Total Hip Arthroplasty: A Propensity Score-Matched Study.

PubMed

McLawhorn, Alexander S; Schairer, William W; Schwarzkopf, Ran; Halsey, David A; Iorio, Richard; Padgett, Douglas E

2017-12-06

For Medicare beneficiaries, hospital reimbursement for nonrevision hip arthroplasty is anchored to either diagnosis-related group code 469 or 470. Under alternative payment models, reimbursement for care episodes is not further risk-adjusted. This study's purpose was to compare outcomes of primary total hip arthroplasty (THA) vs conversion THA to explore the rationale for risk adjustment for conversion procedures. All primary and conversion THAs from 2007 to 2014, excluding acute hip fractures and cancer patients, were identified in the National Surgical Quality Improvement Program database. Conversion and primary THA patients were matched 1:1 using propensity scores, based on preoperative covariates. Multivariable logistic regressions evaluated associations between conversion THA and 30-day outcomes. A total of 2018 conversions were matched to 2018 primaries. There were no differences in preoperative covariates. Conversions had longer operative times (148 vs 95 minutes, P < .001), more transfusions (37% vs 17%, P < .001), and longer length of stay (4.4 vs 3.1 days, P < .001). Conversion THA had increased odds of complications (odds ratio [OR] 1.75; 95% confidence interval [CI] 1.37-2.24), deep infection (OR 4.21; 95% CI 1.72-10.28), discharge to inpatient care (OR 1.52; 95% CI 1.34-1.72), and death (OR 2.39; 95% CI 1.04-5.47). Readmission odds were similar. Compared with primary THA, conversion THA is associated with more complications, longer length of stay, and increased discharge to continued inpatient care, implying greater resource utilization for conversion patients. As reimbursement models shift toward bundled payment paradigms, conversion THA appears to be a procedure for which risk adjustment is appropriate. Copyright © 2017 Elsevier Inc. All rights reserved.
Estimating contribution of anthocyanin pigments to osmotic adjustment during winter leaf reddening.

PubMed

Hughes, Nicole M; Carpenter, Kaylyn L; Cannon, Jonathan G

2013-01-15

The association between plant water stress and synthesis of red, anthocyanin pigments in leaves has led some plant biologists to propose an osmotic function of leaf reddening. According to this hypothesis, anthocyanins function as a solute in osmotic adjustment (OA), contributing to depression of osmotic potential (Ψ(π)) and maintenance of turgor pressure during drought-stressed conditions. Here we calculate the percent contribution of anthocyanin to leaf Ψ(π) during OA in two angiosperm evergreen species, Galax urceolata and Gaultheria procumbens. Both species exhibit dramatic leaf reddening under high light during winter, concomitant with declines in leaf water potential and accumulation of solutes. Data previously published by the authors on osmotic potential at full turgor (Ψ(π,100)) of G. urceolata and G. procumbens leaves before and after leaf reddening were used to estimate OA. In vivo molar concentrations of anthocyanin, glucose, fructose, and sucrose measured from the same individuals were converted to pressure equivalents using the Ideal Gas Law, and percent contribution to OA was estimated. Estimated mean OA during winter was -0.7MPa for G. urceolata and -0.8MPa for G. procumbens. In vivo concentrations of anthocyanin (3-10mM) were estimated to account for ∼2% of OA during winter, and comprised <0.7% of Ψ(π,100) in both species. Glucose, fructose, and sucrose combined accounted for roughly 50 and 80% of OA for G. urceolata and G. procumbens, respectively, and comprised ∼20% of Ψ(π,100). We observed that a co-occurring, acyanic species (Vinca minor) achieved similar OA without synthesizing anthocyanin. We conclude that anthocyanins represent a measurable, albeit meager, component of OA in red-leafed evergreen species during winter. However, due to their low concentrations, metabolic costliness relative to other osmolytes, and striking red color (unnecessary for an osmotic function), it is unlikely that they are synthesized solely for an
REFAME: Rain Estimation Using Forward Adjusted-Advection of Microwave Estimates

NASA Technical Reports Server (NTRS)

Behrangi, Ali; Imam, Bisher; Hsu, Kuolin; Sorooshian, Soroosh; Bellerby, Timothy J.

2009-01-01

Sensors flying on satellites provide the only practical means of estimating the precipitation that falls over the entire globe, particularly across the vast unpopulated expanses of Earth s oceans. The sensors that observe the Earth using microwave frequencies provide the best data, but currently these are mounted only on satellites flying in "low Earth orbit". Such satellites constantly move across the Earth s surface, providing snapshots of any given location every 12-36 hours. The entire constellation of low-orbit satellites numbers less than a dozen, and their orbits are not coordinated, so a location will frequently go two or more hours between snapshots. "Geosynchronous Earth orbit" (GEO) satellites continuously observe the same region of the globe, allowing them to provide very frequent pictures. For example, the "satellite movies" shown on television come from GEO satellites. However, the sensors available on GEO satellites cannot match the skill of the low-orbit microwave sensors in estimating precipitation. It is perhaps obvious that scientists should try to combine these very different kinds of data, taking advantage of the strengths of each, but this simple concept has proved to be a huge challenge. The scheme in this paper is "Lagrangian", meaning we follow the storm systems, rather than being tied to a fixed grid of boxes on the Earth s surface. Whenever a microwave snapshot occurs, we gladly use the resulting precipitation estimate. Then at all the times between the microwave snapshots we force the storm system to make a smooth transition from one snapshot s values to the next. We know that a lot more changes occur between the snapshots, but this smooth transition the best we can do with the microwave data alone. The key new contribution in this paper is that we also look at the relative variations in the GEO estimates during these in-between times and force the estimated changes in the precipitation to have similar variations. Preliminary testing
Risk factors for UK Plasmodium falciparum cases

PubMed Central

2014-01-01

Background An increasing proportion of malaria cases diagnosed in UK residents with a history of travel to malaria endemic areas are due to Plasmodium falciparum. Methods In order to identify travellers at most risk of acquiring malaria a proportional hazards model was used to estimate the risk of acquiring malaria stratified by purpose of travel and age whilst adjusting for entomological inoculation rate (EIR) and duration of stay in endemic countries. Results Travellers visiting friends and relatives and business travellers were found to have significantly higher hazard of acquiring malaria (adjusted hazard ratio (HR) relative to that of holiday makers 7.4, 95% CI 6.4–8.5, p < 0. 0001 and HR 3.4, 95% CI 2.9-3.8, p < 0. 0001, respectively). All age-groups were at lower risk than children aged 0–15 years. Conclusions These estimates of the increased risk for business travellers and those visiting friends and relatives should be used to inform programmes to improve awareness of the risks of malaria when travelling. PMID:25091803
Uncertainties in estimating health risks associated with exposure to ionising radiation.

PubMed

Preston, R Julian; Boice, John D; Brill, A Bertrand; Chakraborty, Ranajit; Conolly, Rory; Hoffman, F Owen; Hornung, Richard W; Kocher, David C; Land, Charles E; Shore, Roy E; Woloschak, Gayle E

2013-09-01

The information for the present discussion on the uncertainties associated with estimation of radiation risks and probability of disease causation was assembled for the recently published NCRP Report No. 171 on this topic. This memorandum provides a timely overview of the topic, given that quantitative uncertainty analysis is the state of the art in health risk assessment and given its potential importance to developments in radiation protection. Over the past decade the increasing volume of epidemiology data and the supporting radiobiology findings have aided in the reduction of uncertainty in the risk estimates derived. However, it is equally apparent that there remain significant uncertainties related to dose assessment, low dose and low dose-rate extrapolation approaches (e.g. the selection of an appropriate dose and dose-rate effectiveness factor), the biological effectiveness where considerations of the health effects of high-LET and lower-energy low-LET radiations are required and the transfer of risks from a population for which health effects data are available to one for which such data are not available. The impact of radiation on human health has focused in recent years on cancer, although there has been a decided increase in the data for noncancer effects together with more reliable estimates of the risk following radiation exposure, even at relatively low doses (notably for cataracts and cardiovascular disease). New approaches for the estimation of hereditary risk have been developed with the use of human data whenever feasible, although the current estimates of heritable radiation effects still are based on mouse data because of an absence of effects in human studies. Uncertainties associated with estimation of these different types of health effects are discussed in a qualitative and semi-quantitative manner as appropriate. The way forward would seem to require additional epidemiological studies, especially studies of low dose and low dose
Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

PubMed

Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Dimick, Justin B; Wang, Edward; Chow, Warren B; Ko, Clifford Y; Bilimoria, Karl Y

2012-05-01

The measurement of hospital quality based on outcomes requires risk adjustment. The c-statistic is a popular tool used to judge model performance, but can be limited, particularly when evaluating specific operations in focused populations. Our objectives were to examine the interpretation and relevance of the c-statistic when used in models with increasingly similar case mix and to consider an alternative perspective on model calibration based on a graphical depiction of model fit. From the American College of Surgeons National Surgical Quality Improvement Program (2008-2009), patients were identified who underwent a general surgery procedure, and procedure groups were increasingly restricted: colorectal-all, colorectal-elective cases only, and colorectal-elective cancer cases only. Mortality and serious morbidity outcomes were evaluated using logistic regression-based risk adjustment, and model c-statistics and calibration curves were used to compare model performance. During the study period, 323,427 general, 47,605 colorectal-all, 39,860 colorectal-elective, and 21,680 colorectal cancer patients were studied. Mortality ranged from 1.0% in general surgery to 4.1% in the colorectal-all group, and serious morbidity ranged from 3.9% in general surgery to 12.4% in the colorectal-all procedural group. As case mix was restricted, c-statistics progressively declined from the general to the colorectal cancer surgery cohorts for both mortality and serious morbidity (mortality: 0.949 to 0.866; serious morbidity: 0.861 to 0.668). Calibration was evaluated graphically by examining predicted vs observed number of events over risk deciles. For both mortality and serious morbidity, there was no qualitative difference in calibration identified between the procedure groups. In the present study, we demonstrate how the c-statistic can become less informative and, in certain circumstances, can lead to incorrect model-based conclusions, as case mix is restricted and patients become
[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

PubMed

Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

2017-03-10

To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.
Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs.

PubMed

Mealing, Nicole M; Banks, Emily; Jorm, Louisa R; Steel, David G; Clements, Mark S; Rogers, Kris D

2010-04-01

There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%). Logistic regression analysis of questionnaire data from 45 and Up Study participants (n = 101,812) and 2006/2007 PHS participants (n = 14,796) was used to calculate prevalence estimates and odds ratios (ORs) for comparable variables, adjusting for age, sex and remoteness. ORs were compared using Wald tests modelling each study separately, with and without sampling weights. Prevalence of some outcomes (smoking, private health insurance, diabetes, hypertension, asthma) varied between the two studies. For highly comparable questionnaire items, exposure-outcome relationship patterns were almost identical between the studies and ORs for eight of the ten relationships examined did not differ significantly. For questionnaire items that were only moderately comparable, the nature of the observed relationships did not differ materially between the two studies, although many ORs differed significantly. These findings show that for a broad range of risk factors, two studies of the same population with varying response rate, sampling frame and mode of questionnaire administration yielded consistent estimates of exposure-outcome relationships. However, ORs varied between the studies where they did not use identical questionnaire items.
Estimating risk reduction required to break even in a health promotion program.

PubMed

Ozminkowski, Ronald J; Goetzel, Ron Z; Santoro, Jan; Saenz, Betty-Jo; Eley, Christine; Gorsky, Bob

2004-01-01

To illustrate a formula to estimate the amount of risk reduction required to break even on a corporate health promotion program. A case study design was implemented. Base year (2001) health risk and medical expenditure data from the company, along with published information on the relationships between employee demographics, health risks, and medical expenditures, were used to forecast demographics, risks, and expenditures for 2002 through 2011 and estimate the required amount of risk reduction. Motorola. 52,124 domestic employees. Demographics included age, gender, race, and job type. Health risks for 2001 were measured via health risk appraisal. Risks were noted as either high or low and related to exercise/eating habits, body weight, blood pressure, blood sugar levels, cholesterol levels, depression, stress, smoking/drinking habits, and seat belt use. Medical claims for 2001 were used to calculate medical expenditures per employee. Assuming a dollar 282 per employee program cost, Motorola employees would need to reduce their lifestyle-related health risks by 1.08% to 1.42% per year to break even on health promotion programming, depending upon the discount rate. Higher or lower program investments would change the risk reduction percentages. Employers can use information from published studies, along with their own data, to estimate the amount of risk reduction required to break even on their health promotion programs.
Haloacetic acids in drinking water and risk for stillbirth

PubMed Central

King, W; Dodds, L; Allen, A; Armson, B; Fell, D; Nimrod, C

2005-01-01

Aims: To investigate the effects of haloacetic acid (HAA) compounds in drinking water on stillbirth risk. Methods: A population based case-control study was conducted in Nova Scotia and Eastern Ontario, Canada. Estimates of daily exposure to total and specific HAAs were based on household water samples and questionnaire information on water consumption at home and work. Results: The analysis included 112 stillbirth cases and 398 live birth controls. In analysis without adjustment for total THM exposure, a relative risk greater than 2 was observed for an intermediate exposure category for total HAA and dichloroacetic acid measures. After adjustment for total THM exposure, the risk estimates for intermediate exposure categories were diminished, the relative risk associated with the highest category was in the direction of a protective effect, and all confidence intervals included the null value. Conclusions: No association was observed between HAA exposures and stillbirth risk after controlling for THM exposures. PMID:15657195
Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?

PubMed

Hey, Spencer Phillips; Kimmelman, Jonathan

2016-10-01

Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach - forecast analysis - that would enable direct and effective measure of the quality of risk/benefit estimation. We then consider some objections and limitations to the forecasting approach. © 2016 John Wiley & Sons Ltd.

Vascular Disease, ESRD, and Death: Interpreting Competing Risk Analyses

PubMed Central

Coresh, Josef; Segev, Dorry L.; Kucirka, Lauren M.; Tighiouart, Hocine; Sarnak, Mark J.

2012-01-01

Summary Background and objectives Vascular disease, a common condition in CKD, is a risk factor for mortality and ESRD. Optimal patient care requires accurate estimation and ordering of these competing risks. Design, setting, participants, & measurements This is a prospective cohort study of screened (n=885) and randomized participants (n=837) in the Modification of Diet in Renal Disease study (original study enrollment, 1989–1992), evaluating the association of vascular disease with ESRD and pre-ESRD mortality using standard survival analysis and competing risk regression. Results The method of analysis resulted in markedly different estimates. Cumulative incidence by standard analysis (censoring at the competing event) implied that, with vascular disease, the 15-year incidence was 66% and 51% for ESRD and pre-ESRD death, respectively. A more accurate representation of absolute risk was estimated with competing risk regression: 15-year incidence was 54% and 29% for ESRD and pre-ESRD death, respectively. For the association of vascular disease with pre-ESRD death, estimates of relative risk by the two methods were similar (standard survival analysis adjusted hazard ratio, 1.63; 95% confidence interval, 1.20–2.20; competing risk regression adjusted subhazard ratio, 1.57; 95% confidence interval, 1.15–2.14). In contrast, the hazard and subhazard ratios differed substantially for other associations, such as GFR and pre-ESRD mortality. Conclusions When competing events exist, absolute risk is better estimated using competing risk regression, but etiologic associations by this method must be carefully interpreted. The presence of vascular disease in CKD decreases the likelihood of survival to ESRD, independent of age and other risk factors. PMID:22859747
Cancer-related risk indicators and preventive screening behaviors among lesbians and bisexual women.

PubMed Central

Cochran, S D; Mays, V M; Bowen, D; Gage, S; Bybee, D; Roberts, S J; Goldstein, R S; Robison, A; Rankow, E J; White, J

2001-01-01

OBJECTIVES: This study examined whether lesbians are at increased risk for certain cancers as a result of an accumulation of behavioral risk factors and difficulties in accessing health care. METHODS: Prevalence estimates of behavioral risk factors (nulliparity, obesity, smoking, and alcohol use), cancer screening behaviors, and self-reported breast cancer histories derived from 7 independently conducted surveys of lesbians/bisexual women (n = 11,876) were compared with national estimates for women. RESULTS: In comparison with adjusted estimates for the US female population, lesbians/bisexual women exhibited greater prevalence rates of obesity, alcohol use, and tobacco use and lower rates of parity and birth control pill use. These women were also less likely to have health insurance coverage or to have had a recent pelvic examination or mammogram. Self-reported histories of breast cancer, however, did not differ from adjusted US female population estimates. CONCLUSIONS: Lesbians and bisexual women differ from heterosexual women in patterns of health risk. These women would be expected to be at especially greater risk for chronic diseases linked to smoking and obesity. PMID:11291371
Methods to Develop Inhalation Cancer Risk Estimates for ...

EPA Pesticide Factsheets

This document summarizes the approaches and rationale for the technical and scientific considerations used to derive inhalation cancer risks for emissions of chromium and nickel compounds from electric utility steam generating units. The purpose of this document is to discuss the methods used to develop inhalation cancer risk estimates associated with emissions of chromium and nickel compounds from coal- and oil-fired electric utility steam generating units (EGUs) in support of EPA's recently proposed Air Toxics Rule.
Diesel exhaust exposure and bladder cancer risk.

PubMed

Iyer, V; Harris, R E; Wynder, E L

1990-03-01

A total of 136 cases of men with urinary bladder cancer and 272 matched hospital controls were examined for potential exposure to diesel exhaust. A lifetime occupational history was obtained for all subjects in the study and assessment of exposure to diesel exhaust was based on the job titles of the subject and self-reported exposure. The risk was assessed by odds ratios, with adjustment for confounding variables, in particular cigarette smoking. There was no evidence of elevated risk in occupations with possible or probable exposure (the ORs adjusted for smoking were 1.1. and 0.9 respectively). Truck driving alone was also not associated with elevated risk (adjusted OR = 0.5). There was a weak positive crude association with any exposure, including self-reports (OR = 1.4); however after adjustment for smoking, the estimate did not retain statistical significance (OR = 1.2, 95% CI = 0.8-2.0). This study provides little to support the hypothesis of an excess of bladder cancer risk from occupational exposure to diesel exhaust.
Comparison of the performance of the CMS Hierarchical Condition Category (CMS-HCC) risk adjuster with the Charlson and Elixhauser comorbidity measures in predicting mortality.

PubMed

Li, Pengxiang; Kim, Michelle M; Doshi, Jalpa A

2010-08-20

The Centers for Medicare and Medicaid Services (CMS) has implemented the CMS-Hierarchical Condition Category (CMS-HCC) model to risk adjust Medicare capitation payments. This study intends to assess the performance of the CMS-HCC risk adjustment method and to compare it to the Charlson and Elixhauser comorbidity measures in predicting in-hospital and six-month mortality in Medicare beneficiaries. The study used the 2005-2006 Chronic Condition Data Warehouse (CCW) 5% Medicare files. The primary study sample included all community-dwelling fee-for-service Medicare beneficiaries with a hospital admission between January 1st, 2006 and June 30th, 2006. Additionally, four disease-specific samples consisting of subgroups of patients with principal diagnoses of congestive heart failure (CHF), stroke, diabetes mellitus (DM), and acute myocardial infarction (AMI) were also selected. Four analytic files were generated for each sample by extracting inpatient and/or outpatient claims for each patient. Logistic regressions were used to compare the methods. Model performance was assessed using the c-statistic, the Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and their 95% confidence intervals estimated using bootstrapping. The CMS-HCC had statistically significant higher c-statistic and lower AIC and BIC values than the Charlson and Elixhauser methods in predicting in-hospital and six-month mortality across all samples in analytic files that included claims from the index hospitalization. Exclusion of claims for the index hospitalization generally led to drops in model performance across all methods with the highest drops for the CMS-HCC method. However, the CMS-HCC still performed as well or better than the other two methods. The CMS-HCC method demonstrated better performance relative to the Charlson and Elixhauser methods in predicting in-hospital and six-month mortality. The CMS-HCC model is preferred over the Charlson and Elixhauser methods
Estimating high-risk cannabis and opiate use in Ankara, Istanbul and Izmir.

PubMed

Kraus, Ludwig; Hay, Gordon; Richardson, Clive; Yargic, Ilhan; Ilhan, Mustafa Necmi; Ay, Pinar; Karasahin, Füsun; Pinarci, Mustafa; Tuncoglu, Tolga; Piontek, Daniela; Schulte, Bernd

2017-09-01

Information on high-risk drug use in Turkey, particularly at the regional level, is lacking. The present analysis aims at estimating high-risk cannabis use (HRCU) and high-risk opiate use (HROU) in the cities of Ankara, Istanbul and Izmir. Capture-recapture and multiplier methods were applied based on treatment and police data stratified by age and gender in the years 2009 and 2010. Case definitions refer to ICD-10 cannabis (F.12) and opiate (F.11) disorder diagnoses from outpatient and inpatient treatment records and illegal possession of these drugs as recorded by the police. High-risk cannabis use was estimated at 28 500 (8.5 per 1000; 95% confidence interval 7.3-10.3) and 33 400 (11.9 per 1000; 95% confidence interval 10.7-13.5) in Ankara and Izmir, respectively. Using multipliers based on capture-recapture estimates for Izmir, HRCU in Istanbul was estimated up to 166 000 (18.0 per 1000; range: 2.8-18.0). Capture-recapture estimates of HROU resulted in 4800 (1.4 per 1000; 95% confidence interval 0.9-1.9) in Ankara and multipliers based on these gave estimates up to 20 000 (2.2 per 1000; range: 0.9-2.2) in Istanbul. HROU in Izmir was not estimated due to the low absolute numbers of opiate users. While HRCU prevalence in both Ankara and Izmir was considerably lower in comparison to an estimate for Berlin, the rate for Istanbul was only slightly lower. Compared with the majority of European cities, HROU in these three Turkish cities may be considered rather low. [Kraus L, Hay G, Richardson C, Yargic I, Ilhan N M, Ay P, Karasahin F, Pinarci M, Tuncoglu T, Piontek D, Schulte B Estimating high-risk cannabis and opiate use in Ankara, Istanbul and Izmir Drug Alcohol Rev 2016;00:000-000]. © 2016 Australasian Professional Society on Alcohol and other Drugs.
Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes.

PubMed

Petersen, Laura A; Pietz, Kenneth; Woodard, LeChauncy D; Byrne, Margaret

2005-01-01

Many possible methods of risk adjustment exist, but there is a dearth of comparative data on their performance. We compared the predictive validity of 2 widely used methods (Diagnostic Cost Groups [DCGs] and Adjusted Clinical Groups [ACGs]) for 2 clinical outcomes using a large national sample of patients. We studied all patients who used Veterans Health Administration (VA) medical services in fiscal year (FY) 2001 (n = 3,069,168) and assigned both a DCG and an ACG to each. We used logistic regression analyses to compare predictive ability for death or long-term care (LTC) hospitalization for age/gender models, DCG models, and ACG models. We also assessed the effect of adding age to the DCG and ACG models. Patients in the highest DCG categories, indicating higher severity of illness, were more likely to die or to require LTC hospitalization. Surprisingly, the age/gender model predicted death slightly more accurately than the ACG model (c-statistic of 0.710 versus 0.700, respectively). The addition of age to the ACG model improved the c-statistic to 0.768. The highest c-statistic for prediction of death was obtained with a DCG/age model (0.830). The lowest c-statistics were obtained for age/gender models for LTC hospitalization (c-statistic 0.593). The c-statistic for use of ACGs to predict LTC hospitalization was 0.783, and improved to 0.792 with the addition of age. The c-statistics for use of DCGs and DCG/age to predict LTC hospitalization were 0.885 and 0.890, respectively, indicating the best prediction. We found that risk adjusters based upon diagnoses predicted an increased likelihood of death or LTC hospitalization, exhibiting good predictive validity. In this comparative analysis using VA data, DCG models were generally superior to ACG models in predicting clinical outcomes, although ACG model performance was enhanced by the addition of age.
Estimation of the Forest Fire Risk in Indonesia based on Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Suzuki, H.; Takahashi, Y.; Hashimoto, A.; Akita, M.; Hasegawa, Y.; Ogino, Y.; Naruse, N.; Takahashi, Y.

2016-12-01

To minimize forest fires in tropical area is extremely important, because the fire has a large impact on global warming, biodiversity, and human society. In the previous study, Shimada and Ishibashi monitored the ground-water lever from the value of Normalized Difference Vegetation Index (NDVI) obtained in Kalimantan Island to predict where the forest fires will happen. We have developed a method to map the forest fire risk by calculating the value of Modified Soil Adjusted Vegetation Index 2 (MSAVI2). Moreover, we investigated the relation between the distance from a road as an artificial factor and the occurrence of the fire.First, calculating the MSAVI2 from Landsat 7 and 8 images of August, 2015 around Martapura in South Sumatra, Indonesia, we mapped the area where the plants were stressed. Next, we checked the degrees of matching between the area of low MSAVI2 and the forest fire points.As a result, half of the fires happened in the area having the MSAVI2 values of 0.20 to 0.35. When we focused on only the area which is over 5 kilometers far from a road, the degrees of matching became higher; it rose up to 62 percent.Those results indicate that the fire risks relate to the dry area calculated as low MSAVI2 in the case with less human activities. We need to consider an effect of artificial factors to estimate the whole risk of forest fire.In conclusion, the map of forest fire risk by calculating the value of MSAVI2 is applicable to an area with less artificial factor, while we have to take the effect of artificial fire factor into the consideration.
Risk factors for chronic undernutrition among children in India: Estimating relative importance, population attributable risk and fractions.

PubMed

Corsi, Daniel J; Mejía-Guevara, Iván; Subramanian, S V

2016-05-01

Nearly 40% of the world's stunted children live in India and the prevalence of undernutrition has been persistently high in recent decades. Given numerous available interventions for reducing undernutrition in children, it is not clear of the relative importance of each within a multifactorial framework. We assess the simultaneous contribution of 15 known risk factors for child chronic undernutrition in India. Data are from the 3rd Indian National Family Health Survey (NFHS-3), a nationally representative cross-sectional survey undertaken in 2005-2006. The study population consisted of children aged 6-59 months [n = 26,842 (stunting/low height-for-age), n = 27,483 (underweight/low weight-for-age)]. Risk factors examined for their association with undernutrition were: vitamin A supplementation, vaccination, use of iodized salt, household air quality, improved sanitary facilities, safe disposal of stools, improved drinking water, prevalence of infectious disease, initiation of breastfeeding, dietary diversity, age at marriage, maternal BMI, height, education, and household wealth. Age/sex-adjusted and multivariable adjusted effect sizes (odds ratios) were calculated for risk factors along with Population Attributable Risks (PAR) and Fractions (PAF) using logistic regression. In the mutually adjusted models, the five most important predictors of childhood stunting/underweight were short maternal stature, mother having no education, households in lowest wealth quintile, poor dietary diversity, and maternal underweight. These five factors had a combined PAR of 67.2% (95% CI: 63.3-70.7) and 69.7% (95% CI: 66.3-72.8) for stunting and underweight, respectively. The remaining factors were associated with a combined PAR of 11.7% (95% CI: 6.0-17.4) and 15.1% (95% CI: 8.9-21.3) for stunting and underweight, respectively. Implementing strategies focused on broader progress on social circumstances and infrastructural domains as well as investments in nutrition specific
Bleeding injuries in professional football: estimating the risk for HIV transmission.

PubMed

Brown, L S; Drotman, D P; Chu, A; Brown, C L; Knowlan, D

1995-02-15

To determine the risk for bleeding injuries in professional football and to estimate the risk for transmission of the human immunodeficiency virus (HIV) through such injuries. A prospective, observational study. Professional football players from 11 teams of the National Football League were observed during 155 regular season games from September through December 1992. The frequencies of bleeding injuries were calculated in association with environmental and athletic factors. Using this information, HIV prevalence, and data on transmission of HIV in other circumstances, the risk for transmission of HIV during football games was estimated. 575 bleeding injuries (average, 3.7 per game for each team) involving 538 players (average, 3.5 players on each team per game) were observed. Approximately 88% of the bleeding injuries were abrasions; the remainder were lacerations. Bleeding injuries were markedly more frequent during games played on artificial surfaces, during games played in domed stadiums, and on teams with a final win/loss percentage of 0.500 or lower. Using data on the prevalence of HIV among college men and rates of HIV transmission in the health care setting, the risk for HIV transmission to each player was estimated to be less than 1 per 85 million game contacts. Although injuries occur in professional football competitions, bleeding injuries, especially lacerations, occur infrequently. We estimate that the risk for HIV transmission during such competition is extremely remote. The role of artificial playing surfaces on the incidence or severity of bleeding injuries should be investigated.
The 2006 William Feinberg lecture: shifting the paradigm from stroke to global vascular risk estimation.

PubMed

Sacco, Ralph L

2007-06-01

By the year 2010, it is estimated that 18.1 million people worldwide will die annually because of cardiovascular diseases and stroke. "Global vascular risk" more broadly includes the multiple overlapping disease silos of stroke, myocardial infarction, peripheral arterial disease, and vascular death. Estimation of global vascular risk requires consideration of a variety of variables including demographics, environmental behaviors, and risk factors. Data from multiple studies suggest continuous linear relationships between the physiological vascular risk modulators of blood pressure, lipids, and blood glucose rather than treating these conditions as categorical risk factors. Constellations of risk factors may be more relevant than individual categorical components. Exciting work with novel risk factors may also have predictive value in estimates of global vascular risk. Advances in imaging have led to the measurement of subclinical conditions such as carotid intima-media thickness and subclinical brain conditions such as white matter hyperintensities and silent infarcts. These subclinical measurements may be intermediate stages in the transition from asymptomatic to symptomatic vascular events, appear to be associated with the fundamental vascular risk factors, and represent opportunities to more precisely quantitate disease progression. The expansion of studies in molecular epidemiology and detection of genetic markers underlying vascular risks also promises to extend our precision of global vascular risk estimation. Global vascular risk estimation will require quantitative methods that bundle these multi-dimensional data into more precise estimates of future risk. The power of genetic information coupled with data on demographics, risk-inducing behaviors, vascular risk modulators, biomarkers, and measures of subclinical conditions should provide the most realistic approximation of an individual's future global vascular risk. The ultimate public health benefit
Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.
The Boehringer Ingelheim employee study (Part 2): 10-year cardiovascular diseases risk estimation.

PubMed

Kempf, K; Martin, S; Döhring, C; Dugi, K; Haastert, B; Schneider, M

2016-10-01

Cardiovascular disease (CVD) may cause an economic burden to companies, but CVD risk estimations specific to working populations are lacking. To estimate the 10-year CVD risk in the Boehringer Ingelheim (BI) employee cohort and analyse the potential effect of hypothetical risk reduction interventions. We estimated CVD risk using the Framingham (FRS), PROCAM (PRS) and Reynolds (RRS) risk scores, using cross-sectional baseline data on BI Pharma employees collected from 2005 to 2011. Results were compared using Fisher's exact and Wilcoxon tests. The predictive ability of the score estimates was assessed using receiver-operating characteristics analyses. Among the 4005 study subjects, we estimated 10-year CVD risks of 35% (FRS), 9% (PRS) and 6% (RRS) for men and 10% (FRS), 4% (PRS) and 1% (RRS) for women. One hundred and thirty-four (6%) men and 111 (6%) women employees had current CVD. The best predictors of prevalent CVD were the FRS and the RRS for men [area-under-the-curve 0.62 (0.57-0.67) for both]. A hypothetical intervention that would improve systolic blood pressure, HbA1c (for diabetes), C-reactive protein, triglycerides and total and high-density lipoprotein cholesterol by 10% each would potentially reduce expected CVD cases by 36-41% in men and 30-45% in women, and if smoking cessation is incorporated, by 39-45% and 30-55%, respectively, depending on the pre-intervention risk score. There was a substantial risk of developing CVD in this working cohort. Occupational health programmes with lifestyle interventions for high-risk individuals may be an effective risk reduction measure. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Estimated GFR and Risk of Hip Fracture in Older Men: Comparison of Associations Using Cystatin C and Creatinine

PubMed Central

Ensrud, Kristine E.; Parimi, Neeta; Fink, Howard A.; Ishani, Areef; Taylor, Brent C.; Steffes, Michael; Cauley, Jane A.; Lewis, Cora E.; Orwoll, Eric S.

2013-01-01

Background Higher serum cystatin C is associated with an increased risk of hip fracture in postmenopausal white women, but there is a paucity of data in men. Whether an estimated GFR (eGFR) based on cystatin C (eGFRcys) is superior in predicting hip fracture risk to an eGFR based on creatinine (eGFRcr) or the combination (eGFRcr-cys) is also uncertain. Study Design Nested case-cohort. Setting & Participants Participants enrolled in the Osteoporotic Fractures in Men (MrOS) Study (5,994 men aged ≥65 years from six U.S. centers) including a random subcohort of 1602 men and 168 men with incident hip fractures (51 of whom were in the subcohort). Predictor eGFRcys, eGFRcr and eGFRcr-cys computed using the CKD-EPI equations and expressed in categories of <60, 60–74, and ≥75 mL/min/l.73 m2 (referent group). Outcome Incident hip fracture ascertained by participant contacts every 4 months and confirmed with radiographic reports. Results Median eGFRcys was 72.9 (IQR, 60.5–85.7) mL/min/1.73 m2. In unadjusted models, all measures of eGFR were associated with increased hip fracture risk. However, after adjustment for age, race, site and BMI, the association of lower eGFRcys (but not lower eGFRcr or lower eGFRcr-cys) with higher hip fracture risk remained: for <60 vs. ≥75 mL/min/l.73 m2, HRs were 1.96 [95% CI, 1.25–3.09], 0.84 [95% CI, 0.52–1.37], and 1.08 [95% CI, 0.66–1.77] for eGFRcys, eGFRcr, and eGFRcr-cys, respectively. Similarly, after adjustment for age, race, site and BMI, eGFR of <60 ml/min/1.73 m2 defined by eGFRcys but not eGFRcr or eGFRcr-cys, was associated with higher hip fracture risk. The association between eGFRcys and hip fracture was not explained by levels of calcitropic hormones or inflammatory markers, but the relationship was attenuated and no longer reached significance (for <60 vs. ≥75 mL/min/l.73 m2: HR, 1.43; 95% CI, 0.88–2.34) after consideration of additional clinical risk factors and bone mineral density. Limitations Findings not
Bedside risk estimation of morbidly adherent placenta using simple calculator.

PubMed

Maymon, R; Melcer, Y; Pekar-Zlotin, M; Shaked, O; Cuckle, H; Tovbin, J

2018-03-01

To construct a calculator for 'bedside' estimation of morbidly adherent placenta (MAP) risk based on ultrasound (US) findings. This retrospective study included all pregnant women with at least one previous cesarean delivery attending in our US unit between December 2013 and January 2017. The examination was based on a scoring system which determines the probability for MAP. The study population included 471 pregnant women, and 41 of whom (8.7%) were diagnosed with MAP. Based on ROC curve, the most effective US criteria for detection of MAP were the presence of the placental lacunae, obliteration of the utero-placental demarcation, and placenta previa. On the multivariate logistic regression analysis, US findings of placental lacunae (OR = 3.5; 95% CI, 1.2-9.5; P = 0.01), obliteration of the utero-placental demarcation (OR = 12.4; 95% CI, 3.7-41.6; P < 0.0001), and placenta previa (OR = 10.5; 95% CI, 3.5-31.3; P < 0.0001) were associated with MAP. By combining these three parameters, the receiver operating characteristic curve was calculated, yielding an area under the curve of 0.93 (95% CI, 0.87-0.97). Accordingly, we have constructed a simple calculator for 'bedside' estimation of MAP risk. The calculator is mounted on the hospital's internet website ( http://www.assafh.org/Pages/PPCalc/index.html ). The risk estimation of MAP varies between 1.5 and 87%. The present calculator enables a simple 'bedside' MAP estimation, facilitating accurate and adequate antenatal risk assessment.
Corrigendum: direct adjustment for confounding by smoking reduces radiation-related cancer risk estimates of mortality among male nuclear workers in Japan, 1999-2010.

PubMed

Kudo, Shin'ichi; Ishida, Jun'ichi; Yoshimoto, Keiko; Mizuno, Shoichi; Ohshima, Sumio; Furuta, Hiroshige; Kasagi, Fumiyoshi

2018-05-30

We found some trivial errors which might confuse reader. The errors can be identified as the following two types. (1) The one is that misuse of "ERR" and "ERR/Sv". We denoted "Table 4 shows ERRs/Sv and 90% CIs ..." in line 7 of page 366. While we denoted "ERR and 90% CI for all cancers, excluding leukaemia, by dose category ..." in title of Table 4. The values described in Table 4 were ERR by dose category and not ERR/Sv. In addition, the explanation about the model that derived ERR by dose category is better to be added. Therefore, the description mentioned above should be changed as follows. (Misprinted) Table 4 shows ERRs/Sv and 90% CIs for all cancers excluding leukaemia by dose category. (Corrected) Table 4 shows ERRs which were defined as follow equation and 90% CIs for all cancers excluding leukaemia by dose category. λ=λ0 (a,c,y,r,s)exp(α1z1+α2z2+α3z3) (1+βi di) where di is the dose category, and βi is the ERR by dose category. The lowest dose category was set as reference. (2) The other were errors in surface caput of several tables. We described "ERR without adjustment for smoking" and "ERR with adjustment for smoking" in Table 4. These are correct description. However, "ERR with adjustment for smoking" was described as "For smoking" in Table 2. In addition, "Without adjustment" and "With adjustment" denoted in the surface caput of Table 5, 6, 7 should be denoted as "Without adjustment for smoking" and "With adjustment for smoking". The author wishes to apologies for the errors. . Creative Commons Attribution license.
Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide—An Overview

PubMed Central

Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete

2017-01-01

People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during admission. Most studies are based on low power, thus compromising quality and generalisability. The few studies with sufficient statistical power mainly identified non-modifiable risk predictors such as male gender, diagnosis, or recent deliberate self-harm. Also, the predictive value of these predictors is low. It would be of great benefit if future studies would be based on large samples while focusing on modifiable predictors over the course of an admission, such as hopelessness, depressive symptoms, and family/social situations. This would improve our chances of developing better risk assessment tools. PMID:28257103
A regression-adjusted approach can estimate competing biomass

Treesearch

James H. Miller

1983-01-01

A method is presented for estimating above-ground herbaceous and woody biomass on competition research plots. On a set of destructively-sampled plots, an ocular estimate of biomass by vegetative component is first made, after which vegetation is clipped, dried, and weighed. Linear regressions are then calculated for each component between estimated and actual weights...
Adjusting HIV prevalence estimates for non-participation: an application to demographic surveillance

PubMed Central

McGovern, Mark E.; Marra, Giampiero; Radice, Rosalba; Canning, David; Newell, Marie-Louise; Bärnighausen, Till

2015-01-01

Introduction HIV testing is a cornerstone of efforts to combat the HIV epidemic, and testing conducted as part of surveillance provides invaluable data on the spread of infection and the effectiveness of campaigns to reduce the transmission of HIV. However, participation in HIV testing can be low, and if respondents systematically select not to be tested because they know or suspect they are HIV positive (and fear disclosure), standard approaches to deal with missing data will fail to remove selection bias. We implemented Heckman-type selection models, which can be used to adjust for missing data that are not missing at random, and established the extent of selection bias in a population-based HIV survey in an HIV hyperendemic community in rural South Africa. Methods We used data from a population-based HIV survey carried out in 2009 in rural KwaZulu-Natal, South Africa. In this survey, 5565 women (35%) and 2567 men (27%) provided blood for an HIV test. We accounted for missing data using interviewer identity as a selection variable which predicted consent to HIV testing but was unlikely to be independently associated with HIV status. Our approach involved using this selection variable to examine the HIV status of residents who would ordinarily refuse to test, except that they were allocated a persuasive interviewer. Our copula model allows for flexibility when modelling the dependence structure between HIV survey participation and HIV status. Results For women, our selection model generated an HIV prevalence estimate of 33% (95% CI 27–40) for all people eligible to consent to HIV testing in the survey. This estimate is higher than the estimate of 24% generated when only information from respondents who participated in testing is used in the analysis, and the estimate of 27% when imputation analysis is used to predict missing data on HIV status. For men, we found an HIV prevalence of 25% (95% CI 15–35) using the selection model, compared to 16% among those who
Psychological impact of providing women with personalised 10-year breast cancer risk estimates.

PubMed

French, David P; Southworth, Jake; Howell, Anthony; Harvie, Michelle; Stavrinos, Paula; Watterson, Donna; Sampson, Sarah; Evans, D Gareth; Donnelly, Louise S

2018-05-08

The Predicting Risk of Cancer at Screening (PROCAS) study estimated 10-year breast cancer risk for 53,596 women attending NHS Breast Screening Programme. The present study, nested within the PROCAS study, aimed to assess the psychological impact of receiving breast cancer risk estimates, based on: (a) the Tyrer-Cuzick (T-C) algorithm including breast density or (b) T-C including breast density plus single-nucleotide polymorphisms (SNPs), versus (c) comparison women awaiting results. A sample of 2138 women from the PROCAS study was stratified by testing groups: T-C only, T-C(+SNPs) and comparison women; and by 10-year risk estimates received: 'moderate' (5-7.99%), 'average' (2-4.99%) or 'below average' (<1.99%) risk. Postal questionnaires were returned by 765 (36%) women. Overall state anxiety and cancer worry were low, and similar for women in T-C only and T-C(+SNPs) groups. Women in both T-C only and T-C(+SNPs) groups showed lower-state anxiety but slightly higher cancer worry than comparison women awaiting results. Risk information had no consistent effects on intentions to change behaviour. Most women were satisfied with information provided. There was considerable variation in understanding. No major harms of providing women with 10-year breast cancer risk estimates were detected. Research to establish the feasibility of risk-stratified breast screening is warranted.

[Applying temporally-adjusted land use regression models to estimate ambient air pollution exposure during pregnancy].

PubMed

Zhang, Y J; Xue, F X; Bai, Z P

2017-03-06

The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression (LUR) models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.
National and subnational mortality and disability-adjusted life years (DALYs) attributable to 17 occupational risk factors in Iran, 1990-2015.

PubMed

Abtahi, Mehrnoosh; Koolivand, Ali; Dobaradaran, Sina; Yaghmaeian, Kamyar; Khaloo, Shokooh Sadat; Jorfi, Sahand; Keshmiri, Saeed; Nafez, Amir Hossein; Saeedi, Reza

2018-04-26

We estimated age-sex specific and cause-specific mortality, years of life lost due to premature mortality (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) attributable to 17 individual occupational risks in Iran at the national and subnational levels in 1990-2015 based on the Global Burden of Disease Study 2015 (GBD 2015). The burden of disease attributable to occupational risk factors was calculated using the comparative risk assessment methodology based on 10 outcomes and 21 risk-outcome pairs. The temporal changes in the attributable burden of disease were decomposed into the contribution of population growth, population ageing, risk-deleted DALY rate, and risk exposure. National DALYs attributable to occupational risks at the national level in 1990, 2005, and 2015 were 138,210 (95% uncertainty interval 64,429-223,028), 193,243 (91,645-310,281), and 228,310 (106,782-371,709), respectively indicating a total increase of 65% (65-67) during the study period. Between 1990 and 2015, the share of the attributable DALYs for women rose by 55% (51-58) from 13% (12-14) to 20% (19-21). The proportion of YLLs in national DALYs attributable to occupational risks during the study period slightly decreased from 24% in 1990 to 23% in 2015. The five occupational risks with the highest contributions in the national attributable DALYs in 2015 were ergonomic factors (107,490), noise (52,122), exposure to particulate matter, gases, and fumes (26,847), asthmagens (19,347), and exposure to asbestos (7842). From 1990 to 2015, the increase in total DALYs attributable to occupational carcinogens (112%) was higher than that for other occupational risks. During the study period, changes in risk deleted DALY rate and risk exposure led to decreases in total DALYs attributable to occupational risks by 14% and 30%, respectively. Based on the Gini coefficient, spatial inequality in DALY rate attributable to occupational risks at the provincial level
Estimation model of life insurance claims risk for cancer patients by using Bayesian method

NASA Astrophysics Data System (ADS)

Sukono; Suyudi, M.; Islamiyati, F.; Supian, S.

2017-01-01

This paper discussed the estimation model of the risk of life insurance claims for cancer patients using Bayesian method. To estimate the risk of the claim, the insurance participant data is grouped into two: the number of policies issued and the number of claims incurred. Model estimation is done using a Bayesian approach method. Further, the estimator model was used to estimate the risk value of life insurance claims each age group for each sex. The estimation results indicate that a large risk premium for insured males aged less than 30 years is 0.85; for ages 30 to 40 years is 3:58; for ages 41 to 50 years is 1.71; for ages 51 to 60 years is 2.96; and for those aged over 60 years is 7.82. Meanwhile, for insured women aged less than 30 years was 0:56; for ages 30 to 40 years is 3:21; for ages 41 to 50 years is 0.65; for ages 51 to 60 years is 3:12; and for those aged over 60 years is 9.99. This study is useful in determining the risk premium in homogeneous groups based on gender and age.
Net Efficacy Adjusted for Risk (NEAR): A Simple Procedure for Measuring Risk:Benefit Balance

PubMed Central

Boada, José N.; Boada, Carlos; García-Sáiz, Mar; García, Marcelino; Fernández, Eduardo; Gómez, Eugenio

2008-01-01

Background Although several mathematical models have been proposed to assess the risk:benefit of drugs in one measure, their use in practice has been rather limited. Our objective was to design a simple, easily applicable model. In this respect, measuring the proportion of patients who respond favorably to treatment without being affected by adverse drug reactions (ADR) could be a suitable endpoint. However, remarkably few published clinical trials report the data required to calculate this proportion. As an approach to the problem, we calculated the expected proportion of this type of patients. Methodology/Principal Findings Theoretically, responders without ADR may be obtained by multiplying the total number of responders by the total number of subjects that did not suffer ADR, and dividing the product by the total number of subjects studied. When two drugs are studied, the same calculation may be repeated for the second drug. Then, by constructing a 2×2 table with the expected frequencies of responders with and without ADR, and non-responders with and without ADR, the odds ratio and relative risk with their confidence intervals may be easily calculated and graphically represented on a logarithmic scale. Such measures represent “net efficacy adjusted for risk” (NEAR). We assayed the model with results extracted from several published clinical trials or meta-analyses. On comparing our results with those originally reported by the authors, marked differences were found in some cases, with ADR arising as a relevant factor to balance the clinical benefit obtained. The particular features of the adverse reaction that must be weighed against benefit is discussed in the paper. Conclusion NEAR representing overall risk-benefit may contribute to improving knowledge of drug clinical usefulness. As most published clinical trials tend to overestimate benefits and underestimate toxicity, our measure represents an effort to change this trend. PMID:18974868
Evaluating the effects of variation in clinical practice: a risk adjusted cost-effectiveness (RAC-E) analysis of acute stroke services.

PubMed

Pham, Clarabelle; Caffrey, Orla; Ben-Tovim, David; Hakendorf, Paul; Crotty, Maria; Karnon, Jonathan

2012-08-21

Methods for the cost-effectiveness analysis of health technologies are now well established, but such methods may also have a useful role in the context of evaluating the effects of variation in applied clinical practice. This study illustrates a general methodology for the comparative analysis of applied clinical practice at alternative institutions--risk adjusted cost-effectiveness (RAC-E) analysis--with an application that compares acute hospital services for stroke patients admitted to the main public hospitals in South Australia. Using linked, routinely collected data on all South Australian hospital separations from July 2001 to June 2008, an analysis of the RAC-E of services provided at four metropolitan hospitals was undertaken using a decision analytic framework. Observed (plus extrapolated) and expected lifetime costs and survival were compared across patient populations, from which the relative cost-effectiveness of services provided at the different hospitals was estimated. Unadjusted results showed that at one hospital patients incurred fewer costs and gained more life years than at the other hospitals (i.e. it was the dominant hospital). After risk adjustment, the cost minimizing hospital incurred the lowest costs, but with fewer life-years gained than one other hospital. The mean incremental cost per life-year gained of services provided at the most effective hospital was under $20,000, with an associated 65% probability of being cost-effective at a $50,000 per life year monetary threshold. RAC-E analyses can be used to identify important variation in the costs and outcomes associated with clinical practice at alternative institutions. Such data provides an impetus for further investigation to identify specific areas of variation, which may then inform the dissemination of best practice service delivery and organisation.
Estimating Skin Cancer Risk: Evaluating Mobile Computer-Adaptive Testing.

PubMed

Djaja, Ngadiman; Janda, Monika; Olsen, Catherine M; Whiteman, David C; Chien, Tsair-Wei

2016-01-22

Response burden is a major detriment to questionnaire completion rates. Computer adaptive testing may offer advantages over non-adaptive testing, including reduction of numbers of items required for precise measurement. Our aim was to compare the efficiency of non-adaptive (NAT) and computer adaptive testing (CAT) facilitated by Partial Credit Model (PCM)-derived calibration to estimate skin cancer risk. We used a random sample from a population-based Australian cohort study of skin cancer risk (N=43,794). All 30 items of the skin cancer risk scale were calibrated with the Rasch PCM. A total of 1000 cases generated following a normal distribution (mean [SD] 0 [1]) were simulated using three Rasch models with three fixed-item (dichotomous, rating scale, and partial credit) scenarios, respectively. We calculated the comparative efficiency and precision of CAT and NAT (shortening of questionnaire length and the count difference number ratio less than 5% using independent t tests). We found that use of CAT led to smaller person standard error of the estimated measure than NAT, with substantially higher efficiency but no loss of precision, reducing response burden by 48%, 66%, and 66% for dichotomous, Rating Scale Model, and PCM models, respectively. CAT-based administrations of the skin cancer risk scale could substantially reduce participant burden without compromising measurement precision. A mobile computer adaptive test was developed to help people efficiently assess their skin cancer risk.
Uncertainties in estimates of the risks of late effects from space radiation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P. B.; Dicello, J. F.

2004-01-01

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. Published by Elsevier Ltd on behalf of COSPAR.
Uncertainties in estimates of the risks of late effects from space radiation

NASA Astrophysics Data System (ADS)

Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P. B.; Dicello, J. F.

2004-01-01

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits.
Risk cross sections and their application to risk estimation in the galactic cosmic-ray environment

NASA Technical Reports Server (NTRS)

Curtis, S. B.; Nealy, J. E.; Wilson, J. W.; Chatterjee, A. (Principal Investigator)

1995-01-01

Radiation risk cross sections (i.e. risks per particle fluence) are discussed in the context of estimating the risk of radiation-induced cancer on long-term space flights from the galactic cosmic radiation outside the confines of the earth's magnetic field. Such quantities are useful for handling effects not seen after low-LET radiation. Since appropriate cross-section functions for cancer induction for each particle species are not yet available, the conventional quality factor is used as an approximation to obtain numerical results for risks of excess cancer mortality. Risks are obtained for seven of the most radiosensitive organs as determined by the ICRP [stomach, colon, lung, bone marrow (BFO), bladder, esophagus and breast], beneath 10 g/cm2 aluminum shielding at solar minimum. Spectra are obtained for excess relative risk for each cancer per LET interval by calculating the average fluence-LET spectrum for the organ and converting to risk by multiplying by a factor proportional to R gamma L Q(L) before integrating over L, the unrestricted LET. Here R gamma is the risk coefficient for low-LET radiation (excess relative mortality per Sv) for the particular organ in question. The total risks of excess cancer mortality obtained are 1.3 and 1.1% to female and male crew, respectively, for a 1-year exposure at solar minimum. Uncertainties in these values are estimated to range between factors of 4 and 15 and are dominated by the biological uncertainties in the risk coefficients for low-LET radiation and in the LET (or energy) dependence of the risk cross sections (as approximated by the quality factor). The direct substitution of appropriate risk cross sections will eventually circumvent entirely the need to calculate, measure or use absorbed dose, equivalent dose and quality factor for such a high-energy charged-particle environment.
Usefulness of administrative databases for risk adjustment of adverse events in surgical patients.

PubMed

Rodrigo-Rincón, Isabel; Martin-Vizcaíno, Marta P; Tirapu-León, Belén; Zabalza-López, Pedro; Abad-Vicente, Francisco J; Merino-Peralta, Asunción; Oteiza-Martínez, Fabiola

2016-03-01

The aim of this study was to assess the usefulness of clinical-administrative databases for the development of risk adjustment in the assessment of adverse events in surgical patients. The study was conducted at the Hospital of Navarra, a tertiary teaching hospital in northern Spain. We studied 1602 hospitalizations of surgical patients from 2008 to 2010. We analysed 40 comorbidity variables included in the National Surgical Quality Improvement (NSQIP) Program of the American College of Surgeons using 2 sources of information: The clinical and administrative database (CADB) and the data extracted from the complete clinical records (CR), which was considered the gold standard. Variables were catalogued according to compliance with the established criteria: sensitivity, positive predictive value and kappa coefficient >0.6. The average number of comorbidities per study participant was 1.6 using the CR and 0.95 based on CADB (p<.0001). Thirteen types of comorbidities (accounting for 8% of the comorbidities detected in the CR) were not identified when the CADB was the source of information. Five of the 27 remaining comorbidities complied with the 3 established criteria; 2 pathologies fulfilled 2 criteria, whereas 11 fulfilled 1, and 9 did not fulfil any criterion. CADB detected prevalent comorbidities such as comorbid hypertension and diabetes. However, the CABD did not provide enough information to assess the variables needed to perform the risk adjustment proposed by the NSQIP for the assessment of adverse events in surgical patients. Copyright © 2015. Publicado por Elsevier España, S.L.U.
Explaining Behavior Change after Genetic Testing: The Problem of Collinearity between Test Results and Risk Estimates

PubMed Central

Fanshawe, Thomas R.; Prevost, A. Toby; Roberts, J. Scott; Green, Robert C.; Armstrong, David; Marteau, Theresa M.

2010-01-01

This paper explores whether and how the behavioral impact of genotype disclosure can be disentangled from the impact of numerical risk estimates generated by genetic tests. Secondary data analyses are presented from a randomized controlled trial of 162 first-degree relatives of Alzheimer’s disease (AD) patients. Each participant received a lifetime risk estimate of AD. Control group estimates were based on age, gender, family history, and assumed ε4-negative apolipoprotein E (APOE) genotype; intervention group estimates were based upon the first three variables plus true APOE genotype, which was also disclosed. AD-specific self-reported behavior change (diet, exercise, and medication use) was assessed at 12 months. Behavior change was significantly more likely with increasing risk estimates, and also more likely, but not significantly so, in ε4-positive intervention group participants (53% changed behavior) than in control group participants (31%). Intervention group participants receiving ε4-negative genotype feedback (24% changed behavior) and control group participants had similar rates of behavior change and risk estimates, the latter allowing assessment of the independent effects of genotype disclosure. However, collinearity between risk estimates and ε4-positive genotypes, which engender high-risk estimates, prevented assessment of the independent effect of the disclosure of an ε4 genotype. Novel study designs are proposed to determine whether genotype disclosure has an impact upon behavior beyond that of numerical risk estimates. PMID:18666860
Explaining behavior change after genetic testing: the problem of collinearity between test results and risk estimates.

PubMed

Fanshawe, Thomas R; Prevost, A Toby; Roberts, J Scott; Green, Robert C; Armstrong, David; Marteau, Theresa M

2008-09-01

This paper explores whether and how the behavioral impact of genotype disclosure can be disentangled from the impact of numerical risk estimates generated by genetic tests. Secondary data analyses are presented from a randomized controlled trial of 162 first-degree relatives of Alzheimer's disease (AD) patients. Each participant received a lifetime risk estimate of AD. Control group estimates were based on age, gender, family history, and assumed epsilon4-negative apolipoprotein E (APOE) genotype; intervention group estimates were based upon the first three variables plus true APOE genotype, which was also disclosed. AD-specific self-reported behavior change (diet, exercise, and medication use) was assessed at 12 months. Behavior change was significantly more likely with increasing risk estimates, and also more likely, but not significantly so, in epsilon4-positive intervention group participants (53% changed behavior) than in control group participants (31%). Intervention group participants receiving epsilon4-negative genotype feedback (24% changed behavior) and control group participants had similar rates of behavior change and risk estimates, the latter allowing assessment of the independent effects of genotype disclosure. However, collinearity between risk estimates and epsilon4-positive genotypes, which engender high-risk estimates, prevented assessment of the independent effect of the disclosure of an epsilon4 genotype. Novel study designs are proposed to determine whether genotype disclosure has an impact upon behavior beyond that of numerical risk estimates.
Risk Estimation and Sexual Behaviour: A Longitudinal Study of 16- 21-year olds.

PubMed

Breakwell, G M; Breakwell, G M

1996-01-01

The relationships among risk estimation, impulsivity and patterns of sexual risk-taking in 16-21-year-olds are examined. A sample of 236 males and 340 females completed a postal questionnaire on three occasions at annual intervals. They reported their assessment of their own risk of HIV infection, the risk of HIV infection associated with six types of sexual activity, their likelihood of engaging in each of these activities, and whether they had participated in these activities between the first and second data collections. Impulsivity was indexed using a standard test. The data support the conclusion that strong social representations of sexual risks exist which do not markedly change during late adolescence. These risk estimates predict behavioural expectations, primarily for the riskiest behaviours, and for females (actual participation in vaginal sex); but for males, risk estimates fail to predict behaviour. Evidence here for a rational model of individual decision- making in relation to sexual risk- taking is sparse. Impulsivity was not a good predictor of expected or actual patterns of sexual behaviour, though higher impulsivity was associated with having more sexual partners and, in females, with starting to have sex younger.
The estimation of time-varying risks in asset pricing modelling using B-Spline method

NASA Astrophysics Data System (ADS)

Nurjannah; Solimun; Rinaldo, Adji

2017-12-01

Asset pricing modelling has been extensively studied in the past few decades to explore the risk-return relationship. The asset pricing literature typically assumed a static risk-return relationship. However, several studies found few anomalies in the asset pricing modelling which captured the presence of the risk instability. The dynamic model is proposed to offer a better model. The main problem highlighted in the dynamic model literature is that the set of conditioning information is unobservable and therefore some assumptions have to be made. Hence, the estimation requires additional assumptions about the dynamics of risk. To overcome this problem, the nonparametric estimators can also be used as an alternative for estimating risk. The flexibility of the nonparametric setting avoids the problem of misspecification derived from selecting a functional form. This paper investigates the estimation of time-varying asset pricing model using B-Spline, as one of nonparametric approach. The advantages of spline method is its computational speed and simplicity, as well as the clarity of controlling curvature directly. The three popular asset pricing models will be investigated namely CAPM (Capital Asset Pricing Model), Fama-French 3-factors model and Carhart 4-factors model. The results suggest that the estimated risks are time-varying and not stable overtime which confirms the risk instability anomaly. The results is more pronounced in Carhart’s 4-factors model.
Improving Risk Adjustment for Mortality After Pediatric Cardiac Surgery: The UK PRAiS2 Model.

PubMed

Rogers, Libby; Brown, Katherine L; Franklin, Rodney C; Ambler, Gareth; Anderson, David; Barron, David J; Crowe, Sonya; English, Kate; Stickley, John; Tibby, Shane; Tsang, Victor; Utley, Martin; Witter, Thomas; Pagel, Christina

2017-07-01

Partial Risk Adjustment in Surgery (PRAiS), a risk model for 30-day mortality after children's heart surgery, has been used by the UK National Congenital Heart Disease Audit to report expected risk-adjusted survival since 2013. This study aimed to improve the model by incorporating additional comorbidity and diagnostic information. The model development dataset was all procedures performed between 2009 and 2014 in all UK and Ireland congenital cardiac centers. The outcome measure was death within each 30-day surgical episode. Model development followed an iterative process of clinical discussion and development and assessment of models using logistic regression under 25 × 5 cross-validation. Performance was measured using Akaike information criterion, the area under the receiver-operating characteristic curve (AUC), and calibration. The final model was assessed in an external 2014 to 2015 validation dataset. The development dataset comprised 21,838 30-day surgical episodes, with 539 deaths (mortality, 2.5%). The validation dataset comprised 4,207 episodes, with 97 deaths (mortality, 2.3%). The updated risk model included 15 procedural, 11 diagnostic, and 4 comorbidity groupings, and nonlinear functions of age and weight. Performance under cross-validation was: median AUC of 0.83 (range, 0.82 to 0.83), median calibration slope and intercept of 0.92 (range, 0.64 to 1.25) and -0.23 (range, -1.08 to 0.85) respectively. In the validation dataset, the AUC was 0.86 (95% confidence interval [CI], 0.82 to 0.89), and the calibration slope and intercept were 1.01 (95% CI, 0.83 to 1.18) and 0.11 (95% CI, -0.45 to 0.67), respectively, showing excellent performance. A more sophisticated PRAiS2 risk model for UK use was developed with additional comorbidity and diagnostic information, alongside age and weight as nonlinear variables. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Adjusting Estimates of the Expected Value of Information for Implementation: Theoretical Framework and Practical Application.

PubMed

Andronis, Lazaros; Barton, Pelham M

2016-04-01

Value of information (VoI) calculations give the expected benefits of decision making under perfect information (EVPI) or sample information (EVSI), typically on the premise that any treatment recommendations made in light of this information will be implemented instantly and fully. This assumption is unlikely to hold in health care; evidence shows that obtaining further information typically leads to "improved" rather than "perfect" implementation. To present a method of calculating the expected value of further research that accounts for the reality of improved implementation. This work extends an existing conceptual framework by introducing additional states of the world regarding information (sample information, in addition to current and perfect information) and implementation (improved implementation, in addition to current and optimal implementation). The extension allows calculating the "implementation-adjusted" EVSI (IA-EVSI), a measure that accounts for different degrees of implementation. Calculations of implementation-adjusted estimates are illustrated under different scenarios through a stylized case study in non-small cell lung cancer. In the particular case study, the population values for EVSI and IA-EVSI were £ 25 million and £ 8 million, respectively; thus, a decision assuming perfect implementation would have overestimated the expected value of research by about £ 17 million. IA-EVSI was driven by the assumed time horizon and, importantly, the specified rate of change in implementation: the higher the rate, the greater the IA-EVSI and the lower the difference between IA-EVSI and EVSI. Traditionally calculated measures of population VoI rely on unrealistic assumptions about implementation. This article provides a simple framework that accounts for improved, rather than perfect, implementation and offers more realistic estimates of the expected value of research. © The Author(s) 2015.
Uncertainties in Estimates of the Risks of Late Effects from Space Radiation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P.; Dicelli, J. F.

2002-01-01

The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.
Age adjustment in ecological studies: using a study on arsenic ingestion and bladder cancer as an example.

PubMed

Guo, How-Ran

2011-10-20

Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example. A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.
Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats

USGS Publications Warehouse

Sando, Steven K.; Sando, Roy; McCarthy, Peter M.; Dutton, DeAnn M.

2016-04-05

The climatic conditions of the specific time period during which peak-flow data were collected at a given streamflow-gaging station (hereinafter referred to as gaging station) can substantially affect how well the peak-flow frequency (hereinafter referred to as frequency) results represent long-term hydrologic conditions. Differences in the timing of the periods of record can result in substantial inconsistencies in frequency estimates for hydrologically similar gaging stations. Potential for inconsistency increases with decreasing peak-flow record length. The representativeness of the frequency estimates for a short-term gaging station can be adjusted by various methods including weighting the at-site results in association with frequency estimates from regional regression equations (RREs) by using the Weighted Independent Estimates (WIE) program. Also, for gaging stations that cannot be adjusted by using the WIE program because of regulation or drainage areas too large for application of RREs, frequency estimates might be improved by using record extension procedures, including a mixed-station analysis using the maintenance of variance type I (MOVE.1) procedure. The U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, completed a study to provide adjusted frequency estimates for selected gaging stations through water year 2011.The purpose of Chapter D of this Scientific Investigations Report is to present adjusted frequency estimates for 504 selected streamflow-gaging stations in or near Montana based on data through water year 2011. Estimates of peak-flow magnitudes for the 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to the 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.The at-site frequency estimates were
A novel tool for user-friendly estimation of natural, diagnostic and professional radiation risk: Radio-Risk software.

PubMed

Carpeggiani, Clara; Paterni, Marco; Caramella, Davide; Vano, Eliseo; Semelka, Richard C; Picano, Eugenio

2012-11-01

Awareness of radiological risk is low among doctors and patients. An educational/decision tool that considers each patient' s cumulative lifetime radiation exposure would facilitate provider-patient communication. The purpose of this work was to develop user-friendly software for simple estimation and communication of radiological risk to patients and doctors as a part of the SUIT-Heart (Stop Useless Imaging Testing in Heart disease) Project of the Tuscany Region. We developed a novel software program (PC-platform, Windows OS fully downloadable at http://suit-heart.ifc.cnr.it) considering reference dose estimates from American Heart Association Radiological Imaging 2009 guidelines and UK Royal College of Radiology 2007 guidelines. Cancer age and gender-weighted risk were derived from Biological Effects of Ionising Radiation VII Committee, 2006. With simple input functions (demographics, age, gender) the user selects from a predetermined menu variables relating to natural (e.g., airplane flights and geo-tracked background exposure), professional (e.g., cath lab workers) and medical (e.g., CT, cardiac scintigraphy, coronary stenting) sources. The program provides a simple numeric (cumulative effective dose in milliSievert, mSv, and equivalent number of chest X-rays) and graphic (cumulative temporal trends of exposure, cancer cases out of 100 exposed persons) display. A simple software program allows straightforward estimation of cumulative dose (in multiples of chest X-rays) and risk (in extra % lifetime cancer risk), with simple numbers quantifying lifetime extra cancer risk. Pictorial display of radiation risk may be valuable for increasing radiological awareness in cardiologists. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Evaluation of energy balance closure adjustment methods by independent evapotranspiration estimates from lysimeters and hydrological simulations

DOE PAGES

Mauder, Matthias; Genzel, Sandra; Fu, Jin; ...

2017-11-10

Here, we report non-closure of the surface energy balance is a frequently observed phenomenon of hydrometeorological field measurements, when using the eddy-covariance method, which can be ascribed to an underestimation of the turbulent fluxes. Several approaches have been proposed in order to adjust the measured fluxes for this apparent systematic error. However, there are uncertainties about partitioning of the energy balance residual between the sensible and latent heat flux and whether such a correction should be applied on 30-minute data or longer time scales. The data for this study originate from two grassland sites in southern Germany, where measurements frommore » weighable lysimeters are available as reference. The adjusted evapotranspiration rates are also compared with joint energy and water balance simulations using a physically-based distributed hydrological model. We evaluate two adjustment methods: the first one preserves the Bowen ratio and the correction factor is determined on a daily basis. The second one attributes a smaller portion of the residual energy to the latent heat flux than to the sensible heat flux for closing the energy balance for every 30-minute flux integration interval. Both methods lead to an improved agreement of the eddy-covariance based fluxes with the independent lysimeter estimates and the physically-based model simulations. The first method results in a better comparability of evapotranspiration rates, and the second method leads to a smaller overall bias. These results are similar between both sites despite considerable differences in terrain complexity and grassland management. Moreover, we found that a daily adjustment factor leads to less scatter than a complete partitioning of the residual for every half-hour time interval. Lastly, the vertical temperature gradient in the surface layer and friction velocity were identified as important predictors for a potential future parameterization of the energy balance
Evaluation of energy balance closure adjustment methods by independent evapotranspiration estimates from lysimeters and hydrological simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mauder, Matthias; Genzel, Sandra; Fu, Jin

Here, we report non-closure of the surface energy balance is a frequently observed phenomenon of hydrometeorological field measurements, when using the eddy-covariance method, which can be ascribed to an underestimation of the turbulent fluxes. Several approaches have been proposed in order to adjust the measured fluxes for this apparent systematic error. However, there are uncertainties about partitioning of the energy balance residual between the sensible and latent heat flux and whether such a correction should be applied on 30-minute data or longer time scales. The data for this study originate from two grassland sites in southern Germany, where measurements frommore » weighable lysimeters are available as reference. The adjusted evapotranspiration rates are also compared with joint energy and water balance simulations using a physically-based distributed hydrological model. We evaluate two adjustment methods: the first one preserves the Bowen ratio and the correction factor is determined on a daily basis. The second one attributes a smaller portion of the residual energy to the latent heat flux than to the sensible heat flux for closing the energy balance for every 30-minute flux integration interval. Both methods lead to an improved agreement of the eddy-covariance based fluxes with the independent lysimeter estimates and the physically-based model simulations. The first method results in a better comparability of evapotranspiration rates, and the second method leads to a smaller overall bias. These results are similar between both sites despite considerable differences in terrain complexity and grassland management. Moreover, we found that a daily adjustment factor leads to less scatter than a complete partitioning of the residual for every half-hour time interval. Lastly, the vertical temperature gradient in the surface layer and friction velocity were identified as important predictors for a potential future parameterization of the energy balance
Resources for global risk assessment: the International Toxicity Estimates for Risk (ITER) and Risk Information Exchange (RiskIE) databases.

PubMed

Wullenweber, Andrea; Kroner, Oliver; Kohrman, Melissa; Maier, Andrew; Dourson, Michael; Rak, Andrew; Wexler, Philip; Tomljanovic, Chuck

2008-11-15

The rate of chemical synthesis and use has outpaced the development of risk values and the resolution of risk assessment methodology questions. In addition, available risk values derived by different organizations may vary due to scientific judgments, mission of the organization, or use of more recently published data. Further, each organization derives values for a unique chemical list so it can be challenging to locate data on a given chemical. Two Internet resources are available to address these issues. First, the International Toxicity Estimates for Risk (ITER) database (www.tera.org/iter) provides chronic human health risk assessment data from a variety of organizations worldwide in a side-by-side format, explains differences in risk values derived by different organizations, and links directly to each organization's website for more detailed information. It is also the only database that includes risk information from independent parties whose risk values have undergone independent peer review. Second, the Risk Information Exchange (RiskIE) is a database of in progress chemical risk assessment work, and includes non-chemical information related to human health risk assessment, such as training modules, white papers and risk documents. RiskIE is available at http://www.allianceforrisk.org/RiskIE.htm, and will join ITER on National Library of Medicine's TOXNET (http://toxnet.nlm.nih.gov/). Together, ITER and RiskIE provide risk assessors essential tools for easily identifying and comparing available risk data, for sharing in progress assessments, and for enhancing interaction among risk assessment groups to decrease duplication of effort and to harmonize risk assessment procedures across organizations.
Premorbid social adjustment and association with attenuated psychotic symptoms in clinical high-risk and help-seeking youth.

PubMed

Tarbox-Berry, S I; Perkins, D O; Woods, S W; Addington, J

2018-04-01

Attenuated positive symptom syndrome (APSS), characterized by 'putatively prodromal' attenuated psychotic-like pathology, indicates increased risk for psychosis. Poor premorbid social adjustment predicts severity of APSS symptoms and predicts subsequent psychosis in APSS-diagnosed individuals, suggesting application for improving detection of 'true' prodromal youth who will transition to psychosis. However, these predictive associations have not been tested in controls and therefore may be independent of the APSS diagnosis, negating utility for improving prediction in APSS-diagnosed individuals. Association between premorbid social maladjustment and severity of positive, negative, disorganized, and general APSS symptoms was tested in 156 individuals diagnosed with APSS and 76 help-seeking (non-APSS) controls enrolled in the Enhancing the Prospective Prediction of Psychosis (PREDICT) study using prediction analysis. Premorbid social maladjustment was associated with social anhedonia, reduced expression of emotion, restricted ideational richness, and deficits in occupational functioning, independent of the APSS diagnosis. Associations between social maladjustment and suspiciousness, unusual thought content, avolition, dysphoric mood, and impaired tolerance to normal stress were uniquely present in participants meeting APSS criteria. Social maladjustment was associated with odd behavior/appearance and diminished experience of emotions and self only in participants who did not meet APSS criteria. Predictive associations between poor premorbid social adjustment and attenuated psychotic-like pathology were identified, a subset of which were indicative of high risk for psychosis. This study offers a method for improving risk identification while ruling out low-risk individuals.
Burden of Six Healthcare-Associated Infections on European Population Health: Estimating Incidence-Based Disability-Adjusted Life Years through a Population Prevalence-Based Modelling Study

PubMed Central

Eckmanns, Tim; Abu Sin, Muna; Ducomble, Tanja; Harder, Thomas; Sixtensson, Madlen; Velasco, Edward; Weiß, Bettina; Kramarz, Piotr; Monnet, Dominique L.; Kretzschmar, Mirjam E.; Suetens, Carl

2016-01-01

Background Estimating the burden of healthcare-associated infections (HAIs) compared to other communicable diseases is an ongoing challenge given the need for good quality data on the incidence of these infections and the involved comorbidities. Based on the methodology of the Burden of Communicable Diseases in Europe (BCoDE) project and 2011–2012 data from the European Centre for Disease Prevention and Control (ECDC) point prevalence survey (PPS) of HAIs and antimicrobial use in European acute care hospitals, we estimated the burden of six common HAIs. Methods and Findings The included HAIs were healthcare-associated pneumonia (HAP), healthcare-associated urinary tract infection (HA UTI), surgical site infection (SSI), healthcare-associated Clostridium difficile infection (HA CDI), healthcare-associated neonatal sepsis, and healthcare-associated primary bloodstream infection (HA primary BSI). The burden of these HAIs was measured in disability-adjusted life years (DALYs). Evidence relating to the disease progression pathway of each type of HAI was collected through systematic literature reviews, in order to estimate the risks attributable to HAIs. For each of the six HAIs, gender and age group prevalence from the ECDC PPS was converted into incidence rates by applying the Rhame and Sudderth formula. We adjusted for reduced life expectancy within the hospital population using three severity groups based on McCabe score data from the ECDC PPS. We estimated that 2,609,911 new cases of HAI occur every year in the European Union and European Economic Area (EU/EEA). The cumulative burden of the six HAIs was estimated at 501 DALYs per 100,000 general population each year in EU/EEA. HAP and HA primary BSI were associated with the highest burden and represented more than 60% of the total burden, with 169 and 145 DALYs per 100,000 total population, respectively. HA UTI, SSI, HA CDI, and HA primary BSI ranked as the third to sixth syndromes in terms of burden of disease
Adjusting survival time estimates to account for treatment switching in randomized controlled trials--an economic evaluation context: methods, limitations, and recommendations.

PubMed

Latimer, Nicholas R; Abrams, Keith R; Lambert, Paul C; Crowther, Michael J; Wailoo, Allan J; Morden, James P; Akehurst, Ron L; Campbell, Michael J

2014-04-01

Treatment switching commonly occurs in clinical trials of novel interventions in the advanced or metastatic cancer setting. However, methods to adjust for switching have been used inconsistently and potentially inappropriately in health technology assessments (HTAs). We present recommendations on the use of methods to adjust survival estimates in the presence of treatment switching in the context of economic evaluations. We provide background on the treatment switching issue and summarize methods used to adjust for it in HTAs. We discuss the assumptions and limitations associated with adjustment methods and draw on results of a simulation study to make recommendations on their use. We demonstrate that methods used to adjust for treatment switching have important limitations and often produce bias in realistic scenarios. We present an analysis framework that aims to increase the probability that suitable adjustment methods can be identified on a case-by-case basis. We recommend that the characteristics of clinical trials, and the treatment switching mechanism observed within them, should be considered alongside the key assumptions of the adjustment methods. Key assumptions include the "no unmeasured confounders" assumption associated with the inverse probability of censoring weights (IPCW) method and the "common treatment effect" assumption associated with the rank preserving structural failure time model (RPSFTM). The limitations associated with switching adjustment methods such as the RPSFTM and IPCW mean that they are appropriate in different scenarios. In some scenarios, both methods may be prone to bias; "2-stage" methods should be considered, and intention-to-treat analyses may sometimes produce the least bias. The data requirements of adjustment methods also have important implications for clinical trialists.
Data Sources for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).
Correlates of household seismic hazard adjustment adoption.

PubMed

Lindell, M K; Whitney, D J

2000-02-01

This study examined the relationships of self-reported adoption of 12 seismic hazard adjustments (pre-impact actions to reduce danger to persons and property) with respondents' demographic characteristics, perceived risk, perceived hazard knowledge, perceived protection responsibility, and perceived attributes of the hazard adjustments. Consistent with theoretical predictions, perceived attributes of the hazard adjustments differentiated among the adjustments and had stronger correlations with adoption than any of the other predictors. These results identify the adjustments and attributes that emergency managers should address to have the greatest impact on improving household adjustment to earthquake hazard.
Bayesian Framework for Water Quality Model Uncertainty Estimation and Risk Management

EPA Science Inventory

A formal Bayesian methodology is presented for integrated model calibration and risk-based water quality management using Bayesian Monte Carlo simulation and maximum likelihood estimation (BMCML). The primary focus is on lucid integration of model calibration with risk-based wat...
Estimating the concordance probability in a survival analysis with a discrete number of risk groups.

PubMed

Heller, Glenn; Mo, Qianxing

2016-04-01

A clinical risk classification system is an important component of a treatment decision algorithm. A measure used to assess the strength of a risk classification system is discrimination, and when the outcome is survival time, the most commonly applied global measure of discrimination is the concordance probability. The concordance probability represents the pairwise probability of lower patient risk given longer survival time. The c-index and the concordance probability estimate have been used to estimate the concordance probability when patient-specific risk scores are continuous. In the current paper, the concordance probability estimate and an inverse probability censoring weighted c-index are modified to account for discrete risk scores. Simulations are generated to assess the finite sample properties of the concordance probability estimate and the weighted c-index. An application of these measures of discriminatory power to a metastatic prostate cancer risk classification system is examined.
Quality of pancreatic transplant program assessment using a risk-adjusted cumulative sum chart: experience from a single, small center.

PubMed

Grochowiecki, T; Jakimowicz, T; Grabowska-Derlatka, L; Szmidt, J

2014-10-01

The high rate of complication after pancreas transplantation not only had an impact on recipient quality of life and survival but also had significant financial implications. Thus, monitoring transplant center performance was crucial to indentifying changes in clinical practice that result in quality deterioration. To evaluate retrospectively the quality of the single, small pancreatic transplant program and to establish prospective monitoring of the center using risk-adjusted cumulative sum (CUSUM). From 1988 to 2014, 119 simultaneous pancreas and the kidney transplantations (SPKTx) were performed. The program was divided into 3 eras, based on surgical technique and immunosuppression. Analyses of the 15 fatal outcomes due to complication from pancreatic graft were performed. The risk model was developed using multivariable logistic regression analysis based on retrospective data of 112 SPKTx recipients. The risk-adjusted 1-sided CUSUM chart was plotted for retrospective and prospective events. The upper control limit was set to 2. There were 2 main causes of death: multiorgan failure (73.3%; 11/15) and septic hemorrhage (26.7%; 4/15). Quality analysis using the CUSUM chart revealed that the process was not homogeneous; however, no significant signal of program deterioration was obtained and the performance of the whole program was within the settled control limit. For a single pancreatic transplant center. The risk-adjusted CUSUM chart was a useful tool for quality program assessment. It could support decision making during traditional surgical morbidity and mortality conferences. For small transplant centers, increasing the sensitivity of the CUSUM method by lowering the upper control limit should be considered. However, an individual assessment approach of the for particular centers is recommended.
Auditory risk estimates for youth target shooting

PubMed Central

Meinke, Deanna K.; Murphy, William J.; Finan, Donald S.; Lankford, James E.; Flamme, Gregory A.; Stewart, Michael; Soendergaard, Jacob; Jerome, Trevor W.

2015-01-01

Objective To characterize the impulse noise exposure and auditory risk for youth recreational firearm users engaged in outdoor target shooting events. The youth shooting positions are typically standing or sitting at a table, which places the firearm closer to the ground or reflective surface when compared to adult shooters. Design Acoustic characteristics were examined and the auditory risk estimates were evaluated using contemporary damage-risk criteria for unprotected adult listeners and the 120-dB peak limit suggested by the World Health Organization (1999) for children. Study sample Impulses were generated by 26 firearm/ammunition configurations representing rifles, shotguns, and pistols used by youth. Measurements were obtained relative to a youth shooter’s left ear. Results All firearms generated peak levels that exceeded the 120 dB peak limit suggested by the WHO for children. In general, shooting from the seated position over a tabletop increases the peak levels, LAeq8 and reduces the unprotected maximum permissible exposures (MPEs) for both rifles and pistols. Pistols pose the greatest auditory risk when fired over a tabletop. Conclusion Youth should utilize smaller caliber weapons, preferably from the standing position, and always wear hearing protection whenever engaging in shooting activities to reduce the risk for auditory damage. PMID:24564688
Job insecurity and risk of diabetes: a meta-analysis of individual participant data.

PubMed

Ferrie, Jane E; Virtanen, Marianna; Jokela, Markus; Madsen, Ida E H; Heikkilä, Katriina; Alfredsson, Lars; Batty, G David; Bjorner, Jakob B; Borritz, Marianne; Burr, Hermann; Dragano, Nico; Elovainio, Marko; Fransson, Eleonor I; Knutsson, Anders; Koskenvuo, Markku; Koskinen, Aki; Kouvonen, Anne; Kumari, Meena; Nielsen, Martin L; Nordin, Maria; Oksanen, Tuula; Pahkin, Krista; Pejtersen, Jan H; Pentti, Jaana; Salo, Paula; Shipley, Martin J; Suominen, Sakari B; Tabák, Adam; Theorell, Töres; Väänänen, Ari; Vahtera, Jussi; Westerholm, Peter J M; Westerlund, Hugo; Rugulies, Reiner; Nyberg, Solja T; Kivimäki, Mika

2016-12-06

Job insecurity has been associated with certain health outcomes. We examined the role of job insecurity as a risk factor for incident diabetes. We used individual participant data from 8 cohort studies identified in 2 open-access data archives and 11 cohort studies participating in the Individual-Participant-Data Meta-analysis in Working Populations Consortium. We calculated study-specific estimates of the association between job insecurity reported at baseline and incident diabetes over the follow-up period. We pooled the estimates in a meta-analysis to produce a summary risk estimate. The 19 studies involved 140 825 participants from Australia, Europe and the United States, with a mean follow-up of 9.4 years and 3954 incident cases of diabetes. In the preliminary analysis adjusted for age and sex, high job insecurity was associated with an increased risk of incident diabetes compared with low job insecurity (adjusted odds ratio [OR] 1.19, 95% confidence interval [CI] 1.09-1.30). In the multivariable-adjusted analysis restricted to 15 studies with baseline data for all covariates (age, sex, socioeconomic status, obesity, physical activity, alcohol and smoking), the association was slightly attenuated (adjusted OR 1.12, 95% CI 1.01-1.24). Heterogeneity between the studies was low to moderate (age- and sex-adjusted model: I 2 = 24%, p = 0.2; multivariable-adjusted model: I 2 = 27%, p = 0.2). In the multivariable-adjusted analysis restricted to high-quality studies, in which the diabetes diagnosis was ascertained from electronic medical records or clinical examination, the association was similar to that in the main analysis (adjusted OR 1.19, 95% CI 1.04-1.35). Our findings suggest that self-reported job insecurity is associated with a modest increased risk of incident diabetes. Health care personnel should be aware of this association among workers reporting job insecurity. © 2016 Canadian Medical Association or its licensors.
Using biomarker data to adjust estimates of the distribution of usual intakes for misreporting: application to energy intake in the US population.

PubMed

Yanetz, Rivka; Kipnis, Victor; Carroll, Raymond J; Dodd, Kevin W; Subar, Amy F; Schatzkin, Arthur; Freedman, Laurence S

2008-03-01

It is now well-established that individuals misreport their dietary intake. We propose a new method (National Research Council-Biomarker [NRC-B]) for estimating population distributions of usual dietary intake from national survey 24-hour recall data, using additional biomarker data from an external study to adjust for such dietary misreporting. NRC-B is an extension of the NRC method, and is based upon two developed assumptions: the ratio of the mean of true intake to that of reported intake is equal in the survey and external biomarker study; and the ratio of the variance of true intake to that of reported intake is equal in these two studies. NRC-B adjusts the usual intake distribution both for within-person variation and for bias (underreporting) that occur with 24-hour recall reports. Using doubly labeled water ((2)H(2)(18)O) measurements from the Observing Protein and Energy Nutrition study, we applied NRC-B to data on energy intake for adults aged 40 to 69 years from two national surveys, the Continuing Survey of Food Intakes by Individuals and National Health and Nutrition Examination Survey. We compared the results with the NRC and traditional methods that used only the survey data to estimate dietary intake distributions. Estimated distributions from NRC-B and NRC were much narrower and less skewed than from the traditional method. However, unlike NRC, the median of the NRC-B based distribution was higher by 8% to 16% than the traditional method in our examples. The proposed method adjusts for the well-documented problem of underreporting of energy intake.
Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.
Estimating Toxicity Pathway Activating Doses for High Throughput Chemical Risk Assessments

EPA Science Inventory

Estimating a Toxicity Pathway Activating Dose (TPAD) from in vitro assays as an analog to a reference dose (RfD) derived from in vivo toxicity tests would facilitate high throughput risk assessments of thousands of data-poor environmental chemicals. Estimating a TPAD requires def...
Latino College Students: The Influence of Risk and Protective Factors on Depression, College Adjustment, and Drop-Out Intentions

ERIC Educational Resources Information Center

Rischall, Emily

2017-01-01

This study examined the influence of risk and protective variables on Latino students' experience of depression, college adjustment, and drop-out intentions. One hundred and seventeen Latino undergraduate students at a Midwestern university participated in this investigation. Perceived bicultural competence emerged as a protective factor; and…
Debris flow risk mapping on medium scale and estimation of prospective economic losses

NASA Astrophysics Data System (ADS)

Blahut, Jan; Sterlacchini, Simone

2010-05-01

Delimitation of potential zones affected by debris flow hazard, mapping of areas at risk, and estimation of future economic damage provides important information for spatial planners and local administrators in all countries endangered by this type of phenomena. This study presents a medium scale (1:25 000 - 1: 50 000) analysis applied in the Consortium of Mountain Municipalities of Valtellina di Tirano (Italian Alps, Lombardy Region). In this area a debris flow hazard map was coupled with the information about the elements at risk to obtain monetary values of prospective damage. Two available hazard maps were obtained from GIS medium scale modelling. Probability estimations of debris flow occurrence were calculated using existing susceptibility maps and two sets of aerial images. Value to the elements at risk was assigned according to the official information on housing costs and land value from the Territorial Agency of Lombardy Region. In the first risk map vulnerability values were assumed to be 1. The second risk map uses three classes of vulnerability values qualitatively estimated according to the debris flow possible propagation. Risk curves summarizing the possible economic losses were calculated. Finally these maps of economic risk were compared to maps derived from qualitative evaluation of the values of the elements at risk.
Carbohydrate intake, obesity, metabolic syndrome and cancer risk? A two-part systematic review and meta-analysis protocol to estimate attributability

PubMed Central

Sartorius, B; Sartorius, K; Aldous, C; Madiba, T E; Stefan, C; Noakes, T

2016-01-01

Introduction Linkages between carbohydrates, obesity and cancer continue to demonstrate conflicting results. Evidence suggests inconclusive direct linkages between carbohydrates and specific cancers. Conversely, obesity has been strongly linked to a wide range of cancers. The purpose of the study is to explore linkages between carbohydrate intake and cancer types using a two-step approach. First the study will evaluate the linkages between carbohydrate intake and obesity, potentially stratified by metabolic syndrome status. Second, the estimated attributable fraction of obesity ascribed to carbohydrate intake will be multiplied against obesity attributable fractions for cancer types to give estimated overall attributable fraction for carbohydrate versus cancer type. Methods and analysis We will perform a comprehensive search to identify all possible published and unpublished studies that have assessed risk factors for obesity including dietary carbohydrate intake. Scientific databases, namely PubMed MEDLINE, EMBASE, EBSCOhost and ISI Web of Science will be searched. Following study selection, paper/data acquisition, and data extraction and synthesis, we will appraise the quality of studies and risk of bias, as well as assess heterogeneity. Meta-weighted attributable fractions of obesity due to carbohydrate intake will be estimated after adjusting for other potential confounding factors (eg, physical inactivity, other dietary intake). Furthermore, previously published systematic reviews assessing the cancer-specific risk associated with obesity will also be drawn. These estimates will be linked with the attributability of carbohydrate intake in part 1 to estimate the cancer-specific burden that can be attributed to dietary carbohydrates. This systematic review protocol has been developed according to the ‘Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) 2015’. Ethics and dissemination The current study will be based on
Patient volume, staffing, and workload in relation to risk-adjusted outcomes in a random stratified sample of UK neonatal intensive care units: a prospective evaluation.

PubMed

Tucker, Janet

2002-01-12

UK recommendations suggest that large neonatal intensive-care units (NICUs) have better outcomes than small units, although this suggestion remains unproven. We assessed whether patient volume, staffing levels, and workload are associated with risk-adjusted outcomes, and with costs or staff wellbeing. 186 UK NICUs were stratified according to volume of patients, nursing provision, and neonatal consultant provision. Primary outcomes were hospital mortality, mortality or cerebral damage, and nosocomial bacteraemia. We studied 13515 infants of all birthweights consecutively admitted to 54 randomly selected NICUs. Multiple logistic regression analyses were done with every primary outcome as the dependent variable. Staff wellbeing and stress were assessed by anonymous mental health index (MHI)-5 questionnaires. Data were available for 13334 (99%) infants. High-volume NICUs treated the sickest infants and had highest crude mortality. Risk-adjusted mortality and mortality or cerebral damage were unrelated to patient volume or staffing provision; however, nosocomial bacteraemia was less frequent in NICUs with low neonatal consultant provision (odds ratio 0.65, 95% CI 0.43-0.98). Mortality was raised with increasing workload in all types of NICUs. Infants admitted at full capacity versus half capacity were about 50% more likely to die, but there was wide uncertainty around this estimate. Most staff had MHI-5 scores that suggested good mental health. The implications of this report for staffing policy, medicolegal risk management, and ethical practice remain to be tested. Centralisation of only the sickest infants could improve efficiency, provided that this does not create excessive workload for staff. Assessment of increased staffing levels that are closer to those in adult intensive care might be appropriate.

Genetic Obesity and the Risk of Atrial Fibrillation – Causal Estimates from Mendelian Randomization

PubMed Central

Chatterjee, Neal A.; Arking, Dan E.; Ellinor, Patrick T.; Heeringa, Jan; Lin, Honghuang; Lubitz, Steven A.; Soliman, Elsayed Z.; Verweij, Niek; Alonso, Alvaro; Benjamin, Emelia J.; Gudnason, Vilmundur; Stricker, Bruno H. C.; Van Der Harst, Pim; Chasman, Daniel I.; Albert, Christine M.

2017-01-01

Background Observational studies have identified an association between body mass index (BMI) and incident atrial fibrillation (AF). Inferring causality from observational studies, however, is subject to residual confounding, reverse causation, and bias. The primary objective of this study was to evaluate the causal association between BMI and AF using genetic predictors of BMI. Methods We identified 51 646 individuals of European ancestry without AF at baseline from seven prospective population-based cohorts initiated between 1987 and 2002 in the United States, Iceland, and the Netherlands with incident AF ascertained between 1987 and 2012. Cohort-specific mean follow-up ranged 7.4 to 19.2 years, over which period there were a total of 4178 cases of incident AF. We performed a Mendelian randomization with instrumental variable analysis to estimate a cohort-specific causal hazard ratio for the association between BMI and AF. Two genetic instruments for BMI were utilized: FTO genotype (rs1558902) and a BMI gene score comprised of 39 single nucleotide polymorphisms identified by genome-wide association studies to be associated with BMI. Cohort-specific estimates were combined by random-effects, inverse variance weighted meta-analysis. Results In age- and sex-adjusted meta-analysis, both genetic instruments were significantly associated with BMI (FTO: 0.43 [95% CI: 0.32 – 0.54] kg/m2 per A-allele, p<0.001); BMI gene score: 1.05 [95% CI: 0.90-1.20] kg/m2 per 1 unit increase, p<0.001) and incident AF (FTO – HR: 1.07 [1.02-1.11] per A-allele, p=0.004; BMI gene score – HR: 1.11 [1.05-1.18] per 1-unit increase, p<0.001). Age- and sex-adjusted instrumental variable estimates for the causal association between BMI and incident AF were HR 1.15 [1.04-1.26] per kg/m2, p=0.005 (FTO) and 1.11 [1.05-1.17] per kg/m2, p<0.001 (BMI gene score). Both of these estimates were consistent with the meta-analyzed estimate between observed BMI and AF (age- and sex-adjusted HR 1.05 [1
Seismic Risk Assessment and Loss Estimation for Tbilisi City

NASA Astrophysics Data System (ADS)

Tsereteli, Nino; Alania, Victor; Varazanashvili, Otar; Gugeshashvili, Tengiz; Arabidze, Vakhtang; Arevadze, Nika; Tsereteli, Emili; Gaphrindashvili, Giorgi; Gventcadze, Alexander; Goguadze, Nino; Vephkhvadze, Sophio

2013-04-01

The proper assessment of seismic risk is of crucial importance for society protection and city sustainable economic development, as it is the essential part to seismic hazard reduction. Estimation of seismic risk and losses is complicated tasks. There is always knowledge deficiency on real seismic hazard, local site effects, inventory on elements at risk, infrastructure vulnerability, especially for developing countries. Lately great efforts was done in the frame of EMME (earthquake Model for Middle East Region) project, where in the work packages WP1, WP2 , WP3 and WP4 where improved gaps related to seismic hazard assessment and vulnerability analysis. Finely in the frame of work package wp5 "City Scenario" additional work to this direction and detail investigation of local site conditions, active fault (3D) beneath Tbilisi were done. For estimation economic losses the algorithm was prepared taking into account obtained inventory. The long term usage of building is very complex. It relates to the reliability and durability of buildings. The long term usage and durability of a building is determined by the concept of depreciation. Depreciation of an entire building is calculated by summing the products of individual construction unit' depreciation rates and the corresponding value of these units within the building. This method of calculation is based on an assumption that depreciation is proportional to the building's (constructions) useful life. We used this methodology to create a matrix, which provides a way to evaluate the depreciation rates of buildings with different type and construction period and to determine their corresponding value. Finally loss was estimated resulting from shaking 10%, 5% and 2% exceedance probability in 50 years. Loss resulting from scenario earthquake (earthquake with possible maximum magnitude) also where estimated.
Estimating the impact of grouping misclassification on risk ...

EPA Pesticide Factsheets

Environmental health risk assessments of chemical mixtures that rely on component approaches often begin by grouping the chemicals of concern according to toxicological similarity. Approaches that assume dose addition typically are used for groups of similarly-acting chemicals and those that assume response addition are used for groups of independently acting chemicals. Grouping criteria for similarity can include a common adverse outcome pathway (AOP) and similarly shaped dose-response curves, with the latter used in the relative potency factor (RPF) method for estimating mixture response. Independence of toxic action is generally assumed if there is evidence that the chemicals act by different mechanisms. Several questions arise about the potential for misclassification error in the mixture risk prediction. If a common AOP has been established, how much error could there be if the same dose-response curve shape is assumed for all chemicals, when the shapes truly differ and, conversely, what is the error potential if different shapes are assumed when they are not? In particular, how do those concerns impact the choice of index chemical and uncertainty of the RPF-estimated mixture response? What is the quantitative impact if dose additivity is assumed when complete or partial independence actually holds and vice versa? These concepts and implications will be presented with numerical examples in the context of uncertainty of the RPF-estimated mixture response,
A-BOMB SURVIVOR SITE-SPECIFIC RADIOGENIC CANCER RISKS ESTIMATES

EPA Science Inventory

A draft manuscript is being prepared that describes ways to improve estimates of risk from radiation that have been derived from A-bomb survivors. The work has been published in the journal Radiation Research volume 169, pages 87-98.
A methodology for estimating risks associated with landslides of contaminated soil into rivers.

PubMed

Göransson, Gunnel; Norrman, Jenny; Larson, Magnus; Alén, Claes; Rosén, Lars

2014-02-15

Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in landslide risk assessments. This study suggests a methodology to estimate the environmental risks associated with landslides in contaminated sites adjacent to rivers. The methodology is probabilistic and allows for datasets with large uncertainties and the use of expert judgements, providing quantitative estimates of probabilities for defined failures. The approach is illustrated by a case study along the river Göta Älv, Sweden, where failures are defined and probabilities for those failures are estimated. Failures are defined from a pollution perspective and in terms of exceeding environmental quality standards (EQSs) and acceptable contaminant loads. Models are then suggested to estimate probabilities of these failures. A landslide analysis is carried out to assess landslide probabilities based on data from a recent landslide risk classification study along the river Göta Älv. The suggested methodology is meant to be a supplement to either landslide risk assessment (LRA) or environmental risk assessment (ERA), providing quantitative estimates of the risks associated with landslide in contaminated sites. The proposed methodology can also act as a basis for communication and discussion, thereby contributing to intersectoral management solutions. From the case study it was found that the defined failures are governed primarily by the probability of a landslide occurring. The overall probabilities for failure are low; however, if a landslide occurs the probabilities of exceeding EQS are high and the probability of having at least a 10% increase in the contamination load
Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose.

PubMed

Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K; Abaidoo, Robert C; Dalsgaard, Anders; Hald, Tine

2017-12-01

The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10 -5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data. In some cases the difference was >2 orders of magnitude. All scenarios using genome copies met the 10 -4 DALY per person per year for consumption of vegetables irrigated with wastewater, although these results are considered to be highly conservative risk estimates. The fecal indicator conversion ratio model of stream-water and drain-water sources of wastewater achieved the 10 -6 DALY per person per year threshold, which tends to indicate an underestimation of health risk when compared to using genome copies for estimating the dose. Copyright © 2017 Elsevier B.V. All rights reserved.
Longitudinal study of mammographic density measures that predict breast cancer risk

PubMed Central

Krishnan, Kavitha; Baglietto, Laura; Stone, Jennifer; Simpson, Julie A; Severi, Gianluca; Evans, Christopher F; MacInnis, Robert J; Giles, Graham G; Apicella, Carmel; Hopper, John L

2016-01-01

Background After adjusting for age and body mass index (BMI), mammographic measures - dense area (DA), percent dense area (PDA) and non-dense area (NDA) - are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time. Methods We collected 4,320 mammograms (age range, 24-83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1-14). DA, PDA and NDA were measured using the Cumulus software and normalised using the Box-Cox method. Correlations in the normalised risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modelling of Gompertz curves. Results Mean normalised DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant from the mid 60s onwards. Mean normalised NDA increased non-linearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalised DA were 0.94, 0.93, 0.91, 0.91 and 0.91 for mammograms taken 2, 4, 6, 8 and 10 years apart, respectively. Similar correlations were estimated for the age and BMI adjusted normalized PDA and NDA. Conclusion The mammographic measures that predict breast cancer risk are highly correlated over time. Impact This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g. early 40s or even younger) and recommended appropriate screening and prevention strategies. PMID:28062399
Adjusted variable plots for Cox's proportional hazards regression model.

PubMed

Hall, C B; Zeger, S L; Bandeen-Roche, K J

1996-01-01

Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.
On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

NASA Astrophysics Data System (ADS)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

2017-10-01

With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.
Relative risk estimates from spatial and space-time scan statistics: Are they biased?

PubMed Central

Prates, Marcos O.; Kulldorff, Martin; Assunção, Renato M.

2014-01-01

The purely spatial and space-time scan statistics have been successfully used by many scientists to detect and evaluate geographical disease clusters. Although the scan statistic has high power in correctly identifying a cluster, no study has considered the estimates of the cluster relative risk in the detected cluster. In this paper we evaluate whether there is any bias on these estimated relative risks. Intuitively, one may expect that the estimated relative risks has upward bias, since the scan statistic cherry picks high rate areas to include in the cluster. We show that this intuition is correct for clusters with low statistical power, but with medium to high power the bias becomes negligible. The same behaviour is not observed for the prospective space-time scan statistic, where there is an increasing conservative downward bias of the relative risk as the power to detect the cluster increases. PMID:24639031
Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry

NASA Astrophysics Data System (ADS)

Pauwels, Ruben; Cockmartin, Lesley; Ivanauskaité, Deimante; Urbonienė, Ausra; Gavala, Sophia; Donta, Catherine; Tsiklakis, Kostas; Jacobs, Reinhilde; Bosmans, Hilde; Bogaerts, Ria; Horner, Keith; SEDENTEXCT Project Consortium, The

2014-07-01

The aim of this study was to measure entrance skin doses on patients undergoing cone-beam computed tomography (CBCT) examinations, to establish conversion factors between skin and organ doses, and to estimate cancer risk from CBCT exposures. 266 patients (age 8-83) were included, involving three imaging centres. CBCT scans were acquired using the SCANORA 3D (Soredex, Tuusula, Finland) and NewTom 9000 (QR, Verona, Italy). Eight thermoluminescent dosimeters were attached to the patient's skin at standardized locations. Using previously published organ dose estimations on various CBCTs with an anthropomorphic phantom, correlation factors to convert skin dose to organ doses were calculated and applied to estimate patient organ doses. The BEIR VII age- and gender-dependent dose-risk model was applied to estimate the lifetime attributable cancer risk. For the SCANORA 3D, average skin doses over the eight locations varied between 484 and 1788 µGy. For the NewTom 9000 the range was between 821 and 1686 µGy for Centre 1 and between 292 and 2325 µGy for Centre 2. Entrance skin dose measurements demonstrated the combined effect of exposure and patient factors on the dose. The lifetime attributable cancer risk, expressed as the probability to develop a radiation-induced cancer, varied between 2.7 per million (age >60) and 9.8 per million (age 8-11) with an average of 6.0 per million. On average, the risk for female patients was 40% higher. The estimated radiation risk was primarily influenced by the age at exposure and the gender, pointing out the continuing need for justification and optimization of CBCT exposures, with a specific focus on children.
An Evidenced-Based Approach for Estimating Decompression Sickness Risk in Aircraft Operations

NASA Technical Reports Server (NTRS)

Robinson, Ronald R.; Dervay, Joseph P.; Conkin, Johnny

1999-01-01

Estimating the risk of decompression Sickness (DCS) in aircraft operations remains a challenge, making the reduction of this risk through the development of operationally acceptable denitrogenation schedules difficult. In addition, the medical recommendations which are promulgated are often not supported by rigorous evaluation of the available data, but are instead arrived at by negotiation with the aircraft operations community, are adapted from other similar aircraft operations, or are based upon the opinion of the local medical community. We present a systematic approach for defining DCS risk in aircraft operations by analyzing the data available for a specific aircraft, flight profile, and aviator population. Once the risk of DCS in a particular aircraft operation is known, appropriate steps can be taken to reduce this risk to a level acceptable to the applicable aviation community. Using this technique will allow any aviation medical community to arrive at the best estimate of DCS risk for its specific mission and aviator population and will allow systematic reevaluation of the decisions regarding DCS risk reduction when additional data are available.
A decision model to estimate a risk threshold for venous thromboembolism prophylaxis in hospitalized medical patients.

PubMed

Le, P; Martinez, K A; Pappas, M A; Rothberg, M B

2017-06-01

Essentials Low risk patients don't require venous thromboembolism (VTE) prophylaxis; low risk is unquantified. We used a Markov model to estimate the risk threshold for VTE prophylaxis in medical inpatients. Prophylaxis was cost-effective for an average medical patient with a VTE risk of ≥ 1.0%. VTE prophylaxis can be personalized based on patient risk and age/life expectancy. Background Venous thromboembolism (VTE) is a common preventable condition in medical inpatients. Thromboprophylaxis is recommended for inpatients who are not at low risk of VTE, but no specific risk threshold for prophylaxis has been defined. Objective To determine a threshold for prophylaxis based on risk of VTE. Patients/Methods We constructed a decision model with a decision-tree following patients for 3 months after hospitalization, and a lifetime Markov model with 3-month cycles. The model tracked symptomatic deep vein thromboses and pulmonary emboli, bleeding events and heparin-induced thrombocytopenia. Long-term complications included recurrent VTE, post-thrombotic syndrome and pulmonary hypertension. For the base case, we considered medical inpatients aged 66 years, having a life expectancy of 13.5 years, VTE risk of 1.4% and bleeding risk of 2.7%. Patients received enoxaparin 40 mg day -1 for prophylaxis. Results Assuming a willingness-to-pay (WTP) threshold of $100 000/ quality-adjusted life year (QALY), prophylaxis was indicated for an average medical inpatient with a VTE risk of ≥ 1.0% up to 3 months after hospitalization. For the average patient, prophylaxis was not indicated when the bleeding risk was > 8.1%, the patient's age was > 73.4 years or the cost of enoxaparin exceeded $60/dose. If VTE risk was < 0.26% or bleeding risk was > 19%, the risks of prophylaxis outweighed benefits. The prophylaxis threshold was relatively insensitive to low-molecular-weight heparin cost and bleeding risk, but very sensitive to patient age and life expectancy. Conclusions The decision to
Nuclear Cataract Shows Significant Familial Aggregation in an Older Population after Adjustment for Possible Shared Environmental Factors

PubMed Central

Congdon, Nathan; Broman, Karl W.; Lai, Hong; Munoz, Beatriz; Bowie, Heidi; Gilber, Donna; Wojciechowski, Robert; Alston, Christine; West, Sheila K.

2011-01-01

Purpose To quantify the association between siblings in age-related nuclear cataract, after adjusting for known environmental and personal risk factors. Methods All participants (probands) in the Salisbury Eye Evaluation (SEE) project and their locally resident siblings underwent digital slit lamp photography and were administered a questionnaire to assess risk factors for cataract including: age, gender, lifetime sun exposure, smoking and diabetes history, and use of alcohol and medications such as estrogens and steroids. In addition, blood pressure, body mass index, and serum antioxidants were measured in all participants. Lens photographs were graded by trained observers masked to the subjects' identity, using the Wilmer Cataract Grading System. The odds ratio for siblings for affectedness with nuclear cataract and the sibling correlation of nuclear cataract grade, after adjusting for covariates, were estimated with generalized estimating equations. Results Among 307 probands (mean age, 77.6 ± 4.5 years) and 434 full siblings (mean age, 72.4 ± 7.4 years), the average sibship size was 2.7 per family. After adjustment for covariates, the probability of development of nuclear cataract was significantly increased (odds ratio [OR] = 2.07, 95% confidence interval [CI], 1.30–3.30) among individuals with a sibling with nuclear cataract (nuclear grade ≥ 3.0). The final fitted model indicated a magnitude of heritability for nuclear cataract of 35.6% (95% CI: 21.0%–50.3%) after adjustment for the covariates. Conclusions Findings in this study are consistent with a genetic effect for age-related nuclear cataract, a common and clinically significant form of lens opacity. PMID:15223793
Albuminuria and Rapid Loss of GFR and Risk of New Hip and Pelvic Fractures

PubMed Central

Gao, Peggy; Clase, Catherine M.; Mente, Andrew; Mann, Johannes F.E.; Sleight, Peter; Yusuf, Salim; Teo, Koon K.

2013-01-01

Summary Background and objectives The microvascular circulation plays an important role in bone health. This study examines whether albuminuria, a marker of renal microvascular disease, is associated with incident hip and pelvic fractures. Design, setting, participants, & measurements This study reanalyzed data from the Ongoing Telmisartan Alone and in combination with Ramipril Global End Point Trial/Telmisartan Randomized Assessment Study in Angiotensin-Converting Enzyme Intolerant Subjects with Cardiovascular Disease trials, which examined the impact of renin angiotensin system blockade on cardiovascular outcomes (n=28,601). Albuminuria was defined as an albumin-to-creatinine ratio≥30 mg/g (n=4597). Cox proportional hazards models were used to determine the association of albuminuria with fracture risk adjusted for known risk factors for fractures, estimated GFR, and rapid decline in estimated GFR (≥5%/yr). Results There were 276 hip and pelvic fractures during a mean of 4.6 years of follow-up. Participants with baseline albuminuria had a significantly increased risk of fracture compared with participants without albuminuria (unadjusted hazard ratio=1.62 [1.22, 2.15], P<0.001; adjusted hazard ratio=1.36 [1.01, 1.84], P=0.05). A dose-dependent relationship was observed, with macroalbuminuria having a large fracture risk (unadjusted hazard ratio=2.01 [1.21, 3.35], P=0.007; adjusted hazard ratio=1.71 [1.007, 2.91], P=0.05) and microalbuminuria associating with borderline or no statistical significance (unadjusted hazard ratio=1.52 [1.10, 2.09], P=0.01; adjusted hazard ratio=1.28 [0.92, 1.78], P=0.15). Estimated GFR was not a predictor of fracture in any model, but rapid loss of estimated GFR over the first 2 years of follow-up predicted subsequent fracture (adjusted hazard ratio=1.47 [1.05, 2.04], P=0.02). Conclusions Albuminuria, especially macroalbuminuria, and rapid decline of estimated GFR predict hip and pelvic fractures. These findings support a
Meta-analysis of breast cancer mortality benefit and overdiagnosis adjusted for adherence: improving information on the effects of attending screening mammography

PubMed Central

Jacklyn, Gemma; Glasziou, Paul; Macaskill, Petra; Barratt, Alexandra

2016-01-01

Background: Women require information about the impact of regularly attending screening mammography on breast cancer mortality and overdiagnosis to make informed decisions. To provide this information we aimed to meta-analyse randomised controlled trials adjusted for adherence to the trial protocol. Methods: Nine screening mammography trials used in the Independent UK Breast Screening Report were selected. Extending an existing approach to adjust intention-to-treat (ITT) estimates for less than 100% adherence rates, we conducted a random-effects meta-analysis. This produced a combined deattenuated prevented fraction and a combined deattenuated percentage risk of overdiagnosis. Results: In women aged 39–75 years invited to screen, the prevented fraction of breast cancer mortality at 13-year follow-up was 0.22 (95% CI 0.15–0.28) and it increased to 0.30 (95% CI 0.18–0.42) with deattenuation. In women aged 40–69 years invited to screen, the ITT percentage risk of overdiagnosis during the screening period was 19.0% (95% CI 15.2–22.7%), deattenuation increased this to 29.7% (95% CI 17.8–41.5%). Conclusions: Adjustment for nonadherence increased the size of the mortality benefit and risk of overdiagnosis by up to 50%. These estimates are more appropriate when developing quantitative information to support individual decisions about attending screening mammography. PMID:27124337
Cable Overheating Risk Warning Method Based on Impedance Parameter Estimation in Distribution Network

NASA Astrophysics Data System (ADS)

Yu, Zhang; Xiaohui, Song; Jianfang, Li; Fei, Gao

2017-05-01

Cable overheating will lead to the cable insulation level reducing, speed up the cable insulation aging, even easy to cause short circuit faults. Cable overheating risk identification and warning is nessesary for distribution network operators. Cable overheating risk warning method based on impedance parameter estimation is proposed in the paper to improve the safty and reliability operation of distribution network. Firstly, cable impedance estimation model is established by using least square method based on the data from distribiton SCADA system to improve the impedance parameter estimation accuracy. Secondly, calculate the threshold value of cable impedance based on the historical data and the forecast value of cable impedance based on the forecasting data in future from distribiton SCADA system. Thirdly, establish risks warning rules library of cable overheating, calculate the cable impedance forecast value and analysis the change rate of impedance, and then warn the overheating risk of cable line based on the overheating risk warning rules library according to the variation relationship between impedance and line temperature rise. Overheating risk warning method is simulated in the paper. The simulation results shows that the method can identify the imedance and forecast the temperature rise of cable line in distribution network accurately. The result of overheating risk warning can provide decision basis for operation maintenance and repair.
On the estimation of risk associated with an attenuation prediction

NASA Technical Reports Server (NTRS)

Crane, R. K.

1992-01-01

Viewgraphs from a presentation on the estimation of risk associated with an attenuation prediction is presented. Topics covered include: link failure - attenuation exceeding a specified threshold for a specified time interval or intervals; risk - the probability of one or more failures during the lifetime of the link or during a specified accounting interval; the problem - modeling the probability of attenuation by rainfall to provide a prediction of the attenuation threshold for a specified risk; and an accounting for the inadequacy of a model or models.
Estimation of the burden of cardiovascular disease attributable to modifiable risk factors and cost-effectiveness analysis of preventative interventions to reduce this burden in Argentina

PubMed Central

2010-01-01

Background Cardiovascular disease (CVD) is the primary cause of mortality and morbidity in Argentina representing 34.2% of deaths and 12.6% of potential years of life lost (PYLL). The aim of the study was to estimate the burden of acute coronary heart disease (CHD) and stroke and the cost-effectiveness of preventative population-based and clinical interventions. Methods An epidemiological model was built incorporating prevalence and distribution of high blood pressure, high cholesterol, hyperglycemia, overweight and obesity, smoking, and physical inactivity, obtained from the Argentine Survey of Risk Factors dataset. Population Attributable Fraction (PAF) of each risk factor was estimated using relative risks from international sources. Total fatal and non-fatal events, PYLL and Disability Adjusted Life Years (DALY) were estimated. Costs of event were calculated from local utilization databases and expressed in international dollars (I$). Incremental cost-effectiveness ratios (ICER) were estimated for six interventions: reducing salt in bread, mass media campaign to promote tobacco cessation, pharmacological therapy of high blood pressure, pharmacological therapy of high cholesterol, tobacco cessation therapy with bupropion, and a multidrug strategy for people with an estimated absolute risk > 20% in 10 years. Results An estimated total of 611,635 DALY was lost due to acute CHD and stroke for 2005. Modifiable risk factors explained 71.1% of DALY and more than 80% of events. Two interventions were cost-saving: lowering salt intake in the population through reducing salt in bread and multidrug therapy targeted to persons with an absolute risk above 20% in 10 years; three interventions had very acceptable ICERs: drug therapy for high blood pressure in hypertensive patients not yet undergoing treatment (I$ 2,908 per DALY saved), mass media campaign to promote tobacco cessation amongst smokers (I$ 3,186 per DALY saved), and lowering cholesterol with statin drug therapy
Geostatistical risk estimation at waste disposal sites in the presence of hot spots.

PubMed

Komnitsas, Kostas; Modis, Kostas

2009-05-30

The present paper aims to estimate risk by using geostatistics at the wider coal mining/waste disposal site of Belkovskaya, Tula region, in Russia. In this area the presence of hot spots causes a spatial trend in the mean value of the random field and a non-Gaussian data distribution. Prior to application of geostatistics, subtraction of trend and appropriate smoothing and transformation of the data into a Gaussian form were carried out; risk maps were then generated for the wider study area in order to assess the probability of exceeding risk thresholds. Finally, the present paper discusses the need for homogenization of soil risk thresholds regarding hazardous elements that will enhance reliability of risk estimation and enable application of appropriate rehabilitation actions in contaminated areas.

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