Prediction of vesicoureteral reflux after a first febrile urinary tract infection in children: validation of a clinical decision rule.

PubMed

Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M

2006-03-01

To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (< or =0 and < or =5) to predict respectively, all-grade or grade > or =3 VUR, were calculated. A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all-grade VUR, and 93% sensitivity and 13% specificity for grade > or =3 VUR. Some methodological weaknesses explain this lack of reproducibility. The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest.

Prediction of vesicoureteral reflux after a first febrile urinary tract infection in children: validation of a clinical decision rule

PubMed Central

Leroy, S; Marc, E; Adamsbaum, C; Gendrel, D; Bréart, G; Chalumeau, M

2006-01-01

Aims To test the reproducibility of a highly sensitive clinical decision rule proposed to predict vesicoureteral reflux (VUR) after a first febrile urinary tract infection in children. This rule combines clinical (family history of uropathology, male gender, young age), biological (raised C reactive protein), and radiological (urinary tract dilation on renal ultrasound) predictors in a score, and provides 100% sensitivity. Methods A retrospective hospital based cohort study included all children, 1 month to 4 years old, with a first febrile urinary tract infection. The sensitivities and specificities of the rule at the two previously proposed score thresholds (⩽0 and ⩽5) to predict respectively, all‐grade or grade ⩾3 VUR, were calculated. Results A total of 149 children were included. VUR prevalence was 25%. The rule yielded 100% sensitivity and 3% specificity for all‐grade VUR, and 93% sensitivity and 13% specificity for grade ⩾3 VUR. Some methodological weaknesses explain this lack of reproducibility. Conclusions The reproducibility of the previously proposed decision rule was poor and its potential contribution to clinical management of children with febrile urinary tract infection seems to be modest. PMID:15890693

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

PubMed Central

DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests.

PubMed

Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A

2015-10-01

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sideline coverage: when to get radiographs? A review of clinical decision tools.

PubMed

Gould, Sara J; Cardone, Dennis A; Munyak, John; Underwood, Philipp J; Gould, Stephen A

2014-05-01

Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Retrospective literature review. Level 4. The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines.

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed

Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

Evaluation of decision rules for identifying low bone density in postmenopausal African-American women.

PubMed Central

Wallace, Lorraine Silver; Ballard, Joyce E.; Holiday, David; Turner, Lori W.; Keenum, Amy J.; Pearman, Cynthia M.

2004-01-01

OBJECTIVE: While African-American women tend to have greater bone mineral density (BMD) than caucasian women, they are still at risk of developing osteoporosis later in life. Clinical decision rules (i.e., algorithms) have been developed to assist clinicians identify women at greatest risk of low BMD. However, such tools have only been validated in caucasian and Asian populations. Accordingly, the objective of this study was to compare the performance of five clinical decision rules in identifying postmenopausal African-American women at greatest risk for low femoral BMD. METHODOLOGY: One hundred-seventy-four (n=174) postmenopausal African-American women completed a valid and reliable oral questionnaire to assess lifestyle characteristics, and completed height and weight measures. BMD at the femoral neck was measured via dual energy x-ray absorptiometry (DXA). We calculated sensitivity, specificity, positive predictive value, and negative predictive value for identifying African-American women with low BMD (T-Score < or = -2.0 SD) using five clinical decision rules: Age, Body Size, No Estrogen (ABONE), Osteoporosis Risk Assessment Instrument (ORAI), Osteoporosis Self-Assessment Tool (OST), Simple Calculated Osteoporosis Risk Estimation (SCORE), and body weight less than 70 kg. RESULTS: Approximately 30% of African-American women had low BMD, half of whom had osteoporosis (BMD T-Score < or = -2.5 SD). Sensitivity for identifying women with a low BMD (T-Score < or = -2.0 SD) ranged from 65.57-83.61%, while specificity ranged from 53.85-78.85%. Positive predictive values ranged from 80.95-87.91%, while negative predictive values ranged from 48.44-58.33%. CONCLUSION: Our data suggest that the clinical decision rules analyzed in this study have some usefulness for identifying postmenopausal African-American women with low BMD. However, there is a need to establish cut-points for these clinical decision rules in a larger, more diverse sample of African-American women. PMID:15040510

Validation of the Ottawa Knee Rules.

PubMed

Emparanza, J I; Aginaga, J R

2001-10-01

We sought to validate the Ottawa Knee Rules for determining the need for radiography in patients with acute knee injury. A prospective cohort study was performed in emergency departments of 11 hospitals of the Osakidetza-Basque Country Health Service. The patient population was composed of a convenience sample of 1,522 eligible adults of 2,315 patients with acute knee injuries. The attending emergency physicians assessed each patient for standardized clinical variables and determined the need for radiography according to the decision rule. Radiography was performed in each patient, irrespective of the determination of the rule, after clinical evaluation findings were recorded. The rule was assessed for the ability to correctly identify fracture of the knee. The decision rule had a sensitivity of 1.0 (95% confidence interval [CI] 0.96 to 1.0), identifying 89 patients with clinically important fractures. The potential reduction in use of radiography was estimated to be 49%. The probability of fracture, if the decision rules were negative, is estimated to be 0% (95% CI 0% to 0.5%). Prospective validation has shown the Ottawa Knee Rules to be 100% sensitive for identifying fractures of the knee and to have the potential to allow physicians to reduce the use of radiography in patients with acute knee injuries.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed Central

Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser. Images Figure 1 PMID:10566470

Acute knee injuries: use of decision rules for selective radiograph ordering.

PubMed

Tandeter, H B; Shvartzman, P; Stevens, Max A

1999-12-01

Family physicians often encounter patients with acute knee trauma. Radiographs of injured knees are commonly ordered, even though fractures are found in only 6 percent of such patients and emergency department physicians can usually discriminate clinically between fracture and nonfracture. Decision rules have been developed to reduce the unnecessary use of radiologic studies in patients with acute knee injury. The Ottawa knee rules and the Pittsburgh decision rules are the latest guidelines for the selective use of radiographs in knee trauma. Application of these rules may lead to a more efficient evaluation of knee injuries and a reduction in health costs without an increase in adverse outcomes.

Evaluation of a multi-arm multi-stage Bayesian design for phase II drug selection trials - an example in hemato-oncology.

PubMed

Jacob, Louis; Uvarova, Maria; Boulet, Sandrine; Begaj, Inva; Chevret, Sylvie

2016-06-02

Multi-Arm Multi-Stage designs aim at comparing several new treatments to a common reference, in order to select or drop any treatment arm to move forward when such evidence already exists based on interim analyses. We redesigned a Bayesian adaptive design initially proposed for dose-finding, focusing our interest in the comparison of multiple experimental drugs to a control on a binary criterion measure. We redesigned a phase II clinical trial that randomly allocates patients across three (one control and two experimental) treatment arms to assess dropping decision rules. We were interested in dropping any arm due to futility, either based on historical control rate (first rule) or comparison across arms (second rule), and in stopping experimental arm due to its ability to reach a sufficient response rate (third rule), using the difference of response probabilities in Bayes binomial trials between the treated and control as a measure of treatment benefit. Simulations were then conducted to investigate the decision operating characteristics under a variety of plausible scenarios, as a function of the decision thresholds. Our findings suggest that one experimental treatment was less efficient than the control and could have been dropped from the trial based on a sample of approximately 20 instead of 40 patients. In the simulation study, stopping decisions were reached sooner for the first rule than for the second rule, with close mean estimates of response rates and small bias. According to the decision threshold, the mean sample size to detect the required 0.15 absolute benefit ranged from 63 to 70 (rule 3) with false negative rates of less than 2 % (rule 1) up to 6 % (rule 2). In contrast, detecting a 0.15 inferiority in response rates required a sample size ranging on average from 23 to 35 (rules 1 and 2, respectively) with a false positive rate ranging from 3.6 to 0.6 % (rule 3). Adaptive trial design is a good way to improve clinical trials. It allows removing ineffective drugs and reducing the trial sample size, while maintaining unbiased estimates. Decision thresholds can be set according to predefined fixed error decision rates. ClinicalTrials.gov Identifier: NCT01342692 .

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

PubMed

Wright, Adam; Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care.

PubMed

Sesen, M Berkan; Peake, Michael D; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

2014-09-06

Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.

27 The DiPEP (Diagnosis of PE in Pregnancy) study: can clinical assessment, d-dimer or chest x-ray be used to select pregnant or postpartum women with suspected PE for diagnostic imaging?

PubMed

Goodacre, Steve; Horspool, Kimberley; Nelson-Piercy, Catherine; Knight, Marian; Shephard, Neil; Lecky, Fiona; Thomas, Steven; Hunt, Beverley; Fuller, Gordon

2017-12-01

To determine whether clinical features (in the form of a clinical decision rule) or d-dimer can be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. Observational cohort study augmented with additional cases. Consultant-led maternity units participating in the UK Obstetric Surveillance System (UKOSS) and emergency departments and maternity units at eleven prospectively recruiting sites. 198 pregnant or postpartum women with diagnosed PE identified through UKOSS and 324 pregnant or postpartum women with suspected PE from prospectively recruiting sites. Data were collected relating to clinical features, elements of clinical decision rules, d-dimer measurements, diagnostic imaging, treatment for PE and adverse outcomes. Women were classified as having or not having PE on the basis of diagnostic imaging, treatment and subsequent adverse outcomes. Primary analysis was limited to women with conclusive diagnostic imaging. Secondary analyses included women with clinically diagnosed or ruled out PE. The primary analysis included 181 women with PE and 259 without. Most clinical features showed no association with PE. The only exceptions were number of previous pregnancies over 24 weeks (p=0.017), no varicose veins (p=0.045), no recent long haul travel (p=0.006), recent surgery including caesarean section (p=0.001), increased temperature (p=0.003), low oxygen saturation (p<0.001), PE-related chest x-ray abnormality (p=0.01) and other chest x-ray abnormality (p=0.001).Clinical decision rules had areas under the receiver-operator characteristic curve ranging from 0.577 to 0.732. No clinically useful threshold for decision-making was identified for any rule. The sensitivities and specificities of d-dimer were 88.4% and 8.8% using the standard laboratory threshold and 69.8% and 32.8% using a pregnancy-specific threshold. Clinical decision rules, d-dimer and chest x-ray should not be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. © 2017, 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.

Sideline Coverage

PubMed Central

Gould, Sara J.; Cardone, Dennis A.; Munyak, John; Underwood, Philipp J.; Gould, Stephen A.

2014-01-01

Context: Sidelines coverage presents unique challenges in the evaluation of injured athletes. Health care providers may be confronted with the question of when to obtain radiographs following an injury. Given that most sidelines coverage occurs outside the elite level, radiographs are not readily available at the time of injury, and the decision of when to send a player for radiographs must be made based on physical examination. Clinical tools have been developed to aid in identifying injuries that are likely to result in radiographically important fractures or dislocations. Evidence Acquisition: A search for the keywords x-ray and decision rule along with the anatomic locations shoulder, elbow, wrist, knee, and ankle was performed using the PubMed database. No limits were set regarding year of publication. We selected meta-analyses, randomized controlled trials, and survey results. Our selection focused on the largest, most well-studied published reports. We also attempted to include studies that reported the application of the rules to the field of sports medicine. Study Design: Retrospective literature review. Level of Evidence: Level 4. Results: The Ottawa Foot and Ankle Rules have been validated and implemented and are appropriate for use in both pediatric and adult populations. The Ottawa Knee Rules have been widely studied, validated, and accepted for evaluation of knee injuries. There are promising studies of decision rules for clinically important fractures of the wrist, but these studies have not been validated. The elbow has been evaluated with good outcomes via the elbow extension test, which has been validated in both single and multicenter studies. Currently, there are no reliable clinical decision tools for traumatic sports injuries to the shoulder to aid in the decision of when to obtain radiographs. Conclusion: Clinical decision tools have been developed to aid in the diagnosis and management of injuries commonly sustained during sporting events. Tools that have been appropriately validated in populations outside the initial study population can assist sports medicine physicians in the decision of when to get radiographs from the sidelines. PMID:24790698

Systematic Analysis of the Decision Rules of Traditional Chinese Medicine

PubMed Central

Bin-Rong, Ma; Xi-Yuan, Jiang; Su-Ming, Liso; Huai-ning, Zhu; Xiu-ru, Lin

1981-01-01

Chinese traditional medicine has evolved over many centuries, and has accumulated a body of observed relationships between symptoms, signs and prognoses, and the efficacy of alternative treatments and prescriptions. With the assistance of a computer-based clinical data base for recording the diagnostic and therapeutic practice of skilled practitioners of Chinese traditional medicine, a systematic program is being conducted to identify and define the clinical decision-making rules that underlie current practice.

[Clinical economics: a concept to optimize healthcare services].

PubMed

Porzsolt, F; Bauer, K; Henne-Bruns, D

2012-03-01

Clinical economics strives to support healthcare decisions by economic considerations. Making economic decisions does not mean saving costs but rather comparing the gained added value with the burden which has to be accepted. The necessary rules are offered in various disciplines, such as economy, epidemiology and ethics. Medical doctors have recognized these rules but are not applying them in daily clinical practice. This lacking orientation leads to preventable errors. Examples of these errors are shown for diagnosis, screening, prognosis and therapy. As these errors can be prevented by application of clinical economic principles the possible consequences for optimization of healthcare are discussed.

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record

PubMed Central

Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Background Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. Objective To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. Study design and methods We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100 000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100 000 records to assess its accuracy. Results Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100 000 randomly selected patients showed high sensitivity (range: 62.8–100.0%) and positive predictive value (range: 79.8–99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. Conclusion We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts. PMID:21613643

Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

Construction of a clinical decision support system for undergoing surgery based on domain ontology and rules reasoning.

PubMed

Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

2014-05-01

To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé-Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia.

Performance of Thirteen Clinical Rules to Distinguish Bacterial and Presumed Viral Meningitis in Vietnamese Children

PubMed Central

Huy, Nguyen Tien; Thao, Nguyen Thanh Hong; Tuan, Nguyen Anh; Khiem, Nguyen Tuan; Moore, Christopher C.; Thi Ngoc Diep, Doan; Hirayama, Kenji

2012-01-01

Background and Purpose Successful outcomes from bacterial meningitis require rapid antibiotic treatment; however, unnecessary treatment of viral meningitis may lead to increased toxicities and expense. Thus, improved diagnostics are required to maximize treatment and minimize side effects and cost. Thirteen clinical decision rules have been reported to identify bacterial from viral meningitis. However, few rules have been tested and compared in a single study, while several rules are yet to be tested by independent researchers or in pediatric populations. Thus, simultaneous test and comparison of these rules are required to enable clinicians to select an optimal diagnostic rule for bacterial meningitis in settings and populations similar to ours. Methods A retrospective cross-sectional study was conducted at the Infectious Department of Pediatric Hospital Number 1, Ho Chi Minh City, Vietnam. The performance of the clinical rules was evaluated by area under a receiver operating characteristic curve (ROC-AUC) using the method of DeLong and McNemar test for specificity comparison. Results Our study included 129 patients, of whom 80 had bacterial meningitis and 49 had presumed viral meningitis. Spanos's rule had the highest AUC at 0.938 but was not significantly greater than other rules. No rule provided 100% sensitivity with a specificity higher than 50%. Based on our calculation of theoretical sensitivity and specificity, we suggest that a perfect rule requires at least four independent variables that posses both sensitivity and specificity higher than 85–90%. Conclusions No clinical decision rules provided an acceptable specificity (>50%) with 100% sensitivity when applying our data set in children. More studies in Vietnam and developing countries are required to develop and/or validate clinical rules and more very good biomarkers are required to develop such a perfect rule. PMID:23209715

Performance of thirteen clinical rules to distinguish bacterial and presumed viral meningitis in Vietnamese children.

PubMed

Huy, Nguyen Tien; Thao, Nguyen Thanh Hong; Tuan, Nguyen Anh; Khiem, Nguyen Tuan; Moore, Christopher C; Thi Ngoc Diep, Doan; Hirayama, Kenji

2012-01-01

Successful outcomes from bacterial meningitis require rapid antibiotic treatment; however, unnecessary treatment of viral meningitis may lead to increased toxicities and expense. Thus, improved diagnostics are required to maximize treatment and minimize side effects and cost. Thirteen clinical decision rules have been reported to identify bacterial from viral meningitis. However, few rules have been tested and compared in a single study, while several rules are yet to be tested by independent researchers or in pediatric populations. Thus, simultaneous test and comparison of these rules are required to enable clinicians to select an optimal diagnostic rule for bacterial meningitis in settings and populations similar to ours. A retrospective cross-sectional study was conducted at the Infectious Department of Pediatric Hospital Number 1, Ho Chi Minh City, Vietnam. The performance of the clinical rules was evaluated by area under a receiver operating characteristic curve (ROC-AUC) using the method of DeLong and McNemar test for specificity comparison. Our study included 129 patients, of whom 80 had bacterial meningitis and 49 had presumed viral meningitis. Spanos's rule had the highest AUC at 0.938 but was not significantly greater than other rules. No rule provided 100% sensitivity with a specificity higher than 50%. Based on our calculation of theoretical sensitivity and specificity, we suggest that a perfect rule requires at least four independent variables that posses both sensitivity and specificity higher than 85-90%. No clinical decision rules provided an acceptable specificity (>50%) with 100% sensitivity when applying our data set in children. More studies in Vietnam and developing countries are required to develop and/or validate clinical rules and more very good biomarkers are required to develop such a perfect rule.

Implementation of adapted PECARN decision rule for children with minor head injury in the pediatric emergency department.

PubMed

Bressan, Silvia; Romanato, Sabrina; Mion, Teresa; Zanconato, Stefania; Da Dalt, Liviana

2012-07-01

Of the currently published clinical decision rules for the management of minor head injury (MHI) in children, the Pediatric Emergency Care Applied Research Network (PECARN) rule, derived and validated in a large multicenter prospective study cohort, with high methodologic standards, appears to be the best clinical decision rule to accurately identify children at very low risk of clinically important traumatic brain injuries (ciTBI) in the pediatric emergency department (PED). This study describes the implementation of an adapted version of the PECARN rule in a tertiary care academic PED in Italy and evaluates implementation success, in terms of medical staff adherence and satisfaction, as well as its effects on clinical practice. The adapted PECARN decision rule algorithms for children (one for those younger than 2 years and one for those older than 2 years) were actively implemented in the PED of Padova, Italy, for a 6-month testing period. Adherence and satisfaction of medical staff to the new rule were calculated. Data from 356 visits for MHI during PECARN rule implementation and those of 288 patients attending the PED for MHI in the previous 6 months were compared for changes in computed tomography (CT) scan rate, ciTBI rate (defined as death, neurosurgery, intubation for longer than 24 hours, or hospital admission at least for two nights associated with TBI) and return visits for symptoms or signs potentially related to MHI. The safety and efficacy of the adapted PECARN rule in clinical practice were also calculated. Adherence to the adapted PECARN rule was 93.5%. The percentage of medical staff satisfied with the new rule, in terms of usefulness and ease of use for rapid decision-making, was significantly higher (96% vs. 51%, p<0.0001) compared to the previous, more complex, internal guideline. CT scan was performed in 30 patients (8.4%, 95% confidence interval [CI]=6% to 11.8%) in the implementation period versus 21 patients (7.3%, 95% CI=4.8% to 10.9%) before implementation. A ciTBI occurred in three children (0.8%, 95% CI=0.3 to 2.5) during the implementation period and in two children (0.7%, 95% CI=0.2 to 2.5) in the prior 6 months. There were five return visits (1.4%) postimplementation and seven (2.4%) before implementation (p=0.506). The safety of use of the adapted PECARN rule in clinical practice was 100% (95% CI=36.8 to 100; three of three patients with ciTBI who received CT scan at first evaluation), while efficacy was 92.3% (95% CI=89 to 95; 326 of 353 patients without ciTBI who did not receive a CT scan). The adapted PECARN rule was successfully implemented in an Italian tertiary care academic PED, achieving high adherence and satisfaction of medical staff. Its use determined a low CT scan rate that was unchanged compared to previous clinical practice and showed an optimal safety and high efficacy profile. Strict monitoring is mandatory to evaluate the long-lasting benefit in patient care and/or resource utilization. © 2012 by the Society for Academic Emergency Medicine.

Robot decisions: on the importance of virtuous judgment in clinical decision making.

PubMed

Gelhaus, Petra

2011-10-01

The aim of this article is to argue for the necessity of emotional professional virtues in the understanding of good clinical practice. This understanding is required for a proper balance of capacities in medical education and further education of physicians. For this reason an ideal physician, incarnating the required virtues, skills and knowledge is compared with a non-emotional robot that is bound to moral rules. This fictive confrontation is meant to clarify why certain demands on the personality of the physician are justified, in addition to a rule- and principle-based moral orientation and biomedical knowledge and skills. Philosophical analysis of thought experiments inspired by science fiction literature by Isaac Asimov. Although prima facie a rule-oriented robot seems more reliable and trustworthy, the complexity of clinical judgment is not met by an encompassing and never contradictory set of rules from which one could logically derive decisions. There are different ways how the robot could still work, but at the cost of the predictability of its behaviour and its moral orientation. In comparison, a virtuous human doctor who is also bound to these rules, although less strictly, will more reliably keep at moral objectives, be understandable, be more flexible in case the rules come to their limits, and will be more predictable in these critical situations. Apart from these advantages of the virtuous human doctor referring to her own person, the most problematic deficit of the robot is its lacking deeper understanding of the inner mental events of patients which makes good contact, good communication and good influence impossible. Although an infallibly rule-oriented robot seems more reliable at first view, in situations that require complex decisions like clinical practice the agency of a moral human person is more trustworthy. Furthermore, the understanding of the patient's emotions must remain insufficient for a non-emotional, non-human being. Because these are crucial preconditions for good clinical practice, enough attention should be given to develop these virtues and emotional skills, in addition to the usual attention on knowledge, technical skills and the obedience to moral rules and principles. © 2011 Blackwell Publishing Ltd.

Clinical prediction rule for delayed hemothorax after minor thoracic injury: a multicentre derivation and validation study

PubMed Central

Émond, Marcel; Guimont, Chantal; Chauny, Jean-Marc; Daoust, Raoul; Bergeron, Éric; Vanier, Laurent; Moore, Lynne; Plourde, Miville; Kuimi, Batomen; Boucher, Valérie; Allain-Boulé, Nadine; Le Sage, Natalie

2017-01-01

Background: About 75% of patients with minor thoracic injury are discharged after an emergency department visit. However, complications such as delayed hemothorax can occur. We sought to derive and validate a clinical decision rule to predict hemothorax in patients discharged from the emergency department. Methods: We conducted a 6-year prospective cohort study in 4 university-affiliated emergency departments. Patients aged 16 years or older presenting with a minor thoracic injury were assessed at 5 time points (initial visit and 7, 14, 30 and 90 d after the injury). Radiologists' reports were reviewed for the presence of hemothorax. We used log-binomial regression models to identify predictors of hemothorax. Results: A total of 1382 patients were included: 830 in the derivation phase and 552 in the validation phase. Of these, 151 (10.9%) had hemothorax at the 14-day follow-up. Patients 65 years of age or older represented 25.3% (210/830) and 23.7% (131/552) of the derivation and validation cohorts, respectively. The final clinical decision rule included a combination of age (> 70 yr, 2 points; 45-70 yr, 1 point), fracture of any high to mid thorax rib (ribs 3-9, 2 points) and presence of 3 or more rib fractures (1 point). Twenty (30.8%) of the 65 high-risk patients (score ≥ 4) experienced hemothorax during the follow-up period. The clinical decision rule had a high specificity (90.7%, 95% confidence interval 87.7%-93.1%) in this high-risk group, thus guiding appropriate post-emergency care. Interpretation: One patient out of every 10 presented with delayed hemothorax after discharge from the emergency department. Implementation of this validated clinical decision rule for minor thoracic injury could guide emergency discharge plans. PMID:28611156

Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies.

PubMed

Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel

2015-02-22

Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.

The predictive value of self-report questions in a clinical decision rule for pediatric lead poisoning screening.

PubMed

Kaplowitz, Stan A; Perlstadt, Harry; D'Onofrio, Gail; Melnick, Edward R; Baum, Carl R; Kirrane, Barbara M; Post, Lori A

2012-01-01

We derived a clinical decision rule for determining which young children need testing for lead poisoning. We developed an equation that combines lead exposure self-report questions with the child's census-block housing and socioeconomic characteristics, personal demographic characteristics, and Medicaid status. This equation better predicts elevated blood lead level (EBLL) than one using ZIP code and Medicaid status. A survey regarding potential lead exposure was administered from October 2001 to January 2003 to Michigan parents at pediatric clinics (n=3,396). These self-report survey data were linked to a statewide clinical registry of blood lead level (BLL) tests. Sensitivity and specificity were calculated and then used to estimate the cost-effectiveness of the equation. The census-block group prediction equation explained 18.1% of the variance in BLLs. Replacing block group characteristics with the self-report questions and dichotomized ZIP code risk explained only 12.6% of the variance. Adding three self-report questions to the census-block group model increased the variance explained to 19.9% and increased specificity with no loss in sensitivity in detecting EBLLs of ≥ 10 micrograms per deciliter. Relying solely on self-reports of lead exposure predicted BLL less effectively than the block group model. However, adding three of 13 self-report questions to our clinical decision rule significantly improved prediction of which children require a BLL test. Using the equation as the clinical decision rule would annually eliminate more than 7,200 unnecessary tests in Michigan and save more than $220,000.

Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care.

PubMed

Verbakel, Jan Y; Lemiengre, Marieke B; De Burghgraeve, Tine; De Sutter, An; Aertgeerts, Bert; Bullens, Dominique M A; Shinkins, Bethany; Van den Bruel, Ann; Buntinx, Frank

2015-08-07

Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. Diagnostic accuracy study validating a clinical prediction rule. Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. Physicians were asked to score the decision tree in every child. The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out. NCT02024282. 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.

Use of clinical prediction rules and D-dimer tests in the diagnostic management of pregnant patients with suspected acute pulmonary embolism.

PubMed

Van der Pol, L M; Mairuhu, A T A; Tromeur, C; Couturaud, F; Huisman, M V; Klok, F A

2017-03-01

Because pregnant women have an increased risk of venous thromboembolism (VTE) and at the same time normal pregnancy is associated with symptoms, mimicking those present in the setting of acute pulmonary embolism (PE), the latter diagnosis is frequently suspected in this patient category. Since imaging tests expose both mother and foetus to ionizing radiation, the ability to rule out PE based on non-radiological diagnostic tests is of paramount importance. However, clinical decision rules have only been scarcely evaluated in the pregnant population with suspected PE, while D-dimer levels lose diagnostic accuracy due to a physiological increase during normal pregnancy. Consequently, clinical guidelines provide contradicting and weak recommendations on this subject and the optimal diagnostic strategy remains highly debated. With this systematic review, we aimed to summarize current evidence on the safety and efficacy of clinical decision rules and biomarkers used in the diagnostic management of suspected acute PE in pregnant patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Healthcare provider perceptions of clinical prediction rules

PubMed Central

Richardson, Safiya; Khan, Sundas; McCullagh, Lauren; Kline, Myriam; Mann, Devin; McGinn, Thomas

2015-01-01

Objectives To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. Setting The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Participants Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. Primary and secondary outcome measures The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Results Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores. Conclusions Healthcare providers describe clear preferences for certain clinical prediction rules, based on medical specialty. PMID:26338684

[The Amsterdam wrist rules: the multicenter prospective derivation and external validation of a clinical decision rule for the use of radiography in acute wrist trauma].

PubMed

Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M S H Suzan; Maas, Mario; Jager, L C Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J C Carel; Schep, Niels W L

2016-01-01

Although only 39% of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95% CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98% (95% CI: 95-99%) and 21% (95% CI: 15%-28). The negative predictive value was 90% (95% CI: 81-99%). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs.

Diagnostic games: from adequate formalization of clinical experience to structure discovery.

PubMed

Shifrin, Michael A; Kasparova, Eva I

2008-01-01

A method of obtaining well-founded and reproducible results in clinical decision making is presented. It is based on "diagnostic games", a procedure of elicitation and formalization of experts' knowledge and experience. The use of this procedure allows formulating decision rules in the terms of an adequate language, that are both unambiguous and clinically clear.

Accuracy of PECARN, CATCH, and CHALICE head injury decision rules in children: a prospective cohort study.

PubMed

Babl, Franz E; Borland, Meredith L; Phillips, Natalie; Kochar, Amit; Dalton, Sarah; McCaskill, Mary; Cheek, John A; Gilhotra, Yuri; Furyk, Jeremy; Neutze, Jocelyn; Lyttle, Mark D; Bressan, Silvia; Donath, Susan; Molesworth, Charlotte; Jachno, Kim; Ward, Brenton; Williams, Amanda; Baylis, Amy; Crowe, Louise; Oakley, Ed; Dalziel, Stuart R

2017-06-17

Clinical decision rules can help to determine the need for CT imaging in children with head injuries. We aimed to validate three clinical decision rules (PECARN, CATCH, and CHALICE) in a large sample of children. In this prospective observational study, we included children and adolescents (aged <18 years) with head injuries of any severity who presented to the emergency departments of ten Australian and New Zealand hospitals. We assessed the diagnostic accuracy of PECARN (stratified into children aged <2 years and ≥2 years), CATCH, and CHALICE in predicting each rule-specific outcome measure (clinically important traumatic brain injury [TBI], need for neurological intervention, and clinically significant intracranial injury, respectively). For each calculation we used rule-specific predictor variables in populations that satisfied inclusion and exclusion criteria for each rule (validation cohort). In a secondary analysis, we compiled a comparison cohort of patients with mild head injuries (Glasgow Coma Scale score 13-15) and calculated accuracy using rule-specific predictor variables for the standardised outcome of clinically important TBI. This study is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12614000463673. Between April 11, 2011, and Nov 30, 2014, we analysed 20 137 children and adolescents attending with head injuries. CTs were obtained for 2106 (10%) patients, 4544 (23%) were admitted, 83 (<1%) underwent neurosurgery, and 15 (<1%) died. PECARN was applicable for 4011 (75%) of 5374 patients younger than 2 years and 11 152 (76%) of 14 763 patients aged 2 years and older. CATCH was applicable for 4957 (25%) patients and CHALICE for 20 029 (99%). The highest point validation sensitivities were shown for PECARN in children younger than 2 years (100·0%, 95% CI 90·7-100·0; 38 patients identified of 38 with outcome [38/38]) and PECARN in children 2 years and older (99·0%, 94·4-100·0; 97/98), followed by CATCH (high-risk predictors only; 95·2%; 76·2-99·9; 20/21; medium-risk and high-risk predictors 88·7%; 82·2-93·4; 125/141) and CHALICE (92·3%, 89·2-94·7; 370/401). In the comparison cohort of 18 913 patients with mild injuries, sensitivities for clinically important TBI were similar. Negative predictive values in both analyses were higher than 99% for all rules. The sensitivities of three clinical decision rules for head injuries in children were high when used as designed. The findings are an important starting point for clinicians considering the introduction of one of the rules. National Health and Medical Research Council, Emergency Medicine Foundation, Perpetual Philanthropic Services, WA Health Targeted Research Funds, Townsville Hospital Private Practice Fund, Auckland Medical Research Foundation, A + Trust. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prospective validation of a clinical decision rule to identify patients presenting to the emergency department with chest pain who can safely be removed from cardiac monitoring

PubMed Central

Syed, Shahbaz; Gatien, Mathieu; Perry, Jeffrey J.; Chaudry, Hina; Kim, Soo-Min; Kwong, Kenneth; Mukarram, Muhammad; Thiruganasambandamoorthy, Venkatesh

2017-01-01

BACKGROUND: Most patients with chest pain in the emergency department are assigned to cardiac monitoring for several hours, blocking access for patients in greater need. We sought to validate a previously derived decision rule for safe removal of patients from cardiac monitoring after initial evaluation in the emergency department. METHODS: We prospectively enrolled adults (age ≥ 18 yr) who presented with chest pain and were assigned to cardiac monitoring at 2 academic emergency departments over 18 months. We collected standardized baseline characteristics, findings from clinical evaluations and predictors for the Ottawa Chest Pain Cardiac Monitoring Rule: whether the patient is currently free of chest pain, and whether the electrocardiogram is normal or shows only nonspecific changes. The outcome was an arrhythmia requiring intervention in the emergency department or within 8 hours of presentation to the emergency department. We calculated diagnostic characteristics for the clinical prediction rule. RESULTS: We included 796 patients (mean age 63.8 yr, 55.8% male, 8.9% admitted to hospital). Fifteen patients (1.9%) had an arrhythmia, and the rule performed with the following characteristics: sensitivity 100% (95% confidence interval [CI] 78.2%–100%) and specificity 36.4% (95% CI 33.0%–39.6%). Application of the Ottawa Chest Pain Cardiac Monitoring Rule would have allowed 284 out of 796 patients (35.7%) to be safely removed from cardiac monitoring. INTERPRETATION: We successfully validated the decision rule for safe removal of a large subset of patients with chest pain from cardiac monitoring after initial evaluation in the emergency department. Implementation of this simple yet highly sensitive rule will allow for improved use of health care resources. PMID:28246315

The effectiveness of the McIsaac clinical decision rule in the management of sore throat: an evaluation from a pediatrics ward.

PubMed

Thillaivanam, Saravanapriya; Amin, Arwa M; Gopalakrishnan, Sheila; Ibrahim, Baharudin

2016-10-01

Sore throats may be due to either viral or group A beta hemolytic streptococcus (GABHS) infections; but diagnosis of the etiology of a sore throat is difficult, often leading to unnecessary antibiotic prescriptions and consequent increases in bacterial resistance. Scoring symptoms using the McIsaac clinical decision rule can help physicians to diagnose and manage streptococcal infections leading to sore throat and have been recommended by the Ministry of Health, Malaysia. In this paper, we offer the first assessment of the effectiveness of the McIsaac rule in a clinical setting in Malaysia. This study is a retrospective review of 116 pediatric patients presenting with sore throat. Group A comprised patients before the implementation of the McIsaac rule and Group B comprised patients after the implementation. Unnecessary throat swab cultures were reduced by 40% (P = 0.003). Redundant antibiotic prescriptions were reduced by 26.5% (P = 0.003) and the overall use of antibiotics was reduced by 22.1% (P = 0.003). The pediatricians' compliance rate to McIsaac rule criteria was 45% before implementation of the McIsaac rule, but improved to 67.9% (P = 0.0005) after implementation. The McIsaac rule is an effective tool for the management of sore throat in children in Malaysia.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Characteristics of knowledge content in a curated online evidence library.

PubMed

Varada, Sowmya; Lacson, Ronilda; Raja, Ali S; Ip, Ivan K; Schneider, Louise; Osterbur, David; Bain, Paul; Vetrano, Nicole; Cellini, Jacqueline; Mita, Carol; Coletti, Margaret; Whelan, Julia; Khorasani, Ramin

2018-05-01

To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.

GLASS Clinical Decision Rule Applied to Thoracolumbar Spinal Fractures in Patients Involved in Motor Vehicle Crashes.

PubMed

Althoff, Seth; Overberger, Ryan; Sochor, Mark; Bose, Dipan; Werner, Joshua

2017-10-01

There are established and validated clinical decision tools for cervical spine clearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Our goal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, to thoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method to evaluate those patients involved in motor vehicle collisions and determine which are at low risk for thoracolumbar injuries. We performed a retrospective cohort study using the National Accident Sampling System-Crashworthiness Data System (NASS-CDS) over an 11-year period (1998-2008). Sampled occupant cases selected in this study included patients age 16-60 who were belt-restrained, front- seat occupants involved in a crash with no airbag deployment, and no glass damage prior to the crash. We evaluated 14,191 occupants involved in motor vehicle collisions in this analysis. GLASS had a sensitivity of 94.4% (95% CI [86.3-98.4%]), specificity of 54.1% (95% CI [53.2-54.9%]), and negative predictive value of 99.9% (95% CI [99.8-99.9%]) for thoracic injuries, and a sensitivity of 90.3% (95% CI [82.8-95.2%]), specificity of 54.2% (95% CI [53.3-54.9%]), and negative predictive value of 99.9% (95% CI [99.7-99.9%]) for lumbar injuries. The GLASS rule represents the possibility of a novel, more-objective thoracolumbar spine clearance tool. Prospective evaluation would be required to further evaluate the validity of this clinical decision rule.

Acceptability of a Mobile Clinical Decision Tool Among Emergency Department Clinicians: Development and Evaluation of The Ottawa Rules App.

PubMed

Paradis, Michelle; Stiell, Ian; Atkinson, Katherine M; Guerinet, Julien; Sequeira, Yulric; Salter, Laura; Forster, Alan J; Murphy, Malia Sq; Wilson, Kumanan

2018-06-11

The Ottawa Ankle Rules, Ottawa Knee Rule, and Canadian C-Spine Rule-together known as The Ottawa Rules-are a set of internationally validated clinical decision rules developed to decrease unnecessary diagnostic imaging in the emergency department. In this study, we sought to develop and evaluate the use of a mobile app version of The Ottawa Rules. The primary objective of this study was to determine acceptability of The Ottawa Rules app among emergency department clinicians. The secondary objective was to evaluate the effect of publicity efforts on uptake of The Ottawa Rules app. The Ottawa Rules app was developed and publicly released for free on iOS and Android operating systems in April 2016. Local and national news and academic media coverage coincided with app release. This study was conducted at a large tertiary trauma care center in Ottawa, Canada. The study was advertised through posters and electronically by email. Emergency department clinicians were approached in person to enroll via in-app consent for a 1-month study during which time they were encouraged to use the app when evaluating patients with suspected knee, foot, or neck injuries. A 23-question survey was administered at the end of the study period via email to determine self-reported frequency, perceived ease of use of the app, and participant Technology Readiness Index scores. A total of 108 emergency department clinicians completed the study including 42 nurses, 33 residents, 20 attending physicians, and 13 medical students completing emergency department rotations. The median Technology Readiness Index for this group was 3.56, indicating a moderate degree of openness for technological adoption. The majority of survey respondents indicated favorable receptivity to the app including finding it helpful to applying the rules (73/108, 67.6%), that they would recommend the app to colleagues (81/108, 75.0%), and that they would continue using the app (73/108, 67.6%). Feedback from study participants highlighted a desire for access to more clinical decision rules and a higher degree of interactivity of the app. Between April 21, 2016, and June 1, 2017, The Ottawa Rules app was downloaded approximately 4000 times across 89 countries. We have found The Ottawa Rules app to be an effective means to disseminate the Ottawa Ankle Rules, Ottawa Knee Rule, and Canadian C-Spine Rule among all levels of emergency department clinicians. We have been successful in monitoring uptake and access of the rules in the app as a result of our publicity efforts. Mobile technology can be leveraged to improve the accessibility of clinical decision tools to health professionals. ©Michelle Paradis, Ian Stiell, Katherine M Atkinson, Julien Guerinet, Yulric Sequeira, Laura Salter, Alan J Forster, Malia SQ Murphy, Kumanan Wilson. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 11.06.2018.

Multicenter comparison of two clinical decision rules for the use of radiography in acute, high-risk knee injuries.

PubMed

Seaberg, D C; Yealy, D M; Lukens, T; Auble, T; Mathias, S

1998-07-01

Two separate clinical decision rules, one developed in Ottawa and the other in Pittsburgh, for the use of radiography in acute knee injuries have been previously validated and published. In this study, the rules were prospectively validated and compared in a new set of patients. A prospective, blinded, multicenter trial was conducted in the emergency departments of three urban teaching hospitals. A convenience sample of 934 patients with knee pain requiring radiographs was enrolled. A standardized data form was completed for each patient, comprising the 10 clinical variables included in the two rules. Standard knee radiographs were then taken in each patient. The rules were interpreted by the primary investigator on the basis of the data sheet and the final radiologist radiograph reading. In the 745 patients in whom the Pittsburgh rules could be applied there were 91 fractures (12.2%). The use of the Pittsburgh rule missed one fracture, yielding a sensitivity of 99% (95% confidence interval [CI], 94% to 100%); the specificity was 60% (95% CI, 56% to 64%). The Ottawa inclusion criteria were met by 750 patients, with 87 fractures (11.6%). The Ottawa rule missed three fractures, for a sensitivity of 97% (95% CI, 90% to 99%); specificity was 27% (95% CI, 23% to 30%). Prospective validation and comparison found the Pittsburgh rule for knee radiographs to be more specific without loss of sensitivity compared with the Ottawa rule.

The Amsterdam wrist rules: the multicenter prospective derivation and external validation of a clinical decision rule for the use of radiography in acute wrist trauma.

PubMed

Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M Suzan H; Maas, Mario; Jager, L Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J Carel; Schep, Niels W L

2015-12-18

Although only 39 % of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95 % CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98 % (95 % CI: 95-99 %) and 21 % (95 % CI: 15 %-28). The negative predictive value was 90 % (95 % CI: 81-99 %). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs. This study was registered in the Dutch Trial Registry, reference number NTR2544 on October 1(st), 2010.

Scalable software architectures for decision support.

PubMed

Musen, M A

1999-12-01

Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

Implementing a Commercial Rule Base as a Medication Order Safety Net

PubMed Central

Reichley, Richard M.; Seaton, Terry L.; Resetar, Ervina; Micek, Scott T.; Scott, Karen L.; Fraser, Victoria J.; Dunagan, W. Claiborne; Bailey, Thomas C.

2005-01-01

A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support. PMID:15802481

Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

PubMed

Parodi, Stefano; Manneschi, Chiara; Verda, Damiano; Ferrari, Enrico; Muselli, Marco

2018-03-01

This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.

Utility of Decision Rules for Transcutaneous Bilirubin Measurements

PubMed Central

Burgos, Anthony E.; Flaherman, Valerie; Chung, Esther K.; Simpson, Elizabeth A.; Goyal, Neera K.; Von Kohorn, Isabelle; Dhepyasuwan, Niramol

2016-01-01

BACKGROUND: Transcutaneous bilirubin (TcB) meters are widely used for screening newborns for jaundice, with a total serum bilirubin (TSB) measurement indicated when the TcB value is classified as “positive” by using a decision rule. The goal of our study was to assess the clinical utility of 3 recommended TcB screening decision rules. METHODS: Paired TcB/TSB measurements were collected at 34 newborn nursery sites. At 27 sites (sample 1), newborns were routinely screened with a TcB measurement. For sample 2, sites that typically screen with TSB levels also obtained a TcB measurement for the study. Three decision rules to define a positive TcB measurement were evaluated: ≥75th percentile on the Bhutani nomogram, 70% of the phototherapy level, and within 3 mg/dL of the phototherapy threshold. The primary outcome was a TSB level at/above the phototherapy threshold. The rate of false-negative TcB screens and percentage of blood draws avoided were calculated for each decision rule. RESULTS: For sample 1, data were analyzed on 911 paired TcB-TSB measurements from a total of 8316 TcB measurements. False-negative rates were <10% with all decision rules; none identified all 31 newborns with a TSB level at/above the phototherapy threshold. The percentage of blood draws avoided ranged from 79.4% to 90.7%. In sample 2, each rule correctly identified all 8 newborns with TSB levels at/above the phototherapy threshold. CONCLUSIONS: Although all of the decision rules can be used effectively to screen newborns for jaundice, each will “miss” some infants with a TSB level at/above the phototherapy threshold. PMID:27244792

Developing an International Register of Clinical Prediction Rules for Use in Primary Care: A Descriptive Analysis

PubMed Central

Keogh, Claire; Wallace, Emma; O’Brien, Kirsty K.; Galvin, Rose; Smith, Susan M.; Lewis, Cliona; Cummins, Anthony; Cousins, Grainne; Dimitrov, Borislav D.; Fahey, Tom

2014-01-01

PURPOSE We describe the methodology used to create a register of clinical prediction rules relevant to primary care. We also summarize the rules included in the register according to various characteristics. METHODS To identify relevant articles, we searched the MEDLINE database (PubMed) for the years 1980 to 2009 and supplemented the results with searches of secondary sources (books on clinical prediction rules) and personal resources (eg, experts in the field). The rules described in relevant articles were classified according to their clinical domain, the stage of development, and the clinical setting in which they were studied. RESULTS Our search identified clinical prediction rules reported between 1965 and 2009. The largest share of rules (37.2%) were retrieved from PubMed. The number of published rules increased substantially over the study decades. We included 745 articles in the register; many contained more than 1 clinical prediction rule study (eg, both a derivation study and a validation study), resulting in 989 individual studies. In all, 434 unique rules had gone through derivation; however, only 54.8% had been validated and merely 2.8% had undergone analysis of their impact on either the process or outcome of clinical care. The rules most commonly pertained to cardiovascular disease, respiratory, and musculoskeletal conditions. They had most often been studied in the primary care or emergency department settings. CONCLUSIONS Many clinical prediction rules have been derived, but only about half have been validated and few have been assessed for clinical impact. This lack of thorough evaluation for many rules makes it difficult to retrieve and identify those that are ready for use at the point of patient care. We plan to develop an international web-based register of clinical prediction rules and computer-based clinical decision support systems. PMID:25024245

Clinical decision rules for termination of resuscitation in out-of-hospital cardiac arrest.

PubMed

Sherbino, Jonathan; Keim, Samuel M; Davis, Daniel P

2010-01-01

Out-of-hospital cardiac arrest (OHCA) has a low probability of survival to hospital discharge. Four clinical decision rules (CDRs) have been validated to identify patients with no probability of survival. Three of these rules focus on exclusive prehospital basic life support care for OHCA, and two of these rules focus on prehospital advanced life support care for OHCA. Can a CDR for the termination of resuscitation identify a patient with no probability of survival in the setting of OHCA? Six validation studies were selected from a PubMed search. A structured review of each of the studies is presented. In OHCA receiving basic life support care, the BLS-TOR (basic life support termination of resuscitation) rule has a positive predictive value for death of 99.5% (95% confidence interval 98.9-99.8%), and decreases the transportation of all patients by 62.6%. This rule has been appropriately validated for widespread use. In OHCA receiving advanced life support care, no current rule has been appropriately validated for widespread use. The BLS-TOR rule is a simple rule that identifies patients who will not survive OHCA. Further research is required to identify similarly robust CDRs for patients receiving advanced life support care in the setting of OHCA. Copyright 2010 Elsevier Inc. All rights reserved.

[Decisions in case of "problematic" cost-effectiveness ratios based on the example of a clinical trial in rehabilitation care].

PubMed

Leidl, R; Jacobi, E; Knab, J; Schweikert, B

2006-04-01

Economic assessment of an additional psychological intervention in the rehabilitation of patients with chronic low-back pain and evaluation of results by decision makers. Piggy-back cost-utility analysis of a randomised clinical trial, including a bootstrap analysis. Costs were measured by using the cost accounting systems of the rehabilitation clinics and by surveying patients. Health-related quality of life was measured using the EQ-5D. Implications of different representations of the decision problem and corresponding decision rules concerning the cost-effectiveness plane are discussed. As compared with the 126 patients of the control arm, the 98 patients in the intervention arm gained 3.5 days in perfect health on average as well as 1219 euro cost saving. However, because of the uncertainty involved, the results of a bootstrap analysis cover all quadrants of the cost-effectiveness plane. Using maximum willingness-to-pay per effect unit gained, decision rules can be defined for parts of the cost-effectiveness plane. These have to be aggregated in a further valuation step. Study results show that decisions on stochastic economic evaluation results may require an additional valuation step aggregating the various parts of the cost-effectiveness plane.

GLASS Clinical Decision Rule Applied to Thoracolumbar Spinal Fractures in Patients Involved in Motor Vehicle Crashes

PubMed Central

Althoff, Seth; Overberger, Ryan; Sochor, Mark; Bose, Dipan; Werner, Joshua

2017-01-01

Introduction There are established and validated clinical decision tools for cervical spine clearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Our goal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, to thoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method to evaluate those patients involved in motor vehicle collisions and determine which are at low risk for thoracolumbar injuries. Methods We performed a retrospective cohort study using the National Accident Sampling System-Crashworthiness Data System (NASS-CDS) over an 11-year period (1998–2008). Sampled occupant cases selected in this study included patients age 16–60 who were belt-restrained, front- seat occupants involved in a crash with no airbag deployment, and no glass damage prior to the crash. Results We evaluated 14,191 occupants involved in motor vehicle collisions in this analysis. GLASS had a sensitivity of 94.4% (95% CI [86.3–98.4%]), specificity of 54.1% (95% CI [53.2–54.9%]), and negative predictive value of 99.9% (95% CI [99.8–99.9%]) for thoracic injuries, and a sensitivity of 90.3% (95% CI [82.8–95.2%]), specificity of 54.2% (95% CI [53.3–54.9%]), and negative predictive value of 99.9% (95% CI [99.7–99.9%]) for lumbar injuries. Conclusion The GLASS rule represents the possibility of a novel, more-objective thoracolumbar spine clearance tool. Prospective evaluation would be required to further evaluate the validity of this clinical decision rule. PMID:29085544

An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems.

PubMed

Sáez, Carlos; Bresó, Adrián; Vicente, Javier; Robles, Montserrat; García-Gómez, Juan Miguel

2013-03-01

The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Derivation of a clinical decision rule to guide the interhospital transfer of patients with blunt traumatic brain injury.

PubMed

Newgard, C D; Hedges, J R; Stone, J V; Lenfesty, B; Diggs, B; Arthur, M; Mullins, R J

2005-12-01

To derive a clinical decision rule for people with traumatic brain injury (TBI) that enables early identification of patients requiring specialised trauma care. We collected data from 1999 through 2003 on a retrospective cohort of consecutive people aged 18-65 years with a serious head injury (AIS > or =3), transported directly from the scene of injury, and evaluated in the ED. Information on 22 demographical, physiological, radiographic, and lab variables was collected. Resource based "high therapeutic intensity" measures occurring within 72 hours of ED arrival (the outcome measure) were identified a priori and included: neurosurgical intervention, exploratory laparotomy, intensive care interventions, or death. We used classification and regression tree analysis to derive and cross validate the decision rule. 504 consecutive trauma patients were identified as having a serious head injury: 246 (49%) required at least one of the HTI measures. Five ED variables (GCS, respiratory rate, age, temperature, and pulse rate) identified subjects requiring at least one of the HTI measures with 94% sensitivity (95% CI 91 to 97%) and 63% specificity (95% CI 57 to 69%) in the derivation sample, and 90% sensitivity and 55% specificity using cross validation. This decision rule identified among a cohort of head injured patients evaluated in the ED the majority of those who urgently required specialised trauma care. The rule will require prospective validation in injured people presenting to non-tertiary care hospitals before implementation can be recommended.

Knowledge Translation of the PERC Rule for Suspected Pulmonary Embolism: A Blueprint for Reducing the Number of CT Pulmonary Angiograms.

PubMed

Drescher, Michael J; Fried, Jeremy; Brass, Ryan; Medoro, Amanda; Murphy, Timothy; Delgado, João

2017-10-01

Computerized decision support decreases the number of computed tomography pulmonary angiograms (CTPA) for pulmonary embolism (PE) ordered in emergency departments, but it is not always well accepted by emergency physicians. We studied a department-endorsed, evidence-based clinical protocol that included the PE rule-out criteria (PERC) rule, multi-modal education using principles of knowledge translation (KT), and clinical decision support embedded in our order entry system, to decrease the number of unnecessary CTPA ordered. We performed a historically controlled observational before-after study for one year pre- and post-implementation of a departmentally-endorsed protocol. We included patients > 18 in whom providers suspected PE and who did not have a contraindication to CTPA. Providers entered clinical information into a diagnostic pathway via computerized order entry. Prior to protocol implementation, we provided education to ordering providers. The primary outcome measure was the number of CTPA ordered per 1,000 visits one year before vs. after implementation. CTPA declined from 1,033 scans for 98,028 annual visits (10.53 per 1,000 patient visits (95% CI [9.9-11.2]) to 892 scans for 101,172 annual visits (8.81 per 1,000 patient visits (95% CI [8.3-9.4]) p<0.001. The absolute reduction in PACT ordered was 1.72 per 1,000 visits (a 16% reduction). Patient characteristics were similar for both periods. Knowledge translation clinical decision support using the PERC rule significantly reduced the number of CTPA ordered.

The Ottawa knee rules - a useful clinical decision tool.

PubMed

Yao, Kaihan; Haque, Tasneem

2012-04-01

Acute knee injuries are a common presentation in the primary care setting. The Ottawa knee rules provide guidance on how to identify which cases of knee injury require radiographic investigation. This article describes the Ottawa knee rules and outlines their sensitivity, reproducibility and application in the clinical setting. The Ottawa knee rules are a valuable tool for clinicians in the routine management of acute knee injuries. Studies show that they are highly sensitive at identifying patients with fractures of the knee and have a high degree of interobserver agreement and reproducible results. Application of the Ottawa knee rules in appropriate clinical scenarios may reduce the number of unnecessary radiographs ordered, streamlining patient throughput and allowing for significant cost savings. Although designed for use in adults, some studies have suggested that the Ottawa knee rules may also be applicable to the paediatric population.

The normalization heuristic: an untested hypothesis that may misguide medical decisions.

PubMed

Aberegg, Scott K; O'Brien, James M

2009-06-01

Medical practice is increasingly informed by the evidence from randomized controlled trials. When such evidence is not available, clinical hypotheses based on pathophysiological reasoning and common sense guide clinical decision making. One commonly utilized general clinical hypothesis is the assumption that normalizing abnormal laboratory values and physiological parameters will lead to improved patient outcomes. We refer to the general use of this clinical hypothesis to guide medical therapeutics as the "normalization heuristic". In this paper, we operationally define this heuristic and discuss its limitations as a rule of thumb for clinical decision making. We review historical and contemporaneous examples of normalization practices as empirical evidence for the normalization heuristic and to highlight its frailty as a guide for clinical decision making.

Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

ERIC Educational Resources Information Center

Kunisch, Joseph Martin

2012-01-01

Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: a sociotechnical analysis.

PubMed

Sheehan, Barbara; Nigrovic, Lise E; Dayan, Peter S; Kuppermann, Nathan; Ballard, Dustin W; Alessandrini, Evaline; Bajaj, Lalit; Goldberg, Howard; Hoffman, Jeffrey; Offerman, Steven R; Mark, Dustin G; Swietlik, Marguerite; Tham, Eric; Tzimenatos, Leah; Vinson, David R; Jones, Grant S; Bakken, Suzanne

2013-10-01

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making. Copyright © 2013 Elsevier Inc. All rights reserved.

Anxiety Evokes Hypofrontality and Disrupts Rule-Relevant Encoding by Dorsomedial Prefrontal Cortex Neurons.

PubMed

Park, Junchol; Wood, Jesse; Bondi, Corina; Del Arco, Alberto; Moghaddam, Bita

2016-03-16

Anxiety is a debilitating symptom of most psychiatric disorders, including major depression, post-traumatic stress disorder, schizophrenia, and addiction. A detrimental aspect of anxiety is disruption of prefrontal cortex (PFC)-mediated executive functions, such as flexible decision making. Here we sought to understand how anxiety modulates PFC neuronal encoding of flexible shifting between behavioral strategies. We used a clinically substantiated anxiogenic treatment to induce sustained anxiety in rats and recorded from dorsomedial PFC (dmPFC) and orbitofrontal cortex (OFC) neurons while they were freely moving in a home cage and while they performed a PFC-dependent task that required flexible switches between rules in two distinct perceptual dimensions. Anxiety elicited a sustained background "hypofrontality" in dmPFC and OFC by reducing the firing rate of spontaneously active neuronal subpopulations. During task performance, the impact of anxiety was subtle, but, consistent with human data, behavior was selectively impaired when previously correct conditions were presented as conflicting choices. This impairment was associated with reduced recruitment of dmPFC neurons that selectively represented task rules at the time of action. OFC rule representation was not affected by anxiety. These data indicate that a neural substrate of the decision-making deficits in anxiety is diminished dmPFC neuronal encoding of task rules during conflict-related actions. Given the translational relevance of the model used here, the data provide a neuronal encoding mechanism for how anxiety biases decision making when the choice involves overcoming a conflict. They also demonstrate that PFC encoding of actions, as opposed to cues or outcome, is especially vulnerable to anxiety. A debilitating aspect of anxiety is its impact on decision making and flexible control of behavior. These cognitive constructs depend on proper functioning of the prefrontal cortex (PFC). Understanding how anxiety affects PFC encoding of cognitive events is of great clinical and evolutionary significance. Using a clinically valid experimental model, we find that, under anxiety, decision making may be skewed by salient and conflicting environmental stimuli at the expense of flexible top-down guided choices. We also find that anxiety suppresses spontaneous activity of PFC neurons, and weakens encoding of task rules by dorsomedial PFC neurons. These data provide a neuronal encoding scheme for how anxiety disengages PFC during decision making. Copyright © 2016 the authors 0270-6474/16/363322-14$15.00/0.

Feasibility of automatic evaluation of clinical rules in general practice.

PubMed

Opondo, Dedan; Visscher, Stefan; Eslami, Saied; Medlock, Stephanie; Verheij, Robert; Korevaar, Joke C; Abu-Hanna, Ameen

2017-04-01

To assess the extent to which clinical rules (CRs) can be implemented for automatic evaluation of quality of care in general practice. We assessed 81 clinical rules (CRs) adapted from a subset of Assessing Care of Vulnerable Elders (ACOVE) clinical rules, against Dutch College of General Practitioners (NHG) data model. Each CR was analyzed using the Logical Elements Rule METHOD: (LERM). LERM is a stepwise method of assessing and formalizing clinical rules for decision support. Clinical rules that satisfied the criteria outlined in the LERM method were judged to be implementable in automatic evaluation in general practice. Thirty-three out of 81 (40.7%) Dutch-translated ACOVE clinical rules can be automatically evaluated in electronic medical record systems. Seven out of 7 CRs (100%) in the domain of diabetes can be automatically evaluated, 9/17 (52.9%) in medication use, 5/10 (50%) in depression care, 3/6 (50%) in nutrition care, 6/13 (46.1%) in dementia care, 1/6 (16.6%) in end of life care, 2/13 (15.3%) in continuity of care, and 0/9 (0%) in the fall-related care. Lack of documentation of care activities between primary and secondary health facilities and ambiguous formulation of clinical rules were the main reasons for the inability to automate the clinical rules. Approximately two-fifths of the primary care Dutch ACOVE-based clinical rules can be automatically evaluated. Clear definition of clinical rules, improved GP database design and electronic linkage of primary and secondary healthcare facilities can improve prospects of automatic assessment of quality of care. These findings are relevant especially because the Netherlands has very high automation of primary care. Copyright © 2017 Elsevier B.V. All rights reserved.

Pathologic C-spine fracture with low risk mechanism and normal physical exam.

PubMed

Hunter, Andrew; McGreevy, Jolion; Linden, Judith

2017-09-01

Cervical spinal fracture is a rare, but potentially disabling complication of trauma to the neck. Clinicians often rely on clinical decision rules and guidelines to decide whether or not imaging is necessary when a patient presents with neck pain. Validated clinical guidelines include the Canadian C-Spine Rule and the Nexus criteria. Studies suggest that the risks of a pathologic fracture from a simple rear end collision are negligible. We present a case of an individual who presented to an emergency department (ED) after a low speed motor vehicle collision complaining of lateral neck pain and had multiple subsequent visits for the same complaint with negative exam findings. Ultimately, he was found to have a severely pathologic cervical spine fracture with notable cord compression. Our objective is to discuss the necessity to incorporate clinical decision rules with physician gestalt and the need to take into account co-morbidities of a patient presenting after a minor MVC. Copyright © 2017 Elsevier Inc. All rights reserved.

The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.

PubMed

Băceanu, Adrian; Atasiei, Ionuţ; Chazard, Emmanuel; Leroy, Nicolas

2009-01-01

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

A clinical decision rule and D-dimer testing to rule out upper extremity deep vein thrombosis in high-risk patients.

PubMed

van Es, Nick; Bleker, Suzanne M; Di Nisio, Marcello; Kleinjan, Ankie; Beyer-Westendorf, Jan; Camporese, Giuseppe; Kamphuisen, Pieter W; Büller, Harry R; Bossuyt, Patrick M

2016-12-01

In a management study, a diagnostic algorithm consisting of a clinical decision rule, D-dimer, and ultrasonography was shown to safely exclude upper extremity deep vein thrombosis (UEDVT). Efficiency may be lower in high-risk subgroups: those with a central venous catheter or pacemaker, inpatients, cancer, and elderly patients. Data of 406 patients with suspected UEDVT enrolled in a prospective management study were used for the present analysis. The aim was to evaluate the efficiency of the algorithm in subgroups, defined as the proportion of patients in whom imaging could be safely withheld based on the combination of a decision rule result indicating "UEDVT unlikely" and a normal D-dimer result. The strategy excluded UEDVT in 87 of 406 patients (21%); ultrasonography was withheld in these patients and none developed UEDVT during 3months of follow-up. In contrast, ultrasonography could be withheld in only 4 of 92 patients with a catheter or pacemaker (4.3%; 95% CI: 1.7% to 11%) and in 4 of 83 inpatients (4.8%; 95% CI: 1.9% to 12%). The efficiency was 11% in patients with cancer and 13% in those older than 75years. Although the combination of a decision rule and D-dimer testing is safe in excluding UEDVT in the overall population of patients with suspected UEDVT, its efficiency appears limited in some subgroups, in particular those with a central venous catheter or pacemaker, and inpatients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Separating Business Logic from Medical Knowledge in Digital Clinical Workflows Using Business Process Model and Notation and Arden Syntax.

PubMed

de Bruin, Jeroen S; Adlassnig, Klaus-Peter; Leitich, Harald; Rappelsberger, Andrea

2018-01-01

Evidence-based clinical guidelines have a major positive effect on the physician's decision-making process. Computer-executable clinical guidelines allow for automated guideline marshalling during a clinical diagnostic process, thus improving the decision-making process. Implementation of a digital clinical guideline for the prevention of mother-to-child transmission of hepatitis B as a computerized workflow, thereby separating business logic from medical knowledge and decision-making. We used the Business Process Model and Notation language system Activiti for business logic and workflow modeling. Medical decision-making was performed by an Arden-Syntax-based medical rule engine, which is part of the ARDENSUITE software. We succeeded in creating an electronic clinical workflow for the prevention of mother-to-child transmission of hepatitis B, where institution-specific medical decision-making processes could be adapted without modifying the workflow business logic. Separation of business logic and medical decision-making results in more easily reusable electronic clinical workflows.

EDRN Breast and Ovary Cancer CVC, Study 4: Phase 3 Validation of Ovarian Cancer Serum Markers in Preclinical WHI Samples — EDRN Public Portal

Cancer.gov

The WHI offers an opportunity to evaluate ovarian cancer markers and screening decision rules developed and validated in EDRN CVC Studies 2 and 3 in women who were not being screened. It is particularly well suited to validation of risk markers, since many serum samples were drawn well before clinical diagnosis of cancer in the WHI cohorts. A strategy is needed to identify from among the general population of women over the age of 50 those at high-risk for a diagnosis of ovarian/fallopian tube cancer so that they can be referred for appropriate surveillance, imaging or surgical consult. Tools to identify high-risk women will be investigated including serum markers CA125, HE4, MSLN, and MMP7 and epidemiologic risk factors. We will optimize decision rules using stored serum samples from the WHI OS and conduct a simulated prospective validation using stored serum samples from the WHI CT. Decision rules to select women for ovarian cancer screening will be investigated as well as decision rules for use in ovarian cancer screening.

Prediction value of the Canadian CT head rule and the New Orleans criteria for positive head CT scan and acute neurosurgical procedures in minor head trauma: a multicenter external validation study.

PubMed

Bouida, Wahid; Marghli, Soudani; Souissi, Sami; Ksibi, Hichem; Methammem, Mehdi; Haguiga, Habib; Khedher, Sonia; Boubaker, Hamdi; Beltaief, Kaouthar; Grissa, Mohamed Habib; Trimech, Mohamed Naceur; Kerkeni, Wiem; Chebili, Nawfel; Halila, Imen; Rejeb, Imen; Boukef, Riadh; Rekik, Noureddine; Bouhaja, Bechir; Letaief, Mondher; Nouira, Semir

2013-05-01

The New Orleans Criteria and the Canadian CT Head Rule have been developed to decrease the number of normal computed tomography (CT) results in mild head injury. We compare the performance of both decision rules for identifying patients with intracranial traumatic lesions and those who require an urgent neurosurgical intervention after mild head injury. This was an observational cohort study performed between 2008 and 2011 on patients with mild head injury who were aged 10 years or older. We collected prospectively clinical head CT scan findings and outcome. Primary outcome was need for neurosurgical intervention, defined as either death or craniotomy, or the need of intubation within 15 days of the traumatic event. Secondary outcome was the presence of traumatic lesions on head CT scan. New Orleans Criteria and Canadian CT Head Rule decision rules were compared by using sensitivity specifications and positive and negative predictive value. We enrolled 1,582 patients. Neurosurgical intervention was performed in 34 patients (2.1%) and positive CT findings were demonstrated in 218 patients (13.8%). Sensitivity and specificity for need for neurosurgical intervention were 100% (95% confidence interval [CI] 90% to 100%) and 60% (95% CI 44% to 76%) for the Canadian CT Head Rule and 82% (95% CI 69% to 95%) and 26% (95% CI 24% to 28%) for the New Orleans Criteria. Negative predictive values for the above-mentioned clinical decision rules were 100% and 99% and positive values were 5% and 2%, respectively, for the Canadian CT Head Rule and New Orleans Criteria. Sensitivity and specificity for clinical significant head CT findings were 95% (95% CI 92% to 98%) and 65% (95% CI 62% to 68%) for the Canadian CT Head Rule and 86% (95% CI 81% to 91%) and 28% (95% CI 26% to 30%) for the New Orleans Criteria. A similar trend of results was found in the subgroup of patients with a Glasgow Coma Scale score of 15. For patients with mild head injury, the Canadian CT Head Rule had higher sensitivity than the New Orleans Criteria, with higher negative predictive value. The question of whether the use of the Canadian CT Head Rule would have a greater influence on head CT scan reduction requires confirmation in real clinical practice. Copyright © 2012 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.

PubMed

Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng

2018-04-20

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.

Using electronic data to predict the probability of true bacteremia from positive blood cultures.

PubMed

Wang, S J; Kuperman, G J; Ohno-Machado, L; Onderdonk, A; Sandige, H; Bates, D W

2000-01-01

As part of a project to help physicians make more appropriate treatment decisions, we implemented a clinical prediction rule that computes the probability of true bacteremia for positive blood cultures and displays this information when culture results are viewed online. Prior to implementing the rule, we performed a revalidation study to verify the accuracy of the previously published logistic regression model. We randomly selected 114 cases of positive blood cultures from a recent one-year period and performed a paper chart review with the help of infectious disease experts to determine whether the cultures were true positives or contaminants. Based on the results of this revalidation study, we updated the probabilities reported by the model and made additional enhancements to improve the accuracy of the rule. Next, we implemented the rule into our hospital's laboratory computer system so that the probability information was displayed with all positive blood culture results. We displayed the prediction rule information on approximately half of the 2184 positive blood cultures at our hospital that were randomly selected during a 6-month period. During the study, we surveyed 54 housestaff to obtain their opinions about the usefulness of this intervention. Fifty percent (27/54) indicated that the information had influenced their belief of the probability of bacteremia in their patients, and in 28% (15/54) of cases it changed their treatment decision. Almost all (98% (53/54)) indicated that they wanted to continue receiving this information. We conclude that the probability information provided by this clinical prediction rule is considered useful to physicians when making treatment decisions.

Updated systematic review and meta-analysis of the performance of risk prediction rules in children and young people with febrile neutropenia.

PubMed

Phillips, Robert S; Lehrnbecher, Thomas; Alexander, Sarah; Sung, Lillian

2012-01-01

Febrile neutropenia is a common and potentially life-threatening complication of treatment for childhood cancer, which has increasingly been subject to targeted treatment based on clinical risk stratification. Our previous meta-analysis demonstrated 16 rules had been described and 2 of them subject to validation in more than one study. We aimed to advance our knowledge of evidence on the discriminatory ability and predictive accuracy of such risk stratification clinical decision rules (CDR) for children and young people with cancer by updating our systematic review. The review was conducted in accordance with Centre for Reviews and Dissemination methods, searching multiple electronic databases, using two independent reviewers, formal critical appraisal with QUADAS and meta-analysis with random effects models where appropriate. It was registered with PROSPERO: CRD42011001685. We found 9 new publications describing a further 7 new CDR, and validations of 7 rules. Six CDR have now been subject to testing across more than two data sets. Most validations demonstrated the rule to be less efficient than when initially proposed; geographical differences appeared to be one explanation for this. The use of clinical decision rules will require local validation before widespread use. Considerable uncertainty remains over the most effective rule to use in each population, and an ongoing individual-patient-data meta-analysis should develop and test a more reliable CDR to improve stratification and optimise therapy. Despite current challenges, we believe it will be possible to define an internationally effective CDR to harmonise the treatment of children with febrile neutropenia.

Updated Systematic Review and Meta-Analysis of the Performance of Risk Prediction Rules in Children and Young People with Febrile Neutropenia

PubMed Central

Phillips, Robert S.; Lehrnbecher, Thomas; Alexander, Sarah; Sung, Lillian

2012-01-01

Introduction Febrile neutropenia is a common and potentially life-threatening complication of treatment for childhood cancer, which has increasingly been subject to targeted treatment based on clinical risk stratification. Our previous meta-analysis demonstrated 16 rules had been described and 2 of them subject to validation in more than one study. We aimed to advance our knowledge of evidence on the discriminatory ability and predictive accuracy of such risk stratification clinical decision rules (CDR) for children and young people with cancer by updating our systematic review. Methods The review was conducted in accordance with Centre for Reviews and Dissemination methods, searching multiple electronic databases, using two independent reviewers, formal critical appraisal with QUADAS and meta-analysis with random effects models where appropriate. It was registered with PROSPERO: CRD42011001685. Results We found 9 new publications describing a further 7 new CDR, and validations of 7 rules. Six CDR have now been subject to testing across more than two data sets. Most validations demonstrated the rule to be less efficient than when initially proposed; geographical differences appeared to be one explanation for this. Conclusion The use of clinical decision rules will require local validation before widespread use. Considerable uncertainty remains over the most effective rule to use in each population, and an ongoing individual-patient-data meta-analysis should develop and test a more reliable CDR to improve stratification and optimise therapy. Despite current challenges, we believe it will be possible to define an internationally effective CDR to harmonise the treatment of children with febrile neutropenia. PMID:22693615

Comparison of PECARN, CATCH, and CHALICE Rules for Children with Minor Head Injury: A prospective cohort study

PubMed Central

Easter, Joshua S.; Bakes, Katherine; Dhaliwal, Jasmeet; Miller, Michael; Caruso, Emily; Haukoos, Jason S.

2014-01-01

Objective To evaluate the diagnostic accuracy of clinical decision rules and physician judgment for identifying clinically important traumatic brain injuries (TBIs) in children with minor head injuries presenting to the emergency department (ED). Methods We prospectively enrolled children <18 years of age with minor head injury (Glasgow Coma Scale 13 – 15) presenting within 24 hours of their injuries. We assessed the ability of 3 clinical decision rules (CATCH, CHALICE, PECARN) and 2 measures of physician judgment (estimated of <1% risk of TBI, actual CT ordering practice) to predict clinically important TBI, as defined by death from TBI, need for neurosurgery, intubation >24 hours for TBI, or hospital admission >2 nights for TBI. Results Among the 1,009 children, 21 (2%; 95% CI: 1% to 3%) had clinically important TBIs. Only physician practice and PECARN identified all clinically important TBIs, with ranked sensitivities as follows (95% CI): Physician practice and PECARN each 100% (84% to 100%), physician estimates 95% (76% to 100%), CATCH 91% (70% to 99%), and CHALICE 84% (60% to 97%). Ranked specificities were as follows: CHALICE 85% (82% to 87%), physician estimates 68% (65% to 71%), PECARN 62% (59% to 66%), physician practice 50% (47% to 53%), and CATCH 44% (41% to 47%). Conclusions Of the 5 modalities studied, only physician practice and PECARN identified all clinically important TBIs, with PECARN being slightly more specific. CHALICE was incompletely sensitive but the most specific of all rules. CATCH was incompletely sensitive and had the poorest specificity of all modalities. PMID:24635987

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development

PubMed Central

Wright, Adam; Sittig, Dean F

2015-01-01

Objective Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. Methods We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. Results Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. Conclusion Significant improvements in the EHR certification and implementation procedures are necessary. PMID:26104739

The Manchester Acute Coronary Syndromes (MACS) decision rule: validation with a new automated assay for heart-type fatty acid binding protein.

PubMed

Body, Richard; Burrows, Gillian; Carley, Simon; Lewis, Philip S

2015-10-01

The Manchester Acute Coronary Syndromes (MACS) decision rule may enable acute coronary syndromes to be immediately 'ruled in' or 'ruled out' in the emergency department. The rule incorporates heart-type fatty acid binding protein (h-FABP) and high sensitivity troponin T levels. The rule was previously validated using a semiautomated h-FABP assay that was not practical for clinical implementation. We aimed to validate the rule with an automated h-FABP assay that could be used clinically. In this prospective diagnostic cohort study we included patients presenting to the emergency department with suspected cardiac chest pain. Serum drawn on arrival was tested for h-FABP using an automated immunoturbidimetric assay (Randox) and high sensitivity troponin T (Roche). The primary outcome, a diagnosis of acute myocardial infarction (AMI), was adjudicated based on 12 h troponin testing. A secondary outcome, major adverse cardiac events (MACE; death, AMI, revascularisation or new coronary stenosis), was determined at 30 days. Of the 456 patients included, 78 (17.1%) had AMI and 97 (21.3%) developed MACE. Using the automated h-FABP assay, the MACS rule had the same C-statistic for MACE as the original rule (0.91; 95% CI 0.88 to 0.92). 18.9% of patients were identified as 'very low risk' and thus eligible for immediate discharge with no missed AMIs and a 2.3% incidence of MACE (n=2, both coronary stenoses). 11.1% of patients were classed as 'high-risk' and had a 92.0% incidence of MACE. Our findings validate the performance of a refined MACS rule incorporating an automated h-FABP assay, facilitating use in clinical settings. The effectiveness of this refined rule should be verified in an interventional trial prior to implementation. UK CRN 8376. 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.

Clinical Decision Support for a Multicenter Trial of Pediatric Head Trauma

PubMed Central

Swietlik, Marguerite; Deakyne, Sara; Hoffman, Jeffrey M.; Grundmeier, Robert W.; Paterno, Marilyn D.; Rocha, Beatriz H.; Schaeffer, Molly H; Pabbathi, Deepika; Alessandrini, Evaline; Ballard, Dustin; Goldberg, Howard S.; Kuppermann, Nathan; Dayan, Peter S.

2016-01-01

Summary Introduction For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial. Methods Thirteen EDs participated in this trial. The 10 sites receiving the CDS intervention used the Epic® EHR. All sites implementing EHR-based CDS built the rules by using the vendor’s CDS engine. Based on a sociotechnical analysis, we designed the CDS so that recommendations could be displayed immediately after any provider entered prediction rule data. One central site developed and tested the intervention package to be exported to other sites. The intervention package included a clinical trial alert, an electronic data collection form, the CDS rules and the format for recommendations. Results The original PECARN head trauma prediction rules were derived from physician documentation while this pragmatic trial led each site to customize their workflows and allow multiple different providers to complete the head trauma assessments. These differences in workflows led to varying completion rates across sites as well as differences in the types of providers completing the electronic data form. Site variation in internal change management processes made it challenging to maintain the same rigor across all sites. This led to downstream effects when data reports were developed. Conclusions The process of a centralized build and export of a CDS system in one commercial EHR system successfully supported a multicenter clinical trial. PMID:27437059

Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

PubMed

Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

2018-06-01

Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

The impact of the introduction of PECARN head CT rules on the utilisation of head CT scans in a private tertiary hospital in Sub-Saharan Africa.

PubMed

Kobe, Isaac O; Qureshi, Mahmoud M; Hassan, Saidi; Oluoch-Olunya, David L

2017-12-01

The decision to order head CT scans to rule out clinically significant traumatic brain injury in mild head injury in children is made on the basis of clinical decision rules of which the Paediatric Emergency Care Applied Research Network (PECARN) CT head rules have been found to be most sensitive. The purpose of this study is to determine the proportion of head CT scans done for children with mild head injury and to determine disposition of patients from casualty after the introduction of PECARN head CT rules compared to the period before. The research question is "will introduction of the PECARN CT head rules reduce the proportion of head CT scans requested for children under 18 years with mild head injury at the AKUHN?" A before and after quasi experimental study with a study population including all children under 18 years presenting to the AKUHN with mild head injury and a Glasgow coma scale of 14 and above on presentation. Sample size was 85. A total of 42 patients files were analysed in the before study while 43 patients were selected for the after study. The median age was 5 years. The proportion of head CT scans reduced from 56% in the before group to 33% in the after group with no missed clinically significant traumatic brain injury. More patients were discharged home after evaluation in the after group (81%) than in the before group (58%). The number of head CT scans ordered reduced without missing any clinically significant traumatic brain injury.

A clinical decision rule for triage of children under 5 years of age with hydrocarbon (kerosene) aspiration in developing countries.

PubMed

Bond, G R; Pièche, S; Sonicki, Z; Gamaluddin, H; El Guindi, M; Sakr, M; El Seddawy, A; Abouzaid, M; Youssef, A

2008-03-01

Unintended hydrocarbon ingestion is a common reason for pediatric hospitalization in the developing world. To derive a clinical decision rule, to identify patients likely to require a higher level facility (resource-requiring cases), that can be used at primary health care facilities with limited diagnostic and therapeutic resources. A prospective study of children 2 to 59 months old presenting to a poison treatment facility within 2 hours of oral hydrocarbon exposure. History and objective signs were recorded at admission and at 6, 12, 24 and, if present, 48 hours. Inclusion in the resource-requiring outcome group required: oxygen saturation <94%; any CNS depression; any treatment with (salbutamol); any care in the ICU; or death. 256 met the inclusion criteria and completed the study. Of these, 170 had a course requiring resources unavailable at most primary health care facilities, and 86 did not. The presence of wheezing, any alteration in consciousness (lethargy or any restlessness), or a rapid respiratory rate for age (RR >or= 50/min if age < 12 mo, >or= 40/min if age >or= 12 mo) at presentation identified 167 of 170 of these patients (sensitivity 0.98). Thirty-six of 86 patients classified as non-resource requiring were correctly identified (specificity 0.42). No combination of clinical symptoms provided better discrimination while preserving sensitivity. This study suggests a triage decision rule based on the presence of wheezing, altered consciousness, or a rapid respiratory rate within 2 hours of hydrocarbon exposure. Such a rule requires validation in other settings.

A knowledge authoring tool for clinical decision support.

PubMed

Dunsmuir, Dustin; Daniels, Jeremy; Brouse, Christopher; Ford, Simon; Ansermino, J Mark

2008-06-01

Anesthesiologists in the operating room are unable to constantly monitor all data generated by physiological monitors. They are further distracted by clinical and educational tasks. An expert system would ideally provide assistance to the anesthesiologist in this data-rich environment. Clinical monitoring expert systems have not been widely adopted, as traditional methods of knowledge encoding require both expert medical and programming skills, making knowledge acquisition difficult. A software application was developed for use as a knowledge authoring tool for physiological monitoring. This application enables clinicians to create knowledge rules without the need of a knowledge engineer or programmer. These rules are designed to provide clinical diagnosis, explanations and treatment advice for optimal patient care to the clinician in real time. By intelligently combining data from physiological monitors and demographical data sources the expert system can use these rules to assist in monitoring the patient. The knowledge authoring process is simplified by limiting connective relationships between rules. The application is designed to allow open collaboration between communities of clinicians to build a library of rules for clinical use. This design provides clinicians with a system for parameter surveillance and expert advice with a transparent pathway of reasoning. A usability evaluation demonstrated that anesthesiologists can rapidly develop useful rules for use in a predefined clinical scenario.

System for selecting relevant information for decision support.

PubMed

Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

2013-01-01

We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.

The Cape Town Clinical Decision Rule for Streptococcal Pharyngitis in Children.

PubMed

Engel, Mark E; Cohen, Karen; Gounden, Ronald; Kengne, Andre P; Barth, Dylan Dominic; Whitelaw, Andrew C; Francis, Veronica; Badri, Motasim; Stewart, Annemie; Dale, James B; Mayosi, Bongani M; Maartens, Gary

2017-03-01

Existing clinical decision rules (CDRs) to diagnose group A streptococcal (GAS) pharyngitis have not been validated in sub-Saharan Africa. We developed a locally applicable CDR while evaluating existing CDRs for diagnosing GAS pharyngitis in South African children. We conducted a prospective cohort study and enrolled 997 children 3-15 years of age presenting to primary care clinics with a complaint of sore throat, and whose parents provided consent. Main outcome measures were signs and symptoms of pharyngitis and a positive GAS culture from a throat swab. Bivariate and multivariate analyses were used to develop the CDR. In addition, the diagnostic effectiveness of 6 existing rules for predicting a positive culture in our cohort was assessed. A total of 206 of 982 children (21%) had a positive GAS culture. Tonsillar swelling, tonsillar exudates, tender or enlarged anterior cervical lymph nodes, absence of cough and absence of rhinorrhea were associated with positive cultures in bivariate and multivariate analyses. Four variables (tonsillar swelling and one of tonsillar exudate, no rhinorrhea, no cough), when used in a cumulative score, showed 83.7% sensitivity and 32.2% specificity for GAS pharyngitis. Of existing rules tested, the rule by McIsaac et al had the highest positive predictive value (28%), but missed 49% of the culture-positive children who should have been treated. The new 4-variable CDR for GAS pharyngitis (ie, tonsillar swelling and one of tonsillar exudate, no rhinorrhea, no cough) outperformed existing rules for GAS pharyngitis diagnosis in children with symptomatic sore throat in Cape Town.

A decision-support system for the analysis of clinical practice patterns.

PubMed

Balas, E A; Li, Z R; Mitchell, J A; Spencer, D C; Brent, E; Ewigman, B G

1994-01-01

Several studies documented substantial variation in medical practice patterns, but physicians often do not have adequate information on the cumulative clinical and financial effects of their decisions. The purpose of developing an expert system for the analysis of clinical practice patterns was to assist providers in analyzing and improving the process and outcome of patient care. The developed QFES (Quality Feedback Expert System) helps users in the definition and evaluation of measurable quality improvement objectives. Based on objectives and actual clinical data, several measures can be calculated (utilization of procedures, annualized cost effect of using a particular procedure, and expected utilization based on peer-comparison and case-mix adjustment). The quality management rules help to detect important discrepancies among members of the selected provider group and compare performance with objectives. The system incorporates a variety of data and knowledge bases: (i) clinical data on actual practice patterns, (ii) frames of quality parameters derived from clinical practice guidelines, and (iii) rules of quality management for data analysis. An analysis of practice patterns of 12 family physicians in the management of urinary tract infections illustrates the use of the system.

Characterising bias in regulatory risk and decision analysis: An analysis of heuristics applied in health technology appraisal, chemicals regulation, and climate change governance.

PubMed

MacGillivray, Brian H

2017-08-01

In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.

Rule acquisition in formal decision contexts based on formal, object-oriented and property-oriented concept lattices.

PubMed

Ren, Yue; Li, Jinhai; Aswani Kumar, Cherukuri; Liu, Wenqi

2014-01-01

Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form: "if conditions 1,2,…, and m hold, then decisions hold." In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency.

Rule Acquisition in Formal Decision Contexts Based on Formal, Object-Oriented and Property-Oriented Concept Lattices

PubMed Central

Ren, Yue; Aswani Kumar, Cherukuri; Liu, Wenqi

2014-01-01

Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form: “if conditions 1,2,…, and m hold, then decisions hold.” In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency. PMID:25165744

Flexible functional regression methods for estimating individualized treatment regimes.

PubMed

Ciarleglio, Adam; Petkova, Eva; Tarpey, Thaddeus; Ogden, R Todd

2016-01-01

A major focus of personalized medicine is on the development of individualized treatment rules. Good decision rules have the potential to significantly advance patient care and reduce the burden of a host of diseases. Statistical methods for developing such rules are progressing rapidly, but few methods have considered the use of pre-treatment functional data to guide in decision-making. Furthermore, those methods that do allow for the incorporation of functional pre-treatment covariates typically make strong assumptions about the relationships between the functional covariates and the response of interest. We propose two approaches for using functional data to select an optimal treatment that address some of the shortcomings of previously developed methods. Specifically, we combine the flexibility of functional additive regression models with Q -learning or A -learning in order to obtain treatment decision rules. Properties of the corresponding estimators are discussed. Our approaches are evaluated in several realistic settings using synthetic data and are applied to real data arising from a clinical trial comparing two treatments for major depressive disorder in which baseline imaging data are available for subjects who are subsequently treated.

A predictive approach to selecting the size of a clinical trial, based on subjective clinical opinion.

PubMed

Spiegelhalter, D J; Freedman, L S

1986-01-01

The 'textbook' approach to determining sample size in a clinical trial has some fundamental weaknesses which we discuss. We describe a new predictive method which takes account of prior clinical opinion about the treatment difference. The method adopts the point of clinical equivalence (determined by interviewing the clinical participants) as the null hypothesis. Decision rules at the end of the study are based on whether the interval estimate of the treatment difference (classical or Bayesian) includes the null hypothesis. The prior distribution is used to predict the probabilities of making the decisions to use one or other treatment or to reserve final judgement. It is recommended that sample size be chosen to control the predicted probability of the last of these decisions. An example is given from a multi-centre trial of superficial bladder cancer.

Incremental cost effectiveness evaluation in clinical research.

PubMed

Krummenauer, Frank; Landwehr, I

2005-01-28

The health economic evaluation of therapeutic and diagnostic strategies is of increasing importance in clinical research. Therefore also clinical trialists have to involve health economic aspects more frequently. However, whereas they are quite familiar with classical effect measures in clinical trials, the corresponding parameters in health economic evaluation of therapeutic and diagnostic procedures are still not this common. The concepts of incremental cost effectiveness ratios (ICERs) and incremental net health benefit (INHB) will be illustrated and contrasted along the cost effectiveness evaluation of cataract surgery with monofocal and multifocal intraocular lenses. ICERs relate the costs of a treatment to its clinical benefit in terms of a ratio expression (indexed as Euro per clinical benefit unit). Therefore ICERs can be directly compared to a pre-specified willingness to pay (WTP) benchmark, which represents the maximum costs, health insurers would invest to achieve one clinical benefit unit. INHBs estimate a treatment's net clinical benefit after accounting for its cost increase versus an established therapeutic standard. Resource allocation rules can be formulated by means of both effect measures. Both the ICER and the INHB approach enable the definition of directional resource allocation rules. The allocation decisions arising from these rules are identical, as long as the willingness to pay benchmark is fixed in advance. Therefore both strategies crucially call for a priori determination of both the underlying clinical benefit endpoint (such as gain in vision lines after cataract surgery or gain in quality-adjusted life years) and the corresponding willingness to pay benchmark. The use of incremental cost effectiveness and net health benefit estimates provides a rationale for health economic allocation discussions and founding decisions. It implies the same requirements on trial protocols as yet established for clinical trials, that is the a priori definition of primary hypotheses (formulated as an allocation rule involving a pre-specified willingness to pay benchmark) and the primary clinical benefit endpoint (as a rationale for effectiveness evaluation).

Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines

PubMed Central

2010-01-01

Background Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs. The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase. Methods A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA). Results The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows. Conclusions The framework is an effective solution for computerizing clinical guidelines as it allows for quick development, evaluation and human-readable visualization of the Rules and has a good performance. By monitoring the parameters of the patient to automatically detect exceptional situations and problems and by notifying the medical staff of tasks that need to be performed, the computerized sedation guideline improves the execution of the guideline. PMID:20082700

Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines.

PubMed

Ongenae, Femke; De Backere, Femke; Steurbaut, Kristof; Colpaert, Kirsten; Kerckhove, Wannes; Decruyenaere, Johan; De Turck, Filip

2010-01-18

Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs.The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase. A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA). The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows. The framework is an effective solution for computerizing clinical guidelines as it allows for quick development, evaluation and human-readable visualization of the Rules and has a good performance. By monitoring the parameters of the patient to automatically detect exceptional situations and problems and by notifying the medical staff of tasks that need to be performed, the computerized sedation guideline improves the execution of the guideline.

Risk factors for invasive fungal disease in critically ill adult patients: a systematic review.

PubMed

Muskett, Hannah; Shahin, Jason; Eyres, Gavin; Harvey, Sheila; Rowan, Kathy; Harrison, David

2011-01-01

Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation.

Risk factors for invasive fungal disease in critically ill adult patients: a systematic review

PubMed Central

2011-01-01

Introduction Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. Methods An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Results Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. Conclusions This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation. PMID:22126425

Computer-assisted categorizing of head computed tomography reports for clinical decision rule research.

PubMed

Wall, Stephen P; Mayorga, Oliver; Banfield, Christine E; Wall, Mark E; Aisic, Ilan; Auerbach, Carl; Gennis, Paul

2006-11-01

To develop software that categorizes electronic head computed tomography (CT) reports into groups useful for clinical decision rule research. Data were obtained from the Second National Emergency X-Radiography Utilization Study, a cohort of head injury patients having received head CT. CT reports were reviewed manually for presence or absence of clinically important subdural or epidural hematoma, defined as greater than 1.0 cm in width or causing mass effect. Manual categorization was done by 2 independent researchers blinded to each other's results. A third researcher adjudicated discrepancies. A random sample of 300 reports with radiologic abnormalities was selected for software development. After excluding reports categorized manually or by software as indeterminate (neither positive nor negative), we calculated sensitivity and specificity by using manual categorization as the standard. System efficiency was defined as the percentage of reports categorized as positive or negative, regardless of accuracy. Software was refined until analysis of the training data yielded sensitivity and specificity approximating 95% and efficiency exceeding 75%. To test the system, we calculated sensitivity, specificity, and efficiency, using the remaining 1,911 reports. Of the 1,911 reports, 160 had clinically important subdural or epidural hematoma. The software exhibited good agreement with manual categorization of all reports, including indeterminate ones (weighted kappa 0.62; 95% confidence interval [CI] 0.58 to 0.65). Sensitivity, specificity, and efficiency of the computerized system for identifying manual positives and negatives were 96% (95% CI 91% to 98%), 98% (95% CI 98% to 99%), and 79% (95% CI 77% to 80%), respectively. Categorizing head CT reports by computer for clinical decision rule research is feasible.

From data mining rules to medical logical modules and medical advices.

PubMed

Gomoi, Valentin; Vida, Mihaela; Robu, Raul; Stoicu-Tivadar, Vasile; Bernad, Elena; Lupşe, Oana

2013-01-01

Using data mining in collaboration with Clinical Decision Support Systems adds new knowledge as support for medical diagnosis. The current work presents a tool which translates data mining rules supporting generation of medical advices to Arden Syntax formalism. The developed system was tested with data related to 2326 births that took place in 2010 at the Bega Obstetrics - Gynaecology Hospital, Timişoara. Based on processing these data, 14 medical rules regarding the Apgar score were generated and then translated in Arden Syntax language.

Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers.

PubMed

Klement, William; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken J; Osmond, Martin H; Verter, Vedat

2012-03-01

Using an automatic data-driven approach, this paper develops a prediction model that achieves more balanced performance (in terms of sensitivity and specificity) than the Canadian Assessment of Tomography for Childhood Head Injury (CATCH) rule, when predicting the need for computed tomography (CT) imaging of children after a minor head injury. CT is widely considered an effective tool for evaluating patients with minor head trauma who have potentially suffered serious intracranial injury. However, its use poses possible harmful effects, particularly for children, due to exposure to radiation. Safety concerns, along with issues of cost and practice variability, have led to calls for the development of effective methods to decide when CT imaging is needed. Clinical decision rules represent such methods and are normally derived from the analysis of large prospectively collected patient data sets. The CATCH rule was created by a group of Canadian pediatric emergency physicians to support the decision of referring children with minor head injury to CT imaging. The goal of the CATCH rule was to maximize the sensitivity of predictions of potential intracranial lesion while keeping specificity at a reasonable level. After extensive analysis of the CATCH data set, characterized by severe class imbalance, and after a thorough evaluation of several data mining methods, we derived an ensemble of multiple Naive Bayes classifiers as the prediction model for CT imaging decisions. In the first phase of the experiment we compared the proposed ensemble model to other ensemble models employing rule-, tree- and instance-based member classifiers. Our prediction model demonstrated the best performance in terms of AUC, G-mean and sensitivity measures. In the second phase, using a bootstrapping experiment similar to that reported by the CATCH investigators, we showed that the proposed ensemble model achieved a more balanced predictive performance than the CATCH rule with an average sensitivity of 82.8% and an average specificity of 74.4% (vs. 98.1% and 50.0% for the CATCH rule respectively). Automatically derived prediction models cannot replace a physician's acumen. However, they help establish reference performance indicators for the purpose of developing clinical decision rules so the trade-off between prediction sensitivity and specificity is better understood. Copyright © 2011 Elsevier B.V. All rights reserved.

Taking a gamble or playing by the rules: Dissociable prefrontal systems implicated in probabilistic versus deterministic rule-based decisions

PubMed Central

Bhanji, Jamil P.; Beer, Jennifer S.; Bunge, Silvia A.

2014-01-01

A decision may be difficult because complex information processing is required to evaluate choices according to deterministic decision rules and/or because it is not certain which choice will lead to the best outcome in a probabilistic context. Factors that tax decision making such as decision rule complexity and low decision certainty should be disambiguated for a more complete understanding of the decision making process. Previous studies have examined the brain regions that are modulated by decision rule complexity or by decision certainty but have not examined these factors together in the context of a single task or study. In the present functional magnetic resonance imaging study, both decision rule complexity and decision certainty were varied in comparable decision tasks. Further, the level of certainty about which choice to make (choice certainty) was varied separately from certainty about the final outcome resulting from a choice (outcome certainty). Lateral prefrontal cortex, dorsal anterior cingulate cortex, and bilateral anterior insula were modulated by decision rule complexity. Anterior insula was engaged more strongly by low than high choice certainty decisions, whereas ventromedial prefrontal cortex showed the opposite pattern. These regions showed no effect of the independent manipulation of outcome certainty. The results disambiguate the influence of decision rule complexity, choice certainty, and outcome certainty on activity in diverse brain regions that have been implicated in decision making. Lateral prefrontal cortex plays a key role in implementing deterministic decision rules, ventromedial prefrontal cortex in probabilistic rules, and anterior insula in both. PMID:19781652

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development.

PubMed

McCoy, Allison B; Wright, Adam; Sittig, Dean F

2015-09-01

Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. Significant improvements in the EHR certification and implementation procedures are necessary. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Abortion foes get turn to ask Supreme Court for constitutional protection.

PubMed

Denniston, L

1994-04-28

The US Supreme Court began hearing arguments on the constitutionality of a Florida judge's order which placed limits on anti-abortion protesting. This case will be the last abortion--related decision for Justice Harry A. Blackmun, who was the author of the original decision granting the right to abortion in Roe vs. Wade, before retiring from the Court in September 1994. Anti-abortion activists claim 1st Amendment protection, much the same as Dr. Martin Luther King's marches in advancing Blacks' civil rights. The case involved a Melbourne abortion clinic. The murder of Dr. Gunn outside an abortion clinic in Pensacola, Florida, will be used to support the need for protection from extremist violence. The conflict appears to be over the right to save women's right to abortion and over simple, peaceful protests and prayers against abortion. One anti-abortion foe, affiliated with Operational Rescue and initiating the appeal to the Supreme Court, is scheduled to testify before the Court: Judy Madsen, a protester who has counseled outside clinics. Ms. Madsen says she is exercising her freedom to protect human life. Other testimony will come from Reverend Ed Martin of Ocala, Rescue America's founder, and Shirley Hobbs, a homemaker from Orlando. Representation will be made by lawyer Matthew Staver, who will argue that the ruling was directed to a political position. Other support will come from religious and anti-abortion groups and the AFL-CIO. Testifying for the clinic, the Aware Women's Center for Choice, will be the owner and operator Patricia Baird Windle. Over the past 5 years, the Melbourne Clinic had been a target for the nationwide anti-abortion campaign by Operation Rescue. Because of the conflicting rulings between the Florida Supreme Court, which ruled to keep protesters away from clinic grounds and staff homes, and 11th US Circuit Court of Appeals ruling of unconstitutionality, no protection is afforded the clinic. Previous protection had occurred due to a 1992 judge's order. Clinic lawyer, Talbot D'Alemberte, president of Florida State University and former president of the American Bar Association, will argue that the issue is about intimidation. The Clinton administration's Solicitor General Drew S. Days III will support Seminole County Circuit Court Judge Robert S. McGregor's decision limiting protester activity.

Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus.

PubMed

Kantor, M; Wright, A; Burton, M; Fraser, G; Krall, M; Maviglia, S; Mohammed-Rajput, N; Simonaitis, L; Sonnenberg, F; Middleton, B

2011-01-01

Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known. We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care. We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites. The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines. Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the provider and providing messages that are actionable recommendations.

A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

PubMed Central

Murphy, Donald R; Hurwitz, Eric L; Nelson, Craig F

2008-01-01

Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source) and 3 (which investigates perpetuating factors of the pain experience). In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed. PMID:18694490

Method to integrate clinical guidelines into the electronic health record (EHR) by applying the archetypes approach.

PubMed

Garcia, Diego; Moro, Claudia Maria Cabral; Cicogna, Paulo Eduardo; Carvalho, Deborah Ribeiro

2013-01-01

Clinical guidelines are documents that assist healthcare professionals, facilitating and standardizing diagnosis, management, and treatment in specific areas. Computerized guidelines as decision support systems (DSS) attempt to increase the performance of tasks and facilitate the use of guidelines. Most DSS are not integrated into the electronic health record (EHR), ordering some degree of rework especially related to data collection. This study's objective was to present a method for integrating clinical guidelines into the EHR. The study developed first a way to identify data and rules contained in the guidelines, and then incorporate rules into an archetype-based EHR. The proposed method tested was anemia treatment in the Chronic Kidney Disease Guideline. The phases of the method are: data and rules identification; archetypes elaboration; rules definition and inclusion in inference engine; and DSS-EHR integration and validation. The main feature of the proposed method is that it is generic and can be applied toany type of guideline.

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma.

PubMed

Goldberg, Howard S; Paterno, Marilyn D; Grundmeier, Robert W; Rocha, Beatriz H; Hoffman, Jeffrey M; Tham, Eric; Swietlik, Marguerite; Schaeffer, Molly H; Pabbathi, Deepika; Deakyne, Sara J; Kuppermann, Nathan; Dayan, Peter S

2016-03-01

To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma. We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians. The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service. The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock. With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of the performance of statistical tests used in making cleanup decisions at Superfund sites. Part 1: Choosing an appropriate statistical test

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

Berman, D.W.; Allen, B.C.; Van Landingham, C.B.

1998-12-31

The decision rules commonly employed to determine the need for cleanup are evaluated both to identify conditions under which they lead to erroneous conclusions and to quantify the rate that such errors occur. Their performance is also compared with that of other applicable decision rules. The authors based the evaluation of decision rules on simulations. Results are presented as power curves. These curves demonstrate that the degree of statistical control achieved is independent of the form of the null hypothesis. The loss of statistical control that occurs when a decision rule is applied to a data set that does notmore » satisfy the rule`s validity criteria is also clearly demonstrated. Some of the rules evaluated do not offer the formal statistical control that is an inherent design feature of other rules. Nevertheless, results indicate that such informal decision rules may provide superior overall control of error rates, when their application is restricted to data exhibiting particular characteristics. The results reported here are limited to decision rules applied to uncensored and lognormally distributed data. To optimize decision rules, it is necessary to evaluate their behavior when applied to data exhibiting a range of characteristics that bracket those common to field data. The performance of decision rules applied to data sets exhibiting a broader range of characteristics is reported in the second paper of this study.« less

Evaluation of a rule base for decision making in general practice.

PubMed Central

Essex, B; Healy, M

1994-01-01

BACKGROUND. Decision making in general practice relies heavily on judgmental expertise. It should be possible to codify this expertise into rules and principles. AIM. A study was undertaken to evaluate the effectiveness, of rules from a rule base designed to improve students' and trainees' management decisions relating to patients seen in general practice. METHOD. The rule base was developed after studying decisions about and management of thousands of patients seen in one general practice over an eight year period. Vignettes were presented to 93 fourth year medical students and 179 general practitioner trainees. They recorded their perception and management of each case before and after being presented with a selection of relevant rules. Participants also commented on their level of agreement with each of the rules provided with the vignettes. A panel of five independent assessors then rated as good, acceptable or poor, the participants' perception and management of each case before and after seeing the rules. RESULTS. Exposure to a few selected rules of thumb improved the problem perception and management decisions of both undergraduates and trainees. The degree of improvement was not related to previous experience or to the stated level of agreement with the proposed rules. The assessors identified difficulties students and trainees experienced in changing their perceptions and management decisions when the rules suggested options they had not considered. CONCLUSION. The rules developed to improve decision making skills in general practice are effective when used with vignettes. The next phase is to transform the rule base into an expert system to train students and doctors to acquire decision making skills. It could also be used to provide decision support when confronted with difficult management decisions in general practice. PMID:8204334

Diagnostic accuracy and reproducibility of the Ottawa Knee Rule vs the Pittsburgh Decision Rule.

PubMed

Cheung, Tung C; Tank, Yeliz; Breederveld, Roelf S; Tuinebreijer, Wim E; de Lange-de Klerk, Elly S M; Derksen, Robert J

2013-04-01

The aim of this present study was to compare the diagnostic accuracy and reproducibility of 2 clinical decision rules (the Ottawa Knee Rules [OKR] and Pittsburgh Decision Rules [PDR]) developed for selective use of x-rays in the evaluation of isolated knee trauma. Application of a decision rule leads to a more efficient evaluation of knee injuries and a reduction in health care costs. The diagnostic accuracy and reproducibility are compared in this study. A cross-sectional interobserver study was conducted in the emergency department of an urban teaching hospital from October 2008 to July 2009. Two observer groups collected data on standardized case-report forms: emergency medicine residents and surgical residents. Standard knee radiographs were performed in each patient. Participants were patients 18 years and older with isolated knee injuries. Pooled sensitivity and specificity were compared using χ(2) statistics, and interobserver agreement was calculated by using κ statistics. Ninety injuries were assessed. Seven injuries concerned fractures (7.8%). For the OKR, the pooled sensitivity and specificity were 0.86 (95% confidence interval [CI], 0.57-0.96) and 0.27 (95% CI, 0.21-0.35), respectively. The PDR had a pooled sensitivity and specificity of 0.86 (95% CI, 0.57-0.96) and 0.51 (95% CI, 0.44-0.59). The PDR was significantly (P = .002) more specific. The κ values for the OKR and PDR were 0.51 (95% CI, 0.32-0.71) and 0.71 (95% CI, 0.57-0.86), respectively. The PDR was found to be more specific than the OKR, with equal sensitivity. Interobserver agreement was moderate for the OKR and substantial for the PDR. Copyright © 2013 Elsevier Inc. All rights reserved.

Accelerating clinical development of HIV vaccine strategies: methodological challenges and considerations in constructing an optimised multi-arm phase I/II trial design.

PubMed

Richert, Laura; Doussau, Adélaïde; Lelièvre, Jean-Daniel; Arnold, Vincent; Rieux, Véronique; Bouakane, Amel; Lévy, Yves; Chêne, Geneviève; Thiébaut, Rodolphe

2014-02-26

Many candidate vaccine strategies against human immunodeficiency virus (HIV) infection are under study, but their clinical development is lengthy and iterative. To accelerate HIV vaccine development optimised trial designs are needed. We propose a randomised multi-arm phase I/II design for early stage development of several vaccine strategies, aiming at rapidly discarding those that are unsafe or non-immunogenic. We explored early stage designs to evaluate both the safety and the immunogenicity of four heterologous prime-boost HIV vaccine strategies in parallel. One of the vaccines used as a prime and boost in the different strategies (vaccine 1) has yet to be tested in humans, thus requiring a phase I safety evaluation. However, its toxicity risk is considered minimal based on data from similar vaccines. We newly adapted a randomised phase II trial by integrating an early safety decision rule, emulating that of a phase I study. We evaluated the operating characteristics of the proposed design in simulation studies with either a fixed-sample frequentist or a continuous Bayesian safety decision rule and projected timelines for the trial. We propose a randomised four-arm phase I/II design with two independent binary endpoints for safety and immunogenicity. Immunogenicity evaluation at trial end is based on a single-stage Fleming design per arm, comparing the observed proportion of responders in an immunogenicity screening assay to an unacceptably low proportion, without direct comparisons between arms. Randomisation limits heterogeneity in volunteer characteristics between arms. To avoid exposure of additional participants to an unsafe vaccine during the vaccine boost phase, an early safety decision rule is imposed on the arm starting with vaccine 1 injections. In simulations of the design with either decision rule, the risks of erroneous conclusions were controlled <15%. Flexibility in trial conduct is greater with the continuous Bayesian rule. A 12-month gain in timelines is expected by this optimised design. Other existing designs such as bivariate or seamless phase I/II designs did not offer a clear-cut alternative. By combining phase I and phase II evaluations in a multi-arm trial, the proposed optimised design allows for accelerating early stage clinical development of HIV vaccine strategies.

A critical comparison of clinical decision instruments for computed tomographic scanning in mild closed traumatic brain injury in adolescents and adults.

PubMed

Stein, Sherman C; Fabbri, Andrea; Servadei, Franco; Glick, Henry A

2009-02-01

A number of clinical decision aids have been introduced to limit unnecessary computed tomographic scans in patients with mild traumatic brain injury. These aids differ in the risk factors they use to recommend a scan. We compare the instruments according to their sensitivity and specificity and recommend ones based on incremental benefit of correctly classifying patients as having surgical, nonsurgical, or no intracranial lesions. We performed a secondary analysis of prospectively collected database from 7,955 patients aged 10 years or older with mild traumatic brain injury to compare sensitivity and specificity of 6 common clinical decision strategies: the Canadian CT Head Rule, the Neurotraumatology Committee of the World Federation of Neurosurgical Societies, the New Orleans, the National Emergency X-Radiography Utilization Study II (NEXUS-II), the National Institute of Clinical Excellence guideline, and the Scandinavian Neurotrauma Committee guideline. Excluded from the database were patients for whom the history of trauma was unclear, the initial Glasgow Coma Scale score was less than 14, the injury was penetrating, vital signs were unstable, or who refused diagnostic tests. Patients revisiting the emergency department within 7 days were counted only once. The percentage of scans that would have been required by applying each of the 6 aids were Canadian CT head rule (high risk only) 53%, Canadian (medium & high risk) 56%, the Neurotraumatology Committee of the World Federation of Neurosurgical Societies 56%, New Orleans 69%, NEXUS-II 56%, National Institute of Clinical Excellence 71%, and the Scandinavian 50%. The 6 decision aids' sensitivities for surgical hematomas could not be distinguished statistically (P>.05). Sensitivity was 100% (95% confidence interval [CI] 96% to 100%) for NEXUS-II, 98.1% (95% CI 93% to 100%) for National Institute of Clinical Excellence, and 99.1% (95% CI 94% to 100%) for the other 4 clinical decision instruments. Sensitivity for any intracranial lesion ranged from 95.7% (95% CI 93% to 97%) (Scandinavian) to 100% (95% CI 98% to 100%) (National Institute of Clinical Excellence). In contrast, specificities varied between 30.9% (95% CI 30% to 32%) (National Institute of Clinical Excellence) and 52.9% (95% CI 52% to 54) (Scandinavian). NEXUS-II and the Scandinavian clinical decision aids displayed the best combination of sensitivity and specificity in this patient population. However, we cannot demonstrate that the higher sensitivity of NEXUS-II for surgical hematomas is statistically significant. Therefore, choosing which of the 2 clinical decision instruments to use must be based on decisionmakers' attitudes toward risk.

Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study.

PubMed

Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford

2015-11-01

To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Termination of resuscitation in the prehospital setting: A comparison of decisions in clinical practice vs. recommendations of a termination rule.

PubMed

Verhaert, Dominique V M; Bonnes, Judith L; Nas, Joris; Keuper, Wessel; van Grunsven, Pierre M; Smeets, Joep L R M; de Boer, Menko Jan; Brouwer, Marc A

2016-03-01

Of the proposed algorithms that provide guidance for in-field termination of resuscitation (TOR) decisions, the guidelines for cardiopulmonary resuscitation (CPR) refer to the basic and advanced life support (ALS)-TOR rules. To assess the potential consequences of implementation of the ALS-TOR rule, we performed a case-by-case evaluation of our in-field termination decisions and assessed the corresponding recommendations of the ALS-TOR rule. Cohort of non-traumatic out-of-hospital cardiac arrest (OHCA)-patients who were resuscitated by the ALS-practising emergency medical service (EMS) in the Nijmegen area (2008-2011). The ALS-TOR rule recommends termination in case all following criteria are met: unwitnessed arrest, no bystander CPR, no shock delivery, no return of spontaneous circulation (ROSC). Of the 598 cases reviewed, resuscitative efforts were terminated in the field in 46% and 15% survived to discharge. The ALS-TOR rule would have recommended in-field termination in only 6% of patients, due to high percentages of witnessed arrests (73%) and bystander CPR (54%). In current practice, absence of ROSC was the most important determinant of termination [aOR 35.6 (95% CI 18.3-69.3)]. Weaker associations were found for: unwitnessed and non-public arrests, non-shockable initial rhythms and longer EMS-response times. While designed to optimise hospital transportations, application of the ALS-TOR rule would almost double our hospital transportation rate to over 90% of OHCA-cases due to the favourable arrest circumstances in our region. Prior to implementation of the ALS-TOR rule, local evaluation of the potential consequences for the efficiency of triage is to be recommended and initiatives to improve field-triage for ALS-based EMS-systems are eagerly awaited. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Derivation and Validation of a Clostridium difficile Infection Recurrence Prediction Rule in a National Cohort of Veterans.

PubMed

Reveles, Kelly R; Mortensen, Eric M; Koeller, Jim M; Lawson, Kenneth A; Pugh, Mary Jo V; Rumbellow, Sarah A; Argamany, Jacqueline R; Frei, Christopher R

2018-03-01

Prior studies have identified risk factors for recurrent Clostridium difficile infection (CDI), but few studies have integrated these factors into a clinical prediction rule that can aid clinical decision-making. The objectives of this study were to derive and validate a CDI recurrence prediction rule to identify patients at risk for first recurrence in a national cohort of veterans. Retrospective cohort study. Veterans Affairs Informatics and Computing Infrastructure. A total of 22,615 adult Veterans Health Administration beneficiaries with first-episode CDI between October 1, 2002, and September 30, 2014; of these patients, 7538 were assigned to the derivation cohort and 15,077 to the validation cohort. A 60-day CDI recurrence prediction rule was created in a derivation cohort using backward logistic regression. Those variables significant at p<0.01 were assigned an integer score proportional to the regression coefficient. The model was then validated in the derivation cohort and a separate validation cohort. Patients were then split into three risk categories, and rates of recurrence were described for each category. The CDI recurrence prediction rule included the following predictor variables with their respective point values: prior third- and fourth-generation cephalosporins (1 point), prior proton pump inhibitors (1 point), prior antidiarrheals (1 point), nonsevere CDI (2 points), and community-onset CDI (3 points). In the derivation cohort, the 60-day CDI recurrence risk for each score ranged from 7.5% (0 points) to 57.9% (8 points). The risk score was strongly correlated with recurrence (R 2  = 0.94). Patients were split into low-risk (0-2 points), medium-risk (3-5 points), and high-risk (6-8 points) classes and had the following recurrence rates: 8.9%, 20.2%, and 35.0%, respectively. Findings were similar in the validation cohort. Several CDI and patient-specific factors were independently associated with 60-day CDI recurrence risk. When integrated into a clinical prediction rule, higher risk scores and risk classes were strongly correlated with CDI recurrence. This clinical prediction rule can be used by providers to identify patients at high risk for CDI recurrence and help guide preventive strategy decisions, while accounting for clinical judgment. © 2018 Pharmacotherapy Publications, Inc.

Scheduling rules to achieve lead-time targets in outpatient appointment systems.

PubMed

Nguyen, Thu-Ba T; Sivakumar, Appa Iyer; Graves, Stephen C

2017-12-01

This paper considers how to schedule appointments for outpatients, for a clinic that is subject to appointment lead-time targets for both new and returning patients. We develop heuristic rules, which are the exact and relaxed appointment scheduling rules, to schedule each new patient appointment (only) in light of uncertainty about future arrivals. The scheduling rules entail two decisions. First, the rules need to determine whether or not a patient's request can be accepted; then, if the request is not rejected, the rules prescribe how to assign the patient to an available slot. The intent of the scheduling rules is to maximize the utilization of the planned resource (i.e., the physician staff), or equivalently to maximize the number of patients that are admitted, while maintaining the service targets on the median, the 95th percentile, and the maximum appointment lead-times. We test the proposed scheduling rules with numerical experiments using real data from the chosen clinic of Tan Tock Seng hospital in Singapore. The results show the efficiency and the efficacy of the scheduling rules, in terms of the service-target satisfaction and the resource utilization. From the sensitivity analysis, we find that the performance of the proposed scheduling rules is fairly robust to the specification of the established lead-time targets.

Can SLE classification rules be effectively applied to diagnose unclear SLE cases?

PubMed Central

Mesa, Annia; Fernandez, Mitch; Wu, Wensong; Narasimhan, Giri; Greidinger, Eric L.; Mills, DeEtta K.

2016-01-01

Summary Objective Develop a novel classification criteria to distinguish between unclear SLE and MCTD cases. Methods A total of 205 variables from 111 SLE and 55 MCTD patients were evaluated to uncover unique molecular and clinical markers for each disease. Binomial logistic regressions (BLR) were performed on currently used SLE and MCTD classification criteria sets to obtain six reduced models with power to discriminate between unclear SLE and MCTD patients which were confirmed by Receiving Operating Characteristic (ROC) curve. Decision trees were employed to delineate novel classification rules to discriminate between unclear SLE and MCTD patients. Results SLE and MCTD patients exhibited contrasting molecular markers and clinical manifestations. Furthermore, reduced models highlighted SLE patients exhibit prevalence of skin rashes and renal disease while MCTD cases show dominance of myositis and muscle weakness. Additionally decision trees analyses revealed a novel classification rule tailored to differentiate unclear SLE and MCTD patients (Lu-vs-M) with an overall accuracy of 88%. Conclusions Validation of our novel proposed classification rule (Lu-vs-M) includes novel contrasting characteristics (calcinosis, CPK elevated and anti-IgM reactivity for U1-70K, U1A and U1C) between SLE and MCTD patients and showed a 33% improvement in distinguishing these disorders when compare to currently used classification criteria sets. Pending additional validation, our novel classification rule is a promising method to distinguish between patients with unclear SLE and MCTD diagnosis. PMID:27353506

Identifying Emergency Department Patients at Low Risk for a Variceal Source of Upper Gastrointestinal Hemorrhage.

PubMed

Klein, Lauren R; Money, Joel; Maharaj, Kaveesh; Robinson, Aaron; Lai, Tarissa; Driver, Brian E

2017-11-01

Assessing the likelihood of a variceal versus nonvariceal source of upper gastrointestinal bleeding (UGIB) guides therapy, but can be difficult to determine on clinical grounds. The objective of this study was to determine if there are easily ascertainable clinical and laboratory findings that can identify a patient as low risk for a variceal source of hemorrhage. This was a retrospective cohort study of adult ED patients with UGIB between January 2008 and December 2014 who had upper endoscopy performed during hospitalization. Clinical and laboratory data were abstracted from the medical record. The source of the UGIB was defined as variceal or nonvariceal based on endoscopic reports. Binary recursive partitioning was utilized to create a clinical decision rule. The rule was internally validated and test characteristics were calculated with 1,000 bootstrap replications. A total of 719 patients were identified; mean age was 55 years and 61% were male. There were 71 (10%) patients with a variceal UGIB identified on endoscopy. Binary recursive partitioning yielded a two-step decision rule (platelet count > 200 × 10 9 /L and an international normalized ratio [INR] < 1.3), which identified patients who were low risk for a variceal source of hemorrhage. For the bootstrapped samples, the rule performed with 97% sensitivity (95% confidence interval [CI] = 91%-100%) and 49% specificity (95% CI = 44%-53%). Although this derivation study must be externally validated before widespread use, patients presenting to the ED with an acute UGIB with platelet count of >200 × 10 9 /L and an INR of <1.3 may be at very low risk for a variceal source of their upper gastrointestinal hemorrhage. © 2017 by the Society for Academic Emergency Medicine.

Are plain radiographs sufficient to exclude cervical spine injuries in low-risk adults?

PubMed

Hunter, Benton R; Keim, Samuel M; Seupaul, Rawle A; Hern, Gene

2014-02-01

The routine use of clinical decision rules and three-view plain radiography to clear the cervical spine in blunt trauma patients has been recently called into question. In low-risk adult blunt trauma patients, can plain radiographs adequately exclude cervical spine injury when clinical prediction rules cannot? Four observational studies investigating the performance of plain radiographs in detecting cervical spine injury in low-risk adult blunt trauma patients were reviewed. The consistently poor performance of plain radiographs to rule out cervical spine injury in adult blunt trauma victims is concerning. Large, rigorously performed prospective trials focusing on low- or low/moderate-risk patients will be needed to truly define the utility of plain radiographs of the cervical spine in blunt trauma. Copyright © 2014 Elsevier Inc. All rights reserved.

Oxytocin conditions trait-based rule adherence

PubMed Central

De Dreu, Carsten K.W.

2017-01-01

Abstract Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive rule adherence is reduced by oxytocin—a hypothalamic neuropeptide that biases the biobehavioural approach-avoidance system. Participants (N = 139) self-administered oxytocin or placebo intranasally, and reported their need for structure and approach-avoidance sensitivity. Next, participants made binary decisions and were given an arbitrary rule that demanded to forgo financial benefits. Under oxytocin, participants violated the rule more often, especially when they had high need for structure and high approach sensitivity. Possibly, oxytocin dampens the need for a highly structured environment and enables individuals to flexibly trade-off internal desires against external restrictions. Implications for the treatment of clinical disorders marked by maladaptive rule adherence are discussed. PMID:27664999

Feasibility of Extracting Key Elements from ClinicalTrials.gov to Support Clinicians' Patient Care Decisions.

PubMed

Kim, Heejun; Bian, Jiantao; Mostafa, Javed; Jonnalagadda, Siddhartha; Del Fiol, Guilherme

2016-01-01

Motivation: Clinicians need up-to-date evidence from high quality clinical trials to support clinical decisions. However, applying evidence from the primary literature requires significant effort. Objective: To examine the feasibility of automatically extracting key clinical trial information from ClinicalTrials.gov. Methods: We assessed the coverage of ClinicalTrials.gov for high quality clinical studies that are indexed in PubMed. Using 140 random ClinicalTrials.gov records, we developed and tested rules for the automatic extraction of key information. Results: The rate of high quality clinical trial registration in ClinicalTrials.gov increased from 0.2% in 2005 to 17% in 2015. Trials reporting results increased from 3% in 2005 to 19% in 2015. The accuracy of the automatic extraction algorithm for 10 trial attributes was 90% on average. Future research is needed to improve the algorithm accuracy and to design information displays to optimally present trial information to clinicians.

Trials, tricks and transparency: how disclosure rules affect clinical knowledge.

PubMed

Dahm, Matthias; González, Paula; Porteiro, Nicolás

2009-12-01

Scandals of selective reporting of clinical trial results by pharmaceutical firms have underlined the need for more transparency in clinical trials. We provide a theoretical framework which reproduces incentives for selective reporting and yields three key implications concerning regulation. First, a compulsory clinical trial registry complemented through a voluntary clinical trial results database can implement full transparency (the existence of all trials as well as their results is known). Second, full transparency comes at a price. It has a deterrence effect on the incentives to conduct clinical trials, as it reduces the firms' gains from trials. Third, in principle, a voluntary clinical trial results database without a compulsory registry is a superior regulatory tool; but we provide some qualified support for additional compulsory registries when medical decision-makers cannot anticipate correctly the drug companies' decisions whether to conduct trials.

Economic Considerations of Early Rule-In/Rule-Out Algorithms for The Diagnosis of Myocardial Infarction in The Emergency Department Using Cardiac Troponin and Glycemic Biomarkers.

PubMed

Shortt, Colleen; Xie, Feng; Whitlock, Richard; Ma, Jinhui; Clayton, Natasha; Sherbino, Jonathan; Hill, Stephen A; Pare, Guillaume; McQueen, Matthew; Mehta, Shamir R; Devereaux, P J; Worster, Andrew; Kavsak, Peter

2017-02-01

We have previously demonstrated the utility of a rule-in/rule-out strategy for myocardial infarction (MI) using glycemic biomarkers in combination with cardiac troponin in the emergency department (ED). Given that the cost of assessing patients with possible MI in the ED is increasing, we sought to compare the health services cost of our previously identified early rule-in/rule-out approaches for MI among patients who present to the ED with symptoms suggestive of acute coronary syndrome (ACS). We compared the cost differences between different rule-in/rule-out strategies for MI using presentation cardiac troponin I (cTnI), high-sensitivity cTnI (hs-cTnI), high-sensitivity cardiac troponin T (hs-cTnT), glucose, and/or hemoglobin A 1c (Hb A 1c ) in 1137 ED patients (7-day MI n = 133) as per our previously defined algorithms and compared them with the European Society of Cardiology (ESC) 0-h algorithm-cutoffs. Costs associated with each decision model were obtained from site-specific sources (length of stay) and provincial sources (Ontario Case Costing Initiative). Algorithms incorporating cardiac troponin and glucose for early rule-in/rule-out were the most cost effective and clinically safest methods (i.e., ≤1 MI missed) for early decision making, with hs-cTnI and glucose yielding lower costs compared to cTnI and glucose, despite the higher price for the hs-cTnI test. The addition of Hb A 1c to the algorithms increased the cost of these algorithms but did not miss any additional patients with MI. Applying the ESC 0-h algorithm-cutoffs for hs-cTnI and hs-cTnT were the most costly. Rule-in/rule-out algorithms incorporating presentation glucose with high-sensitivity cardiac troponin are the safest and most cost-effective options as compared to the ESC 0-h algorithm-cutoffs. © 2016 American Association for Clinical Chemistry.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention.

PubMed

Lobach, David F; Johns, Ellis B; Halpenny, Barbara; Saunders, Toni-Ann; Brzozowski, Jane; Del Fiol, Guilherme; Berry, Donna L; Braun, Ilana M; Finn, Kathleen; Wolfe, Joanne; Abrahm, Janet L; Cooley, Mary E

2016-11-08

Management of uncontrolled symptoms is an important component of quality cancer care. Clinical guidelines are available for optimal symptom management, but are not often integrated into the front lines of care. The use of clinical decision support (CDS) at the point-of-care is an innovative way to incorporate guideline-based symptom management into routine cancer care. The objective of this study was to develop and evaluate a rule-based CDS system to enable management of multiple symptoms in lung cancer patients at the point-of-care. This study was conducted in three phases involving a formative evaluation, a system evaluation, and a contextual evaluation of clinical use. In Phase 1, we conducted iterative usability testing of user interface prototypes with patients and health care providers (HCPs) in two thoracic oncology clinics. In Phase 2, we programmed complex algorithms derived from clinical practice guidelines into a rules engine that used Web services to communicate with the end-user application. Unit testing of algorithms was conducted using a stack-traversal tree-spanning methodology to identify all possible permutations of pathways through each algorithm, to validate accuracy. In Phase 3, we evaluated clinical use of the system among patients and HCPs in the two clinics via observations, structured interviews, and questionnaires. In Phase 1, 13 patients and 5 HCPs engaged in two rounds of formative testing, and suggested improvements leading to revisions until overall usability scores met a priori benchmarks. In Phase 2, symptom management algorithms contained between 29 and 1425 decision nodes, resulting in 19 to 3194 unique pathways per algorithm. Unit testing required 240 person-hours, and integration testing required 40 person-hours. In Phase 3, both patients and HCPs found the system usable and acceptable, and offered suggestions for improvements. A rule-based CDS system for complex symptom management was systematically developed and tested. The complexity of the algorithms required extensive development and innovative testing. The Web service-based approach allowed remote access to CDS knowledge, and could enable scaling and sharing of this knowledge to accelerate availability, and reduce duplication of effort. Patients and HCPs found the system to be usable and useful. ©David F Lobach, Ellis B Johns, Barbara Halpenny, Toni-Ann Saunders, Jane Brzozowski, Guilherme Del Fiol, Donna L Berry, Ilana M Braun, Kathleen Finn, Joanne Wolfe, Janet L Abrahm, Mary E Cooley. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 08.11.2016.

Decision Rules and Group Rationality: Cognitive Gain or Standstill?

PubMed Central

Curşeu, Petru Lucian; Jansen, Rob J. G.; Chappin, Maryse M. H.

2013-01-01

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members’ cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups. PMID:23451050

Decision rules and group rationality: cognitive gain or standstill?

PubMed

Curşeu, Petru Lucian; Jansen, Rob J G; Chappin, Maryse M H

2013-01-01

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members' cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups.

Predictors of one and two years' mortality in patients with colon cancer: A prospective cohort study.

PubMed

Quintana, José M; Antón-Ladislao, Ane; González, Nerea; Lázaro, Santiago; Baré, Marisa; Fernández-de-Larrea, Nerea; Redondo, Maximino; Briones, Eduardo; Escobar, Antonio; Sarasqueta, Cristina; García-Gutierrez, Susana; Aróstegui, Inmaculada

2018-01-01

Tools to aid in the prognosis assessment of colon cancer patients in terms of risk of mortality are needed. Goals of this study are to develop and validate clinical prediction rules for 1- and 2-year mortality in these patients. This is a prospective cohort study of patients diagnosed with colon cancer who underwent surgery at 22 hospitals. The main outcomes were mortality at 1 and 2 years after surgery. Background, clinical parameters, and diagnostic tests findings were evaluated as possible predictors. Multivariable multilevel logistic regression and survival models were used in the analyses to create the clinical prediction rules. Models developed in the derivation sample were validated in another sample of the study. American Society of Anesthesiologists Physical Status Classification System (ASA), Charlson comorbidity index (> = 4), age (>75 years), residual tumor (R2), TNM stage IV and log of lymph nodes ratio (> = -0.53) were predictors of 1-year mortality (C-index (95% CI): 0.865 (0.792-0.938)). Adjuvant chemotherapy was an additional predictor. Again ASA, Charlson Index (> = 4), age (>75 years), log of lymph nodes ratio (> = -0.53), TNM, and residual tumor were predictors of 2-year mortality (C-index:0.821 (0.766-0.876). Chemotherapy was also an additional predictor. These clinical prediction rules show very good predictive abilities of one and two years survival and provide clinicians and patients with an easy and quick-to-use decision tool for use in the clinical decision process while the patient is still in the index admission.

Excusing exclusion: Accounting for rule-breaking and sanctions in a Swedish methadone clinic.

PubMed

Petersson, Frida J M

2013-11-01

Methadone maintenance treatment has been subjected to much debate and controversy in Sweden during the last decades. Thresholds for getting access are high and control policies strict within the programmes. This article analyses how professionals working in a Swedish methadone clinic discuss and decide on appropriate responses to clients' rule-breaking behaviour. The research data consist of field notes from observations of three interprofessional team meetings where different clients' illicit drug use is discussed. A micro-sociological approach and accounts analysis was applied to the data. During their decision-oriented talk at the meetings, the professionals account for: (1) sanctions, (2) nonsanction, (3) mildness. In accounting for (2) and (3), they also account for clients' rule-breaking behaviour. Analysis shows how these ways of accounting are concerned with locating blame and responsibility for the act in question, as well as with constructing excuses and justifications for the clients and for the professionals themselves. In general, these results demonstrate that maintenance treatment in everyday professional decision-making, far from being a neutral evidence-based practice, involves a substantial amount of professional discretion and moral judgements. Sanctions are chosen according to the way in which a deviance from the rules is explained and, in doing so, a certain behaviour is deemed to be serious, dangerous and unacceptable - or excusable. Copyright © 2013 Elsevier B.V. All rights reserved.

Clinical Trials Targeting Aging and Age-Related Multimorbidity

PubMed Central

Crimmins, Eileen M; Grossardt, Brandon R; Crandall, Jill P; Gelfond, Jonathan A L; Harris, Tamara B; Kritchevsky, Stephen B; Manson, JoAnn E; Robinson, Jennifer G; Rocca, Walter A; Temprosa, Marinella; Thomas, Fridtjof; Wallace, Robert; Barzilai, Nir

2017-01-01

Abstract Background There is growing interest in identifying interventions that may increase health span by targeting biological processes underlying aging. The design of efficient and rigorous clinical trials to assess these interventions requires careful consideration of eligibility criteria, outcomes, sample size, and monitoring plans. Methods Experienced geriatrics researchers and clinical trialists collaborated to provide advice on clinical trial design. Results Outcomes based on the accumulation and incidence of age-related chronic diseases are attractive for clinical trials targeting aging. Accumulation and incidence rates of multimorbidity outcomes were developed by selecting at-risk subsets of individuals from three large cohort studies of older individuals. These provide representative benchmark data for decisions on eligibility, duration, and assessment protocols. Monitoring rules should be sensitive to targeting aging-related, rather than disease-specific, outcomes. Conclusions Clinical trials targeting aging are feasible, but require careful design consideration and monitoring rules. PMID:28364543

Does this adult patient with suspected bacteremia require blood cultures?

PubMed

Coburn, Bryan; Morris, Andrew M; Tomlinson, George; Detsky, Allan S

2012-08-01

Clinicians order blood cultures liberally among patients in whom bacteremia is suspected, though a small proportion of blood cultures yield true-positive results. Ordering blood cultures inappropriately may be both wasteful and harmful. To review the accuracy of easily obtained clinical and laboratory findings to inform the decision to obtain blood cultures in suspected bacteremia. A MEDLINE and EMBASE search (inception to April 2012) yielded 35 studies that met inclusion criteria for evaluating the accuracy of clinical variables for bacteremia in adult immunocompetent patients, representing 4566 bacteremia and 25,946 negative blood culture episodes. Data were extracted to determine the prevalence and likelihood ratios (LRs) of findings for bacteremia. The pretest probability of bacteremia varies depending on the clinical context, from low (eg, cellulitis: 2%) to high (eg, septic shock: 69%). Elevated temperatures alone do not accurately predict bacteremia (for ≥38°C [>100.3°F], LR, 1.9 [95% CI, 1.4-2.4]; for ≥38.5°C [>101.2°F], LR, 1.4 [95% CI, 1.1-2.0]), nor does isolated leukocytosis (LR, <1.7). The severity of chills graded on an ordinal scale (shaking chills, LR, 4.7; 95% CI, 3.0-7.2) may be more useful. Both the systemic inflammatory response syndrome (SIRS) and a multivariable decision rule with major and minor criteria are sensitive (but not specific) predictors of bacteremia (SIRS, negative LR, 0.09 [95% CI, 0.03-0.26]; decision rule, negative LR, 0.08 [95% CI, 0.04-0.17]). Blood cultures should not be ordered for adult patients with isolated fever or leukocytosis without considering the pretest probability. SIRS and the decision rule may be helpful in identifying patients who do not need blood cultures. These conclusions do not apply to immunocompromised patients or when endocarditis is suspected.

Evaluation of the safety of C-spine clearance by paramedics: design and methodology

PubMed Central

2011-01-01

Background Canadian Emergency Medical Services annually transport 1.3 million patients with potential neck injuries to local emergency departments. Less than 1% of those patients have a c-spine fracture and even less (0.5%) have a spinal cord injury. Most injuries occur before the arrival of paramedics, not during transport to the hospital, yet most patients are transported in ambulances immobilized. They stay fully immobilized until a bed is available, or until physician assessment and/or X-rays are complete. The prolonged immobilization is often unnecessary and adds to the burden of already overtaxed emergency medical services systems and crowded emergency departments. Methods/Design The goal of this study is to evaluate the safety and potential impact of an active strategy that allows paramedics to assess very low-risk trauma patients using a validated clinical decision rule, the Canadian C-Spine Rule, in order to determine the need for immobilization during transport to the emergency department. This cohort study will be conducted in Ottawa, Canada with one emergency medical service. Paramedics with this service participated in an earlier validation study of the Canadian C-Spine Rule. Three thousand consecutive, alert, stable adult trauma patients with a potential c-spine injury will be enrolled in the study and evaluated using the Canadian C-Spine Rule to determine the need for immobilization. The outcomes that will be assessed include measures of safety (numbers of missed fractures and serious adverse outcomes), measures of clinical impact (proportion of patients transported without immobilization, key time intervals) and performance of the Rule. Discussion Approximately 40% of all very low-risk trauma patients could be transported safely, without c-spine immobilization, if paramedics were empowered to make clinical decisions using the Canadian C-Spine Rule. This safety study is an essential step before allowing all paramedics across Canada to selectively immobilize trauma victims before transport. Once safety and potential impact are established, we intend to implement a multi-centre study to study actual impact. Trial Registration ClinicalTrials.gov NCT01188447 PMID:21284880

46 CFR 201.3 - Authentication of rules, orders, determinations and decisions of the Administration.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Authentication of rules, orders, determinations and decisions of the Administration. 201.3 Section 201.3 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF....3 Authentication of rules, orders, determinations and decisions of the Administration. All rules...

Applying Data Mining Techniques to Extract Hidden Patterns about Breast Cancer Survival in an Iranian Cohort Study.

PubMed

Khalkhali, Hamid Reza; Lotfnezhad Afshar, Hadi; Esnaashari, Omid; Jabbari, Nasrollah

2016-01-01

Breast cancer survival has been analyzed by many standard data mining algorithms. A group of these algorithms belonged to the decision tree category. Ability of the decision tree algorithms in terms of visualizing and formulating of hidden patterns among study variables were main reasons to apply an algorithm from the decision tree category in the current study that has not studied already. The classification and regression trees (CART) was applied to a breast cancer database contained information on 569 patients in 2007-2010. The measurement of Gini impurity used for categorical target variables was utilized. The classification error that is a function of tree size was measured by 10-fold cross-validation experiments. The performance of created model was evaluated by the criteria as accuracy, sensitivity and specificity. The CART model produced a decision tree with 17 nodes, 9 of which were associated with a set of rules. The rules were meaningful clinically. They showed in the if-then format that Stage was the most important variable for predicting breast cancer survival. The scores of accuracy, sensitivity and specificity were: 80.3%, 93.5% and 53%, respectively. The current study model as the first one created by the CART was able to extract useful hidden rules from a relatively small size dataset.

Assessing an AI knowledge-base for asymptomatic liver diseases.

PubMed

Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O

1998-01-01

Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.

Comparison of PECARN, CATCH, and CHALICE rules for children with minor head injury: a prospective cohort study.

PubMed

Easter, Joshua S; Bakes, Katherine; Dhaliwal, Jasmeet; Miller, Michael; Caruso, Emily; Haukoos, Jason S

2014-08-01

We evaluate the diagnostic accuracy of clinical decision rules and physician judgment for identifying clinically important traumatic brain injuries in children with minor head injuries presenting to the emergency department. We prospectively enrolled children younger than 18 years and with minor head injury (Glasgow Coma Scale score 13 to 15), presenting within 24 hours of their injuries. We assessed the ability of 3 clinical decision rules (Canadian Assessment of Tomography for Childhood Head Injury [CATCH], Children's Head Injury Algorithm for the Prediction of Important Clinical Events [CHALICE], and Pediatric Emergency Care Applied Research Network [PECARN]) and 2 measures of physician judgment (estimated of <1% risk of traumatic brain injury and actual computed tomography ordering practice) to predict clinically important traumatic brain injury, as defined by death from traumatic brain injury, need for neurosurgery, intubation greater than 24 hours for traumatic brain injury, or hospital admission greater than 2 nights for traumatic brain injury. Among the 1,009 children, 21 (2%; 95% confidence interval [CI] 1% to 3%) had clinically important traumatic brain injuries. Only physician practice and PECARN identified all clinically important traumatic brain injuries, with ranked sensitivities as follows: physician practice and PECARN each 100% (95% CI 84% to 100%), physician estimates 95% (95% CI 76% to 100%), CATCH 91% (95% CI 70% to 99%), and CHALICE 84% (95% CI 60% to 97%). Ranked specificities were as follows: CHALICE 85% (95% CI 82% to 87%), physician estimates 68% (95% CI 65% to 71%), PECARN 62% (95% CI 59% to 66%), physician practice 50% (95% CI 47% to 53%), and CATCH 44% (95% CI 41% to 47%). Of the 5 modalities studied, only physician practice and PECARN identified all clinically important traumatic brain injuries, with PECARN being slightly more specific. CHALICE was incompletely sensitive but the most specific of all rules. CATCH was incompletely sensitive and had the poorest specificity of all modalities. Copyright © 2014 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

Health data and data governance.

PubMed

Hovenga, Evelyn J S; Grain, Heather

2013-01-01

Health is a knowledge industry, based on data collected to support care, service planning, financing and knowledge advancement. Increasingly there is a need to collect, retrieve and use health record information in an electronic format to provide greater flexibility, as this enables retrieval and display of data in multiple locations and formats irrespective of where the data were collected. Electronically maintained records require greater structure and consistency to achieve this. The use of data held in records generated in real time in clinical systems also has the potential to reduce the time it takes to gain knowledge, as there is less need to collect research specific information, this is only possible if data governance principles are applied. Connected devices and information systems are now generating huge amounts of data, as never before seen. An ability to analyse and mine very large amounts of data, "Big Data", provides policy and decision makers with new insights into varied aspects of work and information flow and operational business patterns and trends, and drives greater efficiencies, and safer and more effective health care. This enables decision makers to apply rules and guidance that have been developed based upon knowledge from many individual patient records through recognition of triggers based upon that knowledge. In clinical decision support systems information about the individual is compared to rules based upon knowledge gained from accumulated information of many to provide guidance at appropriate times in the clinical process. To achieve this the data in the individual system, and the knowledge rules must be represented in a compatible and consistent manner. This chapter describes data attributes; explains the difference between data and information; outlines the requirements for quality data; shows the relevance of health data standards; and describes how data governance impacts representation of content in systems and the use of that information.

48 CFR 6103.306 - Decisions [Rule 306].

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 7 2010-10-01 2010-10-01 false Decisions [Rule 306]. 6103.306 Section 6103.306 Federal Acquisition Regulations System CIVILIAN BOARD OF CONTRACT APPEALS, GENERAL SERVICES ADMINISTRATION TRANSPORTATION RATE CASES 6103.306 Decisions [Rule 306]. The judge will issue a written decision based upon the record,...

iRENEX: a clinically informed decision support system for the interpretation of ⁹⁹mTc-MAG3 scans to detect renal obstruction.

PubMed

Garcia, Ernest V; Taylor, Andrew; Folks, Russell; Manatunga, Daya; Halkar, Raghuveer; Savir-Baruch, Bital; Dubovsky, Eva

2012-09-01

Decision support systems for imaging analysis and interpretation are rapidly being developed and will have an increasing impact on the practice of medicine. RENEX is a renal expert system to assist physicians evaluate suspected obstruction in patients undergoing mercaptoacetyltriglycine (MAG3) renography. RENEX uses quantitative parameters extracted from the dynamic renal scan data using QuantEM™II and heuristic rules in the form of a knowledge base gleaned from experts to determine if a kidney is obstructed; however, RENEX does not have access to and could not consider the clinical information available to diagnosticians interpreting these studies. We designed and implemented a methodology to incorporate clinical information into RENEX, implemented motion detection and evaluated this new comprehensive system (iRENEX) in a pilot group of 51 renal patients. To reach a conclusion as to whether a kidney is obstructed, 56 new clinical rules were added to the previously reported 60 rules used to interpret quantitative MAG3 parameters. All the clinical rules were implemented after iRENEX reached a conclusion on obstruction based on the quantitative MAG3 parameters, and the evidence of obstruction was then modified by the new clinical rules. iRENEX consisted of a library to translate parameter values to certainty factors, a knowledge base with 116 heuristic interpretation rules, a forward chaining inference engine to determine obstruction and a justification engine. A clinical database was developed containing patient histories and imaging report data obtained from the hospital information system associated with the pertinent MAG3 studies. The system was fine-tuned and tested using a pilot group of 51 patients (21 men, mean age 58.2 ± 17.1 years, 100 kidneys) deemed by an expert panel to have 61 unobstructed and 39 obstructed kidneys. iRENEX, using only quantitative MAG3 data agreed with the expert panel in 87 % (34/39) of obstructed and 90 % (55/61) of unobstructed kidneys. iRENEX, using both quantitative and clinical data agreed with the expert panel in 95 % (37/39) of obstructed and 92 % (56/61) of unobstructed kidneys. The clinical information significantly (p < 0.001) increased iRENEX certainty in detecting obstruction over using the quantitative data alone. Our renal expert system for detecting renal obstruction has been substantially expanded to incorporate the clinical information available to physicians as well as advanced quality control features and was shown to interpret renal studies in a pilot group at a standardized expert level. These encouraging results warrant a prospective study in a large population of patients with and without renal obstruction to establish the diagnostic performance of iRENEX.

Bayesian design of decision rules for failure detection

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Willsky, A. S.

1984-01-01

The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.

Traumatic intracranial injury in intoxicated patients with minor head trauma.

PubMed

Easter, Joshua S; Haukoos, Jason S; Claud, Jonathan; Wilbur, Lee; Hagstrom, Michelle Tartalgia; Cantrill, Stephen; Mestek, Michael; Symonds, David; Bakes, Katherine

2013-08-01

Studies focusing on minor head injury in intoxicated patients report disparate prevalences of intracranial injury. It is unclear if the typical factors associated with intracranial injury in published clinical decision rules for computerized tomography (CT) acquisition are helpful in differentiating patients with and without intracranial injuries, as intoxication may obscure particular features of intracranial injury such as headache and mimic other signs of head injury such as altered mental status. This study aimed to estimate the prevalence of intracranial injury following minor head injury (Glasgow Coma Scale [GCS] score ≥14) in intoxicated patients and to assess the performance of established clinical decision rules in this population. This was a prospective cohort study of consecutive intoxicated adults presenting to the emergency department (ED) following minor head injury. Historical and physical examination features included those from the Canadian CT Head Rule, National Emergency X-Radiography Utilization Study (NEXUS), and New Orleans Criteria. All patients underwent head CT. A total of 283 patients were enrolled, with a median age of 40 years (interquartile range [IQR] = 28 to 48 years) and median alcohol concentration of 195 mmol/L (IQR = 154 to 256 mmol/L). A total of 238 of 283 (84%) were male, and 225 (80%) had GCS scores of 15. Clinically important injuries (injuries requiring admission to the hospital or neurosurgical follow-up) were identified in 23 patients (8%; 95% confidence interval [CI] = 5% to 12%); one required neurosurgical intervention (0.4%, 95% CI = 0% to 2%). Loss of consciousness and headache were associated with clinically important intracranial injury on CT. The Canadian CT Head Rule had a sensitivity of 70% (95% CI = 47% to 87%) and NEXUS criteria had a sensitivity of 83% (95% CI = 61% to 95%) for clinically important injury in intoxicated patients. In this study, the prevalence of clinically important injury in intoxicated patients with minor head injury was significant. While the presence of the common features associated with intracranial injury in nonintoxicated patients should raise clinical suspicion for intracranial injury in intoxicated patients, the Canadian CT Head Rule and NEXUS criteria do not have adequate sensitivity to be applied in intoxicated patients with minor head injury. © 2013 by the Society for Academic Emergency Medicine.

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Learning Optimal Individualized Treatment Rules from Electronic Health Record Data

PubMed Central

Wang, Yuanjia; Wu, Peng; Liu, Ying; Weng, Chunhua; Zeng, Donglin

2016-01-01

Medical research is experiencing a paradigm shift from “one-size-fits-all” strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data. Our approach merges statistical modeling and medical domain knowledge with machine learning algorithms to assist personalized medical decision making using EHR. We transform the estimation of optimal ITR into a classification problem and account for the non-experimental features of the EHR data and confounding by clinical indication. We create a broad range of feature variables that reflect both patient health status and healthcare data collection process. Using EHR data collected at Columbia University clinical data warehouse, we construct a decision tree for choosing the best second line therapy for treating type 2 diabetes patients. PMID:28503676

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

PubMed Central

2012-01-01

Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

Surrogate decision making and intellectual virtue.

PubMed

Bock, Gregory L

2014-01-01

Patients can be harmed by a religiously motivated surrogate decision maker whose decisions are contrary to the standard of care; therefore, surrogate decision making should be held to a high standard. Stewart Eskew and Christopher Meyers proposed a two-part rule for deciding which religiously based decisions to honor: (1) a secular reason condition and (2) a rationality condition. The second condition is based on a coherence theory of rationality, which they claim is accessible, generous, and culturally sensitive. In this article, I will propose strengthening the rationality condition by grounding it in a theory of intellectual virtue, which is both rigorous and culturally sensitive. Copyright 2014 The Journal of Clinical Ethics. All rights reserved.

Clinical Decision Rules for Paediatric Minor Head Injury: Are CT Scans a Necessary Evil?

PubMed

Thiam, Desmond Wei; Yap, Si Hui; Chong, Shu Ling

2015-09-01

High performing clinical decision rules (CDRs) have been derived to predict which head-injured child requires a computed tomography (CT) of the brain. We set out to evaluate the performance of these rules in the Singapore population. This is a prospective observational cohort study of children aged less than 16 who presented to the emergency department (ED) from April 2014 to June 2014 with a history of head injury. Predictor variables used in the Canadian Assessment of Tomography for Childhood Head Injury (CATCH), Children's Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) and Pediatric Emergency Care Applied Research Network (PECARN) CDRs were collected. Decisions on CT imaging and disposition were made at the physician's discretion. The performance of the CDRs were assessed and compared to current practices. A total of 1179 children were included in this study. Twelve (1%) CT scans were ordered; 6 (0.5%) of them had positive findings. The application of the CDRs would have resulted in a significant increase in the number of children being subjected to CT (as follows): CATCH 237 (20.1%), CHALICE 282 (23.9%), PECARN high- and intermediate-risk 456 (38.7%), PECARN high-risk only 45 (3.8%). The CDRs demonstrated sensitivities of: CATCH 100% (54.1 to 100), CHALICE 83.3% (35.9 to 99.6), PECARN 100% (54.1 to 100), and specificities of: CATCH 80.3% (77.9 to 82.5), CHALICE 76.4% (73.8 to 78.8), PECARN high- and intermediate-risk 61.6% (58.8 to 64.4) and PECARN high-risk only 96.7% (95.5 to 97.6). The CDRs demonstrated high accuracy in detecting children with positive CT findings but direct application in areas with low rates of significant traumatic brain injury (TBI) is likely to increase unnecessary CT scans ordered. Clinical observation in most cases may be a better alternative.

A Clinical Decision Support System for Breast Cancer Patients

NASA Astrophysics Data System (ADS)

Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

77 FR 532 - Qualification of Drivers; Exemption Applications; Diabetes Mellitus

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-05

... its decision to exempt twenty-two individuals from its rule prohibiting persons with insulin-treated... established medical history or clinical diagnosis of diabetes mellitus currently requiring insulin for control... Insulin-Treated Diabetes Mellitus to Operate in Interstate Commerce as Directed by the Transportation Act...

Testing decision rules for categorizing species' extinction risk to help develop quantitative listing criteria for the U.S. Endangered Species Act.

PubMed

Regan, Tracey J; Taylor, Barbara L; Thompson, Grant G; Cochrane, Jean Fitts; Ralls, Katherine; Runge, Michael C; Merrick, Richard

2013-08-01

Lack of guidance for interpreting the definitions of endangered and threatened in the U.S. Endangered Species Act (ESA) has resulted in case-by-case decision making leaving the process vulnerable to being considered arbitrary or capricious. Adopting quantitative decision rules would remedy this but requires the agency to specify the relative urgency concerning extinction events over time, cutoff risk values corresponding to different levels of protection, and the importance given to different types of listing errors. We tested the performance of 3 sets of decision rules that use alternative functions for weighting the relative urgency of future extinction events: a threshold rule set, which uses a decision rule of x% probability of extinction over y years; a concave rule set, where the relative importance of future extinction events declines exponentially over time; and a shoulder rule set that uses a sigmoid shape function, where relative importance declines slowly at first and then more rapidly. We obtained decision cutoffs by interviewing several biologists and then emulated the listing process with simulations that covered a range of extinction risks typical of ESA listing decisions. We evaluated performance of the decision rules under different data quantities and qualities on the basis of the relative importance of misclassification errors. Although there was little difference between the performance of alternative decision rules for correct listings, the distribution of misclassifications differed depending on the function used. Misclassifications for the threshold and concave listing criteria resulted in more overprotection errors, particularly as uncertainty increased, whereas errors for the shoulder listing criteria were more symmetrical. We developed and tested the framework for quantitative decision rules for listing species under the U.S. ESA. If policy values can be agreed on, use of this framework would improve the implementation of the ESA by increasing transparency and consistency. Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.

Oxytocin conditions trait-based rule adherence.

PubMed

Gross, Jörg; De Dreu, Carsten K W

2017-03-01

Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive rule adherence is reduced by oxytocin-a hypothalamic neuropeptide that biases the biobehavioural approach-avoidance system. Participants (N = 139) self-administered oxytocin or placebo intranasally, and reported their need for structure and approach-avoidance sensitivity. Next, participants made binary decisions and were given an arbitrary rule that demanded to forgo financial benefits. Under oxytocin, participants violated the rule more often, especially when they had high need for structure and high approach sensitivity. Possibly, oxytocin dampens the need for a highly structured environment and enables individuals to flexibly trade-off internal desires against external restrictions. Implications for the treatment of clinical disorders marked by maladaptive rule adherence are discussed. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Description and status update on GELLO: a proposed standardized object-oriented expression language for clinical decision support.

PubMed

Sordo, Margarita; Boxwala, Aziz A; Ogunyemi, Omolola; Greenes, Robert A

2004-01-01

A major obstacle to sharing computable clinical knowledge is the lack of a common language for specifying expressions and criteria. Such a language could be used to specify decision criteria, formulae, and constraints on data and action. Al-though the Arden Syntax addresses this problem for clinical rules, its generalization to HL7's object-oriented data model is limited. The GELLO Expression language is an object-oriented language used for expressing logical conditions and computations in the GLIF3 (GuideLine Interchange Format, v. 3) guideline modeling language. It has been further developed under the auspices of the HL7 Clinical Decision Support Technical Committee, as a proposed HL7 standard., GELLO is based on the Object Constraint Language (OCL), because it is vendor-independent, object-oriented, and side-effect-free. GELLO expects an object-oriented data model. Although choice of model is arbitrary, standardization is facilitated by ensuring that the data model is compatible with the HL7 Reference Information Model (RIM).

SFINX-a drug-drug interaction database designed for clinical decision support systems.

PubMed

Böttiger, Ylva; Laine, Kari; Andersson, Marine L; Korhonen, Tuomas; Molin, Björn; Ovesjö, Marie-Louise; Tirkkonen, Tuire; Rane, Anders; Gustafsson, Lars L; Eiermann, Birgit

2009-06-01

The aim was to develop a drug-drug interaction database (SFINX) to be integrated into decision support systems or to be used in website solutions for clinical evaluation of interactions. Key elements such as substance properties and names, drug formulations, text structures and references were defined before development of the database. Standard operating procedures for literature searches, text writing rules and a classification system for clinical relevance and documentation level were determined. ATC codes, CAS numbers and country-specific codes for substances were identified and quality assured to ensure safe integration of SFINX into other data systems. Much effort was put into giving short and practical advice regarding clinically relevant drug-drug interactions. SFINX includes over 8,000 interaction pairs and is integrated into Swedish and Finnish computerised decision support systems. Over 31,000 physicians and pharmacists are receiving interaction alerts through SFINX. User feedback is collected for continuous improvement of the content. SFINX is a potentially valuable tool delivering instant information on drug interactions during prescribing and dispensing.

A sharable cloud-based pancreaticoduodenectomy collaborative database for physicians: emphasis on security and clinical rule supporting.

PubMed

Yu, Hwan-Jeu; Lai, Hong-Shiee; Chen, Kuo-Hsin; Chou, Hsien-Cheng; Wu, Jin-Ming; Dorjgochoo, Sarangerel; Mendjargal, Adilsaikhan; Altangerel, Erdenebaatar; Tien, Yu-Wen; Hsueh, Chih-Wen; Lai, Feipei

2013-08-01

Pancreaticoduodenectomy (PD) is a major operation with high complication rate. Thereafter, patients may develop morbidity because of the complex reconstruction and loss of pancreatic parenchyma. A well-designed database is very important to address both the short-term and long-term outcomes after PD. The objective of this research was to build an international PD database implemented with security and clinical rule supporting functions, which made the data-sharing easier and improve the accuracy of data. The proposed system is a cloud-based application. To fulfill its requirements, the system comprises four subsystems: a data management subsystem, a clinical rule supporting subsystem, a short message notification subsystem, and an information security subsystem. After completing the surgery, the physicians input the data retrospectively, which are analyzed to study factors associated with post-PD common complications (delayed gastric emptying and pancreatic fistula) to validate the clinical value of this system. Currently, this database contains data from nearly 500 subjects. Five medical centers in Taiwan and two cancer centers in Mongolia are participating in this study. A data mining model of the decision tree analysis showed that elderly patients (>76 years) with pylorus-preserving PD (PPPD) have higher proportion of delayed gastric emptying. About the pancreatic fistula, the data mining model of the decision tree analysis revealed that cases with non-pancreaticogastrostomy (PG) reconstruction - body mass index (BMI)>29.65 or PG reconstruction - BMI>23.7 - non-classic PD have higher proportion of pancreatic fistula after PD. The proposed system allows medical staff to collect and store clinical data in a cloud, sharing the data with other physicians in a secure manner to achieve collaboration in research. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Emergency physicians' knowledge and attitudes of clinical decision support in the electronic health record: a survey-based study.

PubMed

Ballard, Dustin W; Rauchwerger, Adina S; Reed, Mary E; Vinson, David R; Mark, Dustin G; Offerman, Steven R; Chettipally, Uli K; Graetz, Ilana; Dayan, Peter; Kuppermann, Nathan

2013-04-01

The objective was to investigate clinician knowledge of and attitudes toward clinical decision support (CDS) and its incorporation into the electronic health record (EHR). This was an electronic survey of emergency physicians (EPs) within an integrated health care delivery system that uses a complete EHR. Randomly assigned respondents completed one of two questionnaires, both including a hypothetical vignette and self-reported knowledge of and attitudes about CDS. One vignette version included CDS, and the other did not (NCDS). The vignette described a scenario in which a cranial computed tomography (CCT) is not recommended by validated prediction rules (the Pediatric Emergency Care Applied Research Network [PECARN] rules). In both survey versions, subjects responded first with their likely approach to evaluation and then again after receiving either CDS (the PECARN prediction rules) or no additional support. Descriptive statistics were used for self-reported responses and multivariate logistic regression was used to identify predictors of self-reported knowledge and use of the PECARN rules, as well as use of vignette responses. There were 339 respondents (68% response rate), with 172 of 339 (51%) randomized to the CDS version. Initially, 25% of respondents to each version indicated they would order CCTs. After CDS, 30 of 43 (70%) of respondents who initially would order CCTs changed their management decisions to no CCT versus two of 41 (5%) with the NCDS version (chi-square, p = 0.003). In response to self-report questions, 81 of 338 respondents (24%) reported having never heard of the PECARN prediction rules, 122 of 338 (36%) were aware of the rules but not their specifics, and 135 of 338 (40%) reported knowing the rules and their specifics. Respondents agreed with favorable statements about CDS (75% to 96% agreement across seven statements) and approaches to its implementation into the EHR (60% to 93% agreement across seven statements). In multivariable analyses, EPs with tenure of 5 to 14 years (odds ratio [AOR] = 0.51, 95% confidence interval [CI] = 0.30 to 0.86) and for 15 years or more (AOR = 0.37, 95% CI = 0.20 to 0.70) were significantly less likely to report knowing the specifics of the PECARN prediction rules compared with EPs who practiced for fewer than 5 years. In addition, in the initial vignette responses (across both versions), physicians with ≥15 years of ED tenure compared to those with fewer than 5 years of experience (AOR = 0.30, 95% CI = 0.13 to 0.69), and those reporting knowing the specifics of the PECARN prediction rules were less likely to order CCTs (AOR = 0.53, 95% CI = 0.30 to 0.92). EPs incorporated pediatric head trauma CDS via the EHR into their clinical judgment in a hypothetical scenario and reported favorable opinions of CDS in general and their inclusion into the EHR. © 2013 by the Society for Academic Emergency Medicine.

The optimum decision rules for the oddity task.

PubMed

Versfeld, N J; Dai, H; Green, D M

1996-01-01

This paper presents the optimum decision rule for an m-interval oddity task in which m-1 intervals contain the same signal and one is different or odd. The optimum decision rule depends on the degree of correlation among observations. The present approach unifies the different strategies that occur with "roved" or "fixed" experiments (Macmillan & Creelman, 1991, p. 147). It is shown that the commonly used decision rule for an m-interval oddity task corresponds to the special case of highly correlated observations. However, as is also true for the same-different paradigm, there exists a different optimum decision rule when the observations are independent. The relation between the probability of a correct response and d' is derived for the three-interval oddity task. Tables are presented of this relation for the three-, four-, and five-interval oddity task. Finally, an experimental method is proposed that allows one to determine the decision rule used by the observer in an oddity experiment.

Feasibility of Extracting Key Elements from ClinicalTrials.gov to Support Clinicians’ Patient Care Decisions

PubMed Central

Kim, Heejun; Bian, Jiantao; Mostafa, Javed; Jonnalagadda, Siddhartha; Del Fiol, Guilherme

2016-01-01

Motivation: Clinicians need up-to-date evidence from high quality clinical trials to support clinical decisions. However, applying evidence from the primary literature requires significant effort. Objective: To examine the feasibility of automatically extracting key clinical trial information from ClinicalTrials.gov. Methods: We assessed the coverage of ClinicalTrials.gov for high quality clinical studies that are indexed in PubMed. Using 140 random ClinicalTrials.gov records, we developed and tested rules for the automatic extraction of key information. Results: The rate of high quality clinical trial registration in ClinicalTrials.gov increased from 0.2% in 2005 to 17% in 2015. Trials reporting results increased from 3% in 2005 to 19% in 2015. The accuracy of the automatic extraction algorithm for 10 trial attributes was 90% on average. Future research is needed to improve the algorithm accuracy and to design information displays to optimally present trial information to clinicians. PMID:28269867

Decision-making competence in younger and older adults: which cognitive abilities contribute to the application of decision rules?

PubMed

Rosi, Alessia; Bruine de Bruin, Wändi; Del Missier, Fabio; Cavallini, Elena; Russo, Riccardo

2017-12-28

Older adults perform worse than younger adults when applying decision rules to choose between options that vary along multiple attributes. Although previous studies have shown that general fluid cognitive abilities contribute to the accurate application of decision rules, relatively little is known about which specific cognitive abilities play the most important role. We examined the independent roles of working memory, verbal fluency, semantic knowledge, and components of executive functioning. We found that age-related decline in applying decision rules was statistically mediated by age-related decline in working memory and verbal fluency. Our results have implications for theories of aging and decision-making.

External validation of heart-type fatty acid binding protein, high-sensitivity cardiac troponin, and electrocardiography as rule-out for acute myocardial infarction.

PubMed

Van Hise, Christopher B; Greenslade, Jaimi H; Parsonage, William; Than, Martin; Young, Joanna; Cullen, Louise

2018-02-01

To externally validate a clinical decision rule incorporating heart fatty acid binding protein (h-FABP), high-sensitivity troponin (hs-cTn) and electrocardiogram (ECG) for the detection of acute myocardial infarction (AMI) on presentation to the Emergency Department. We also investigated whether this clinical decision rule improved identification of AMI over algorithms incorporating hs-cTn and ECG only. This study included data from 789 patients from the Brisbane ADAPT cohort and 441 patients from the Christchurch TIMI RCT cohort. The primary outcome was index AMI. Sensitivity, specificity, positive predictive value and negative predictive value were used to assess the diagnostic accuracy of the algorithms. 1230 patients were recruited, including 112 (9.1%) with AMI. The algorithm including h-FABP and hs-cTnT had 100% sensitivity and 32.4% specificity. The algorithm utilising h-FABP and hs-cTnI had similar sensitivity (99.1%) and higher specificity (43.4%). The hs-cTnI and hs-cTnT algorithms without h-FABP both had a sensitivity of 98.2%; a result that was not significantly different from either algorithm incorporating h-FABP. Specificity was higher for the hs-cTnI algorithm (68.1%) compared to the hs-cTnT algorithm (33.0%). The specificity of the algorithm incorporating hs-cTnI alone was also significantly higher than both of the algorithms incorporating h-FABP (p<0.01). For patients presenting to the Emergency Department with chest pain, an algorithm incorporating h-FABP, hs-cTn and ECG has high accuracy and can rule out up to 40% of patients. An algorithm incorporating only hs-cTn and ECG has similar sensitivity and may rule out a higher proportion of patients. Each of the algorithms can be used to safely identify patients as low risk for AMI on presentation to the Emergency Department. Copyright © 2017 The Canadian Society of Clinical Chemists. All rights reserved.

75 FR 8182 - Qualification of Drivers; Exemption Applications; Diabetes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-23

... decision to exempt twenty-four individuals from its rule prohibiting persons with insulin-treated diabetes... history or clinical diagnosis of diabetes mellitus currently requiring insulin for control'' (49 CFR 391... entitled ``A Report to Congress on the Feasibility of a Program to Qualify Individuals with Insulin-Treated...

77 FR 10607 - Qualification of Drivers; Exemption Applications; Diabetes Mellitus

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-22

... its decision to exempt sixteen individuals from its rule prohibiting persons with insulin-treated... applicants, Mr. Randall T. Buffkin (NC) no longer requires the use of insulin and therefore does not need a... established medical history or clinical diagnosis of diabetes mellitus currently requiring insulin for control...

78 FR 76400 - Qualification of Drivers; Exemption Applications; Diabetes Mellitus

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-17

...: FMCSA announces its decision to exempt 15 individuals from its rule prohibiting persons with insulin... clinical diagnosis of diabetes mellitus currently requiring insulin for control'' (49 CFR 391.41(b)(3... Report to Congress on the Feasibility of a Program to Qualify Individuals with Insulin-Treated Diabetes...

Using Data Augmentation to Facilitate Conduct of Phase I–II Clinical Trials with Delayed Outcomes

PubMed Central

Jin, Ick Hoon; Liu, Suyu; Thall, Peter F.; Yuan, Ying

2014-01-01

A practical impediment in adaptive clinical trials is that outcomes must be observed soon enough to apply decision rules to choose treatments for new patients. For example, if outcomes take up to six weeks to evaluate and the accrual rate is one patient per week, on average three new patients will be accrued while waiting to evaluate the outcomes of the previous three patients. The question is how to treat the new patients. This logistical problem persists throughout the trial. Various ad hoc practical solutions are used, none entirely satisfactory. We focus on this problem in phase I–II clinical trials that use binary toxicity and efficacy, defined in terms of event times, to choose doses adaptively for successive cohorts. We propose a general approach to this problem that treats late-onset outcomes as missing data, uses data augmentation to impute missing outcomes from posterior predictive distributions computed from partial follow-up times and complete outcome data, and applies the design’s decision rules using the completed data. We illustrate the method with two cancer trials conducted using a phase I–II design based on efficacy-toxicity trade-offs, including a computer stimulation study. PMID:25382884

Requiem for the max rule?

PubMed Central

Ma, Wei Ji; Shen, Shan; Dziugaite, Gintare; van den Berg, Ronald

2015-01-01

In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process haven fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making. PMID:25584425

A Decision Making Methodology in Support of the Business Rules Lifecycle

NASA Technical Reports Server (NTRS)

Wild, Christopher; Rosca, Daniela

1998-01-01

The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.

Prescriptive models to support decision making in genetics.

PubMed

Pauker, S G; Pauker, S P

1987-01-01

Formal prescriptive models can help patients and clinicians better understand the risks and uncertainties they face and better formulate well-reasoned decisions. Using Bayes rule, the clinician can interpret pedigrees, historical data, physical findings and laboratory data, providing individualized probabilities of various diagnoses and outcomes of pregnancy. With the advent of screening programs for genetic disease, it becomes increasingly important to consider the prior probabilities of disease when interpreting an abnormal screening test result. Decision trees provide a convenient formalism for structuring diagnostic, therapeutic and reproductive decisions; such trees can also enhance communication between clinicians and patients. Utility theory provides a mechanism for patients to understand the choices they face and to communicate their attitudes about potential reproductive outcomes in a manner which encourages the integration of those attitudes into appropriate decisions. Using a decision tree, the relevant probabilities and the patients' utilities, physicians can estimate the relative worth of various medical and reproductive options by calculating the expected utility of each. By performing relevant sensitivity analyses, clinicians and patients can understand the impact of various soft data, including the patients' attitudes toward various health outcomes, on the decision making process. Formal clinical decision analytic models can provide deeper understanding and improved decision making in clinical genetics.

New clinical decision rule to exclude subarachnoid haemorrhage for acute headache: a prospective multicentre observational study.

PubMed

Kimura, Akio; Kobayashi, Kentaro; Yamaguchi, Hitoshi; Takahashi, Takeshi; Harada, Masahiro; Honda, Hideki; Mori, Yoshio; Hirose, Keika; Tanaka, Noriko

2016-09-09

To ensure good outcomes in the management of subarachnoid haemorrhage (SAH), accurate prediction is crucial for initial assessment of patients presenting with acute headache. We conducted this study to develop a new clinical decision rule using only objectively measurable predictors to exclude SAH, offering higher specificity than the previous Ottawa SAH Rule while maintaining comparable sensitivity. Multicentre prospective cohort study. Tertiary-care emergency departments of five general hospitals in Japan from April 2011 to March 2014. Eligible patients comprised 1781 patients aged >15 years with acute headache, excluding trauma or toxic causes and patients who presented in an unconscious state. Definitive diagnosis of SAH was based on confirmation of SAH on head CT or lumbar puncture findings of non-traumatic red blood cells or xanthochromia. A total of 1561 patients were enrolled in this study, of whom 277 showed SAH. Using these enrolled patients, we reached a rule with mainly categorical predictors used in previous reports, called the 'Ottawa-like rule', offering 100% sensitivity when using any of age ≥40 years, neck pain or stiffness, altered level of consciousness or onset during exertion. Using the 1317 patients from whom blood samples were obtained, a new rule using any of systolic blood pressure >150 mm Hg, diastolic blood pressure >90 mm Hg, blood sugar >115 mg/dL or serum potassium <3.9 mEq/L offered 100% sensitivity (95% CI 98.6% to 100%) and 14.5% specificity (12.5% to 16.9%), while the Ottawa-like rule showed the same sensitivity with a lower specificity of 8.8% (7.2% to 10.7%). While maintaining equal sensitivity, our new rule seemed to offer higher specificity than the previous rules proposed by the Ottawa group. Despite the need for blood sampling, this method can reduce unnecessary head CT in patients with acute headache. UMIN 00004871. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Decision tables and rule engines in organ allocation systems for optimal transparency and flexibility.

PubMed

Schaafsma, Murk; van der Deijl, Wilfred; Smits, Jacqueline M; Rahmel, Axel O; de Vries Robbé, Pieter F; Hoitsma, Andries J

2011-05-01

Organ allocation systems have become complex and difficult to comprehend. We introduced decision tables to specify the rules of allocation systems for different organs. A rule engine with decision tables as input was tested for the Kidney Allocation System (ETKAS). We compared this rule engine with the currently used ETKAS by running 11,000 historical match runs and by running the rule engine in parallel with the ETKAS on our allocation system. Decision tables were easy to implement and successful in verifying correctness, completeness, and consistency. The outcomes of the 11,000 historical matches in the rule engine and the ETKAS were exactly the same. Running the rule engine simultaneously in parallel and in real time with the ETKAS also produced no differences. Specifying organ allocation rules in decision tables is already a great step forward in enhancing the clarity of the systems. Yet, using these tables as rule engine input for matches optimizes the flexibility, simplicity and clarity of the whole process, from specification to the performed matches, and in addition this new method allows well controlled simulations. © 2011 The Authors. Transplant International © 2011 European Society for Organ Transplantation.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Retrospective checking of compliance with practice guidelines for acute stroke care: a novel experiment using openEHR’s Guideline Definition Language

PubMed Central

2014-01-01

Background Providing scalable clinical decision support (CDS) across institutions that use different electronic health record (EHR) systems has been a challenge for medical informatics researchers. The lack of commonly shared EHR models and terminology bindings has been recognised as a major barrier to sharing CDS content among different organisations. The openEHR Guideline Definition Language (GDL) expresses CDS content based on openEHR archetypes and can support any clinical terminologies or natural languages. Our aim was to explore in an experimental setting the practicability of GDL and its underlying archetype formalism. A further aim was to report on the artefacts produced by this new technological approach in this particular experiment. We modelled and automatically executed compliance checking rules from clinical practice guidelines for acute stroke care. Methods We extracted rules from the European clinical practice guidelines as well as from treatment contraindications for acute stroke care and represented them using GDL. Then we executed the rules retrospectively on 49 mock patient cases to check the cases’ compliance with the guidelines, and manually validated the execution results. We used openEHR archetypes, GDL rules, the openEHR reference information model, reference terminologies and the Data Archetype Definition Language. We utilised the open-sourced GDL Editor for authoring GDL rules, the international archetype repository for reusing archetypes, the open-sourced Ocean Archetype Editor for authoring or modifying archetypes and the CDS Workbench for executing GDL rules on patient data. Results We successfully represented clinical rules about 14 out of 19 contraindications for thrombolysis and other aspects of acute stroke care with 80 GDL rules. These rules are based on 14 reused international archetypes (one of which was modified), 2 newly created archetypes and 51 terminology bindings (to three terminologies). Our manual compliance checks for 49 mock patients were a complete match versus the automated compliance results. Conclusions Shareable guideline knowledge for use in automated retrospective checking of guideline compliance may be achievable using GDL. Whether the same GDL rules can be used for at-the-point-of-care CDS remains unknown. PMID:24886468

38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2010-07-01 2010-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...

38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2011-07-01 2011-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...

38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2013-07-01 2013-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...

38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2014-07-01 2014-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...

38 CFR 20.1303 - Rule 1303. Nonprecedential nature of Board decisions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2012-07-01 2012-07-01 false Rule 1303. Nonprecedential nature of Board decisions. 20.1303 Section 20.1303 Pensions, Bonuses, and Veterans' Relief....1303 Rule 1303. Nonprecedential nature of Board decisions. Although the Board strives for consistency...

19 CFR 177.10 - Publication of decisions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 2 2014-04-01 2014-04-01 false Publication of decisions. 177.10 Section 177.10... TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.10 Publication of decisions. (a....8(a)(3). (b) [Reserved] (c) Changes of practice. Before the publication of a ruling which has the...

The Importance of Conditional Probability in Diagnostic Reasoning and Clinical Decision Making: A Primer for the Eye Care Practitioner.

PubMed

Sanfilippo, Paul G; Hewitt, Alex W; Mackey, David A

2017-04-01

To outline and detail the importance of conditional probability in clinical decision making and discuss the various diagnostic measures eye care practitioners should be aware of in order to improve the scope of their clinical practice. We conducted a review of the importance of conditional probability in diagnostic testing for the eye care practitioner. Eye care practitioners use diagnostic tests on a daily basis to assist in clinical decision making and optimizing patient care and management. These tests provide probabilistic information that can enable the clinician to increase (or decrease) their level of certainty about the presence of a particular condition. While an understanding of the characteristics of diagnostic tests are essential to facilitate proper interpretation of test results and disease risk, many practitioners either confuse or misinterpret these measures. In the interests of their patients, practitioners should be aware of the basic concepts associated with diagnostic testing and the simple mathematical rule that underpins them. Importantly, the practitioner needs to recognize that the prevalence of a disease in the population greatly determines the clinical value of a diagnostic test.

On the necessity of new decision-making methods for cancer-associated, symptomatic, pulmonary embolism.

PubMed

Carmona-Bayonas, A; Font, C; Jiménez-Fonseca, P; Fenoy, Francisco; Otero, R; Beato, C; Plasencia, J; Biosca, M; Sánchez, M; Benegas, M; Calvo-Temprano, D; Varona, D; Faez, L; Vicente, M A; de la Haba, I; Antonio, M; Madridano, O; Ramchandani, A; Castañón, E; Marchena, P J; Martínez, M J; Martín, M; Marín, G; Ayala de la Peña, F; Vicente, V

2016-07-01

Acute symptomatic pulmonary embolism (PE) varies in its clinical manifestations in patients with cancer and entails specific issues. The objective is to assess the performance of five scores (PESI, sPESI, GPS, POMPE, and RIETE) and a clinical decision rule to predict 30-day mortality. This is an ambispective, observational, multicenter study that collected episodes of PE in patients with cancer from 13 Spanish centers. The main criterion for comparing scales was the c-indices and 95% confidence intervals (CIs) of the models for predicting 30-day mortality. 585 patients with acute symptomatic PE were recruited. The 30-day mortality rate was 21.3 (95% CI; 18.2-24.8%). The specific scales (POMPE-C and RIETE) were equally effective in discriminating prognosis (c-index of 0.775 and 0.757, respectively). None of these best performing scales was superior to the ECOG-PS with a c-index of 0.724. The remaining scores (PESI, sPESI, and GPS) performed worse, with c-indexes of 0.719, 0.705, and 0.722, respectively. The dichotomic "clinical decision rule" for ambulatory therapy was at least equally reliable in defining a low risk group: in the absence of all exclusion criteria, 30-day mortality was 2%, compared to 5% and 4% in the POMPE-C and RIETE low-risk categories, respectively. The accuracy of the five scales examined was not high enough to rely on to predict 30-day mortality and none of them contribute significantly to qualitative clinical judgment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Knowledge as a Service at the Point of Care.

PubMed

Shellum, Jane L; Freimuth, Robert R; Peters, Steve G; Nishimura, Rick A; Chaudhry, Rajeev; Demuth, Steve J; Knopp, Amy L; Miksch, Timothy A; Milliner, Dawn S

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources.

Knowledge as a Service at the Point of Care

PubMed Central

Shellum, Jane L.; Freimuth, Robert R.; Peters, Steve G.; Nishimura, Rick A.; Chaudhry, Rajeev; Demuth, Steve J.; Knopp, Amy L.; Miksch, Timothy A.; Milliner, Dawn S.

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources. PMID:28269911

Conformance Testing: Measurement Decision Rules

NASA Technical Reports Server (NTRS)

Mimbs, Scott M.

2010-01-01

The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement decisions rules.

Automated rule-base creation via CLIPS-Induce

NASA Technical Reports Server (NTRS)

Murphy, Patrick M.

1994-01-01

Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

Requiem for the max rule?

PubMed

Ma, Wei Ji; Shen, Shan; Dziugaite, Gintare; van den Berg, Ronald

2015-11-01

In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process have fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been the most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive decision rules for the acquisition of nature reserves.

PubMed

Turner, Will R; Wilcove, David S

2006-04-01

Although reserve-design algorithms have shown promise for increasing the efficiency of conservation planning, recent work casts doubt on the usefulness of some of these approaches in practice. Using three data sets that vary widely in size and complexity, we compared various decision rules for acquiring reserve networks over multiyear periods. We explored three factors that are often important in real-world conservation efforts: uncertain availability of sites for acquisition, degradation of sites, and overall budget constraints. We evaluated the relative strengths and weaknesses of existing optimal and heuristic decision rules and developed a new set of adaptive decision rules that combine the strengths of existing optimal and heuristic approaches. All three of the new adaptive rules performed better than the existing rules we tested under virtually all scenarios of site availability, site degradation, and budget constraints. Moreover, the adaptive rules required no additional data beyond what was readily available and were relatively easy to compute.

Intraoperative Clinical Decision Support for Anesthesia: A Narrative Review of Available Systems.

PubMed

Nair, Bala G; Gabel, Eilon; Hofer, Ira; Schwid, Howard A; Cannesson, Maxime

2017-02-01

With increasing adoption of anesthesia information management systems (AIMS), there is growing interest in utilizing AIMS data for intraoperative clinical decision support (CDS). CDS for anesthesia has the potential for improving quality of care, patient safety, billing, and compliance. Intraoperative CDS can range from passive and post hoc systems to active real-time systems that can detect ongoing clinical issues and deviations from best practice care. Real-time CDS holds the most promise because real-time alerts and guidance can drive provider behavior toward evidence-based standardized care during the ongoing case. In this review, we describe the different types of intraoperative CDS systems with specific emphasis on real-time systems. The technical considerations in developing and implementing real-time CDS are systematically covered. This includes the functional modules of a CDS system, development and execution of decision rules, and modalities to alert anesthesia providers concerning clinical issues. We also describe the regulatory aspects that affect development, implementation, and use of intraoperative CDS. Methods and measures to assess the effectiveness of intraoperative CDS are discussed. Last, we outline areas of future development of intraoperative CDS, particularly the possibility of providing predictive and prescriptive decision support.

Integrative review of clinical decision support for registered nurses in acute care settings.

PubMed

Dunn Lopez, Karen; Gephart, Sheila M; Raszewski, Rebecca; Sousa, Vanessa; Shehorn, Lauren E; Abraham, Joanna

2017-03-01

To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses. We performed an integrative review of qualitative and quantitative peer-reviewed original research studies using a structured search of PubMed, Embase, Cumulative Index to Nursing and Applied Health Literature (CINAHL), Scopus, Web of Science, and IEEE Xplore (Institute of Electrical and Electronics Engineers Xplore Digital Library). We included articles that reported on CDS targeting bedside nurses and excluded in stages based on rules for titles, abstracts, and full articles. We extracted research design and methods, CDS purpose, electronic health record integration, usability, and process and patient outcomes. Our search yielded 3157 articles. After removing duplicates and applying exclusion rules, 28 articles met the inclusion criteria. The majority of studies were single-site, descriptive or qualitative (43%) or quasi-experimental (36%). There was only 1 randomized controlled trial. The purpose of most CDS was to support diagnostic decision-making (36%), guideline adherence (32%), medication management (29%), and situational awareness (25%). All the studies that included process outcomes (7) and usability outcomes (4) and also had analytic procedures to detect changes in outcomes demonstrated statistically significant improvements. Three of 4 studies that included patient outcomes and also had analytic procedures to detect change showed statistically significant improvements. No negative effects of CDS were found on process, usability, or patient outcomes. Clinical support systems targeting bedside nurses have positive effects on outcomes and hold promise for improving care quality; however, this research is lagging behind studies of CDS targeting medical decision-making in both volume and level of evidence. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Interpretable Decision Sets: A Joint Framework for Description and Prediction

PubMed Central

Lakkaraju, Himabindu; Bach, Stephen H.; Jure, Leskovec

2016-01-01

One of the most important obstacles to deploying predictive models is the fact that humans do not understand and trust them. Knowing which variables are important in a model’s prediction and how they are combined can be very powerful in helping people understand and trust automatic decision making systems. Here we propose interpretable decision sets, a framework for building predictive models that are highly accurate, yet also highly interpretable. Decision sets are sets of independent if-then rules. Because each rule can be applied independently, decision sets are simple, concise, and easily interpretable. We formalize decision set learning through an objective function that simultaneously optimizes accuracy and interpretability of the rules. In particular, our approach learns short, accurate, and non-overlapping rules that cover the whole feature space and pay attention to small but important classes. Moreover, we prove that our objective is a non-monotone submodular function, which we efficiently optimize to find a near-optimal set of rules. Experiments show that interpretable decision sets are as accurate at classification as state-of-the-art machine learning techniques. They are also three times smaller on average than rule-based models learned by other methods. Finally, results of a user study show that people are able to answer multiple-choice questions about the decision boundaries of interpretable decision sets and write descriptions of classes based on them faster and more accurately than with other rule-based models that were designed for interpretability. Overall, our framework provides a new approach to interpretable machine learning that balances accuracy, interpretability, and computational efficiency. PMID:27853627

A principled approach to setting optimal diagnostic thresholds: where ROC and indifference curves meet.

PubMed

Irwin, R John; Irwin, Timothy C

2011-06-01

Making clinical decisions on the basis of diagnostic tests is an essential feature of medical practice and the choice of the decision threshold is therefore crucial. A test's optimal diagnostic threshold is the threshold that maximizes expected utility. It is given by the product of the prior odds of a disease and a measure of the importance of the diagnostic test's sensitivity relative to its specificity. Choosing this threshold is the same as choosing the point on the Receiver Operating Characteristic (ROC) curve whose slope equals this product. We contend that a test's likelihood ratio is the canonical decision variable and contrast diagnostic thresholds based on likelihood ratio with two popular rules of thumb for choosing a threshold. The two rules are appealing because they have clear graphical interpretations, but they yield optimal thresholds only in special cases. The optimal rule can be given similar appeal by presenting indifference curves, each of which shows a set of equally good combinations of sensitivity and specificity. The indifference curve is tangent to the ROC curve at the optimal threshold. Whereas ROC curves show what is feasible, indifference curves show what is desirable. Together they show what should be chosen. Copyright © 2010 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Why cost-effectiveness should trump (clinical) effectiveness: the ethical economics of the South West quadrant.

PubMed

Dowie, Jack

2004-05-01

In many health decision making situations there is a requirement that the effectiveness of interventions, usually their 'clinical' effectiveness, be established, as well as their cost-effectiveness. Often indeed this is effectively a prior requirement for their cost-effectiveness being investigated. If, however, one accepts the ethical argument for using a threshold incremental cost-effectiveness ratio (ICER) for interventions that are more effective but more costly (i.e. fall in the NE quadrant of the cost-effectiveness plane), one should apply the same decision rule in the SW quadrant, where the intervention is less effective but less costly. This implication is present in most standard treatments of cost-effectiveness analysis, including recent stochastic versions, and had gone relatively unquestioned within the discipline until the recent suggestion that the ICER threshold might be 'kinked'. A kinked threshold would, O'Brien et al. argue, better reflect the asymmetrical individual preferences found in empirical studies of consumer's willingness to pay and willingness to accept and justify different decision rules in the NE and SW quadrants. We reject the validity of such asymmetric preferences in the context of public health care decisions and consider and counter the two main 'ethical' objections that probably underlie the asymmetry in this case--the objection to 'taking away' and the objection to being required to undergo treatment that is less effective than no treatment at all. Copyright 2004 John Wiley & Sons, Ltd.

Decision Rules Used in Academic Program Closure: Where the Rubber Meets the Road.

ERIC Educational Resources Information Center

Eckel, Peter D.

This study examines, from an organizational perspective, decision rules guiding program discontinuance, testing the framework of decision rule rationality versus action rationality. A multi-site case study method was used; interviews were conducted with 11-16 individuals at each of four research I or II universities that had discontinued at least…

Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.

PubMed

Fific, Mario; Little, Daniel R; Nosofsky, Robert M

2010-04-01

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set of component dimensions. Those independent decisions are then combined via logical rules to determine the overall categorization response. The time course of the independent decisions is modeled via random-walk processes operating along individual dimensions. Alternative mental architectures are used as mechanisms for combining the independent decisions to implement the logical rules. We derive fundamental qualitative contrasts for distinguishing among the predictions of the rule models and major alternative models of classification RT. We also use the models to predict detailed RT-distribution data associated with individual stimuli in tasks of speeded perceptual classification. PsycINFO Database Record (c) 2010 APA, all rights reserved.

14 CFR 16.227 - Standard of proof.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or rule in a party's favor only if the decision or ruling...

Methodological challenges of validating a clinical decision-making tool in the practice environment.

PubMed

Brennan, Caitlin W; Daly, Barbara J

2015-04-01

Validating a measurement tool intended for use in the practice environment poses challenges that may not be present when validating a tool intended solely for research purposes. The aim of this article is to describe the methodological challenges of validating a clinical decision-making tool, the Oncology Acuity Tool, which nurses use to make nurse assignment and staffing decisions prospectively each shift. Data were derived from a larger validation study, during which several methodological challenges arose. Revisions to the tool, including conducting iterative feedback cycles with end users, were necessary before the validation study was initiated. The "true" value of patient acuity is unknown, and thus, two approaches to inter-rater reliability assessment were used. Discordant perspectives existed between experts and end users. Balancing psychometric rigor with clinical relevance may be achieved through establishing research-practice partnerships, seeking active and continuous feedback with end users, and weighing traditional statistical rules of thumb with practical considerations. © The Author(s) 2014.

Information systems: the key to evidence-based health practice.

PubMed Central

Rodrigues, R. J.

2000-01-01

Increasing prominence is being given to the use of best current evidence in clinical practice and health services and programme management decision-making. The role of information in evidence-based practice (EBP) is discussed, together with questions of how advanced information systems and technology (IS&T) can contribute to the establishment of a broader perspective for EBP. The author examines the development, validation and use of a variety of sources of evidence and knowledge that go beyond the well-established paradigm of research, clinical trials, and systematic literature review. Opportunities and challenges in the implementation and use of IS&T and knowledge management tools are examined for six application areas: reference databases, contextual data, clinical data repositories, administrative data repositories, decision support software, and Internet-based interactive health information and communication. Computerized and telecommunications applications that support EBP follow a hierarchy in which systems, tasks and complexity range from reference retrieval and the processing of relatively routine transactions, to complex "data mining" and rule-driven decision support systems. PMID:11143195

Presenting Germany's drug pricing rule as a cost-per-QALY rule.

PubMed

Gandjour, Afschin

2012-06-01

In Germany, the Institute for Quality and Efficiency in Health Care (IQWiG) makes recommendations for ceiling prices of drugs based on an evaluation of the relationship between costs and effectiveness. To set ceiling prices, IQWiG uses the following decision rule: the incremental cost-effectiveness ratio of a new drug compared with the next effective intervention should not be higher than that of the next effective intervention compared to its comparator. The purpose of this paper is to show that IQWiG's decision rule can be presented as a cost-per-QALY rule by using equity-weighted QALYs. This transformation shows where both rules share commonalities. Furthermore, it makes the underlying ethical implications of IQWiG's decision rule transparent and open to debate.

Portfolio theory and the alternative decision rule of cost-effectiveness analysis: theoretical and practical considerations.

PubMed

Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen

2004-05-01

Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.

Clinical decision making: how surgeons do it.

PubMed

Crebbin, Wendy; Beasley, Spencer W; Watters, David A K

2013-06-01

Clinical decision making is a core competency of surgical practice. It involves two distinct types of mental process best considered as the ends of a continuum, ranging from intuitive and subconscious to analytical and conscious. In practice, individual decisions are usually reached by a combination of each, according to the complexity of the situation and the experience/expertise of the surgeon. An expert moves effortlessly along this continuum, according to need, able to apply learned rules or algorithms to specific presentations, choosing these as a result of either pattern recognition or analytical thinking. The expert recognizes and responds quickly to any mismatch between what is observed and what was expected, coping with gaps in information and making decisions even where critical data may be uncertain or unknown. Even for experts, the cognitive processes involved are difficult to articulate as they tend to be very complex. However, if surgeons are to assist trainees in developing their decision-making skills, the processes need to be identified and defined, and the competency needs to be measurable. This paper examines the processes of clinical decision making in three contexts: making a decision about how to manage a patient; preparing for an operative procedure; and reviewing progress during an operative procedure. The models represented here are an exploration of the complexity of the processes, designed to assist surgeons understand how expert clinical decision making occurs and to highlight the challenge of teaching these skills to surgical trainees. © 2013 The Authors. ANZ Journal of Surgery © 2013 Royal Australasian College of Surgeons.

Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores

ERIC Educational Resources Information Center

Douglas, Karen M.; Mislevy, Robert J.

2010-01-01

Important decisions about students are made by combining multiple measures using complex decision rules. Although methods for characterizing the accuracy of decisions based on a single measure have been suggested by numerous researchers, such methods are not useful for estimating the accuracy of decisions based on multiple measures. This study…

Elbow Room for Best Practice? Montgomery, Patients' values, and Balanced Decision-Making in Person-Centred Clinical Care.

PubMed

Herring, Jonathan; Fulford, Kmw; Dunn, Michael; Handa, Ashoki

2017-11-01

The UK Supreme Court Montgomery judgment marks a decisive shift in the legal test of duty of care in the context of consent to treatment, from the perspective of the clinician (as represented by Bolam rules) to that of the patient. A majority of commentators on Montgomery have focused on the implications of the judgment for disclosure of risk. In this article, we set risk disclosure in context with three further elements of the judgment: benefits, options, and dialogue. These elements, we argue, taken together with risk disclosure, reflect the origins of the Montgomery ruling in a model of consent based on autonomy of patient choice through shared decision-making with their doctor. This model reflects recent developments in both law and medicine and is widely regarded (by the General Medical Council and others) as representing best practice in contemporary person-centred medicine. So understood, we suggest, the shift marked by Montgomery in the basis of duty of care is a shift in underpinning values: it is a shift from the clinician's interpretation about what would be best for patients to the values of (to what is significant or matters from the perspective of) the particular patient concerned in the decision in question. But the values of the particular patient do not thereby become paramount. The Montgomery test of duty of care requires the values of the particular patient to be balanced alongside the values of a reasonable person in the patient's position. We illustrate some of the practical challenges arising from the balance of considerations required by Montgomery with examples from surgical care. These examples show the extent to which Montgomery, in mirroring the realities of clinical decision-making, provides elbowroom for best practice in person-centred clinical care. © The Author 2017. Published by Oxford University Press; all rights reserved. For Permissions, please email: journals.permissions@oup.com.

What is an ROC curve?

PubMed

Hoo, Zhe Hui; Candlish, Jane; Teare, Dawn

2017-06-01

The paper by Body et al is concerned with the evaluation of decision aids, which can be used to identify potential acute coronary syndromes (ACS) in the ED. The authors previously developed the Manchester Acute Coronary Syndromes model (MACS) decision aid, which uses several clinical variables and two biomarkers to 'rule in' and 'rule out' ACS. However, one of the two biomarkers (heart-type fatty acid bindingprotein, H-FABP) is not widely used so a revised decision aid has been developed (Troponin-only Manchester Acute Coronary Syndromes, T-MACS), which include a single biomarker hs-cTnT. In this issue, the authors show how they derive a revised decision aid and describe its performance in a number of independent diagnostic cohort studies. Decision aids (as well as other types of 'diagnostic tests') are often evaluated in terms of diagnostic testing parameters such as the area under the receiver operating characteristic (ROC) curve, sensitivity and specificity. In this article, we explain how the ROC analysis is conducted and why it is an essential step towards developing a test with the desirable levels of sensitivity and specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Narrative dynamics in social groups: A discrete choice model

NASA Astrophysics Data System (ADS)

Antoci, A.; Bellanca, N.; Galdi, G.; Sodini, M.

2018-05-01

Individuals follow different rules for action: they react swiftly, grasping the short-term advantages in sight, or they waste cognitive resources to complete otherwise easy tasks, but they are able to plan ahead future complex decisions. Scholars from different disciplines studied the conditions under which either decision rule may enhance the fitness of its adopters, with a focus on the environmental features. However, we here propose that a crucial feature of the evolution of populations and their decision rules is rather inter-group interactions. Indeed, we study what happens when two groups support different decision rules, encapsulated in narratives, and their populations interact with each other. In particular, we assume that the payoff of each rule depends on the share of both social groups which adopt such rules. We then describe the most salient dynamics scenarios and identify the conditions which lead to chaotic dynamics and multistability regimes.

The US Court of Appeals for the D.C. Circuit Ruling to Stay the CSAPR

EPA Pesticide Factsheets

The United States Court of Appeals for the D.C. Circuit issued its ruling to stay the CSAPR pending judicial review. The court's decision is not a decision on the merits of the rule. EPA is ensuring the transition back to the Clean Air Interstate Rule.

Is expected utility theory normative for medical decision making?

PubMed

Cohen, B J

1996-01-01

Expected utility theory is felt by its proponents to be a normative theory of decision making under uncertainty. The theory starts with some simple axioms that are held to be rules that any rational person would follow. It can be shown that if one adheres to these axioms, a numerical quantity, generally referred to as utility, can be assigned to each possible outcome, with the preferred course of action being that which has the highest expected utility. One of these axioms, the independence principle, is controversial, and is frequently violated in experimental situations. Proponents of the theory hold that these violations are irrational. The independence principle is simply an axiom dictating consistency among preferences, in that it dictates that a rational agent should hold a specified preference given another stated preference. When applied to preferences between lotteries, the independence principle can be demonstrated to be a rule that is followed only when preferences are formed in a particular way. The logic of expected utility theory is that this demonstration proves that preferences should be formed in this way. An alternative interpretation is that this demonstrates that the independence principle is not a valid general rule of consistency, but in particular, is a rule that must be followed if one is to consistently apply the decision rule "choose the lottery that has the highest expected utility." This decision rule must be justified on its own terms as a valid rule of rationality by demonstration that violation would lead to decisions that conflict with the decision maker's goals. This rule does not appear to be suitable for medical decisions because often these are one-time decisions in which expectation, a long-run property of a random variable, would not seem to be applicable. This is particularly true for those decisions involving a non-trivial risk of death.

Preventing Errors in Clinical Practice: A Call for Self-Awareness

PubMed Central

Borrell-Carrió, Francesc; Epstein, Ronald M.

2004-01-01

While ascribing medical errors primarily to systems factors can free clinicians from individual blame, there are elements of medical errors that can and should be attributed to individual factors. These factors are related less commonly to lack of knowledge and skill than to the inability to apply the clinician’s abilities to situations under certain circumstances. In concert with efforts to improve health care systems, refining physicians’ emotional and cognitive capacities might also prevent many errors. In general, physicians have the sensation of making a mistake because of the interference of emotional elements. We propose a so-called rational-emotive model that emphasizes 2 factors in error causation: (1) difficulty in reframing the first hypothesis that goes to the physician’s mind in an automatic way, and (2) premature closure of the clinical act to avoid confronting inconsistencies, low-level decision rules, and emotions. We propose a teaching strategy based on developing the physician’s insight and self-awareness to detect the inappropriate use of low-level decision rules, as well as detecting the factors that limit a physician’s capacity to tolerate the tension of uncertainty and ambiguity. Emotional self-awareness and self-regulation of attention can be consciously cultivated as habits to help physicians function better in clinical situations. PMID:15335129

Traumatic Brain Injury in Children: Role of CDRs-PECARN as a Clinical Predictive Resource for Evaluation of Intracranical Lesions and Neuropsychiatric Outcomes.

PubMed

Ferrara, Pietro; Basile, Maria Cristina; Dell'Aquila, Livia; Vena, Flaminia; Coppo, Elena; Chiaretti, Antonio; Verrotti, Alberto; Paolini, Fabrizio; Caldarelli, Massimo

2016-01-01

Cranial computed tomography (CT) is considered the gold standard for the diagnosis of traumatic brain injury (TBI). The aim of this study was to evaluate if the clinical decision rules proposed by the Pediatric Emergency Care Applied Research Network (CDRs-PECARN) are really able to identify the patients who do not need cranial CT. This study investigates the neuropsychiatric outcome after TBI according to a pediatric version of the Glasgow Outcome Scale-Extended (GOS-E Peds). We calculated the sensitivity, specificity, negative predictive value (NPV) and positive predictive value of the CDRs-PECARN in 2 age groups. Sensitivity was very high in both groups, and the NPV was very useful for predicting which subjects, of those who presented without CDRs- PECARN, would have a negative cranial CT. We also evaluated the correlations between the GOS-E Peds and Glasgow Coma Scale and between the GOS-E Peds and cranial CT scan. Our study confirms the validation of the PECARN TBI prediction rules as a clinical instrument which can play a significant role in CT decision-making for children with TBI. It also demonstrates that the GOS-E Peds is a valid pediatric outcome scale for children with TBI, despite some important limitations. © 2016 S. Karger AG, Basel.

Clinical Decision Rules for Diagnostic Imaging in the Emergency Department: A Research Agenda.

PubMed

Finnerty, Nathan M; Rodriguez, Robert M; Carpenter, Christopher R; Sun, Benjamin C; Theyyunni, Nik; Ohle, Robert; Dodd, Kenneth W; Schoenfeld, Elizabeth M; Elm, Kendra D; Kline, Jeffrey A; Holmes, James F; Kuppermann, Nathan

2015-12-01

Major gaps persist in the development, validation, and implementation of clinical decision rules (CDRs) for diagnostic imaging. The objective of this working group and article was to generate a consensus-based research agenda for the development and implementation of CDRs for diagnostic imaging in the emergency department (ED). The authors followed consensus methodology, as outlined by the journal Academic Emergency Medicine (AEM), combining literature review, electronic surveys, telephonic communications, and a modified nominal group technique. Final discussions occurred in person at the 2015 AEM consensus conference. A research agenda was developed, prioritizing the following questions: 1) what are the optimal methods to justify the derivation and validation of diagnostic imaging CDRs, 2) what level of evidence is required before disseminating CDRs for widespread implementation, 3) what defines a successful CDR, 4) how should investigators best compare CDRs to clinical judgment, and 5) what disease states are amenable (and highest priority) to development of CDRs for diagnostic imaging in the ED? The concepts discussed herein demonstrate the need for further research on CDR development and implementation regarding diagnostic imaging in the ED. Addressing this research agenda should have direct applicability to patients, clinicians, and health care systems. © 2015 by the Society for Academic Emergency Medicine.

Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences

PubMed Central

Lo, Benjamin W. Y.; Macdonald, R. Loch; Baker, Andrew; Levine, Mitchell A. H.

2013-01-01

Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH). Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients). Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs). Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique) denoted cut-off points for poor prognosis at greater than 2.5 clusters. Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication. PMID:23690884

Preventing errors in clinical practice: a call for self-awareness.

PubMed

Borrell-Carrió, Francesc; Epstein, Ronald M

2004-01-01

While ascribing medical errors primarily to systems factors can free clinicians from individual blame, there are elements of medical errors that can and should be attributed to individual factors. These factors are related less commonly to lack of knowledge and skill than to the inability to apply the clinician's abilities to situations under certain circumstances. In concert with efforts to improve health care systems, refining physicians' emotional and cognitive capacities might also prevent many errors. In general, physicians have the sensation of making a mistake because of the interference of emotional elements. We propose a so-called rational-emotive model that emphasizes 2 factors in error causation: (1) difficulty in reframing the first hypothesis that goes to the physician's mind in an automatic way, and (2) premature closure of the clinical act to avoid confronting inconsistencies, low-level decision rules, and emotions. We propose a teaching strategy based on developing the physician's insight and self-awareness to detect the inappropriate use of low-level decision rules, as well as detecting the factors that limit a physician's capacity to tolerate the tension of uncertainty and ambiguity. Emotional self-awareness and self-regulation of attention can be consciously cultivated as habits to help physicians function better in clinical situations.

Using whole disease modeling to inform resource allocation decisions: economic evaluation of a clinical guideline for colorectal cancer using a single model.

PubMed

Tappenden, Paul; Chilcott, Jim; Brennan, Alan; Squires, Hazel; Glynne-Jones, Rob; Tappenden, Janine

2013-06-01

To assess the feasibility and value of simulating whole disease and treatment pathways within a single model to provide a common economic basis for informing resource allocation decisions. A patient-level simulation model was developed with the intention of being capable of evaluating multiple topics within National Institute for Health and Clinical Excellence's colorectal cancer clinical guideline. The model simulates disease and treatment pathways from preclinical disease through to detection, diagnosis, adjuvant/neoadjuvant treatments, follow-up, curative/palliative treatments for metastases, supportive care, and eventual death. The model parameters were informed by meta-analyses, randomized trials, observational studies, health utility studies, audit data, costing sources, and expert opinion. Unobservable natural history parameters were calibrated against external data using Bayesian Markov chain Monte Carlo methods. Economic analysis was undertaken using conventional cost-utility decision rules within each guideline topic and constrained maximization rules across multiple topics. Under usual processes for guideline development, piecewise economic modeling would have been used to evaluate between one and three topics. The Whole Disease Model was capable of evaluating 11 of 15 guideline topics, ranging from alternative diagnostic technologies through to treatments for metastatic disease. The constrained maximization analysis identified a configuration of colorectal services that is expected to maximize quality-adjusted life-year gains without exceeding current expenditure levels. This study indicates that Whole Disease Model development is feasible and can allow for the economic analysis of most interventions across a disease service within a consistent conceptual and mathematical infrastructure. This disease-level modeling approach may be of particular value in providing an economic basis to support other clinical guidelines. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Development of clinical decision rules to predict recurrent shock in dengue

PubMed Central

2013-01-01

Introduction Mortality from dengue infection is mostly due to shock. Among dengue patients with shock, approximately 30% have recurrent shock that requires a treatment change. Here, we report development of a clinical rule for use during a patient’s first shock episode to predict a recurrent shock episode. Methods The study was conducted in Center for Preventive Medicine in Vinh Long province and the Children’s Hospital No. 2 in Ho Chi Minh City, Vietnam. We included 444 dengue patients with shock, 126 of whom had recurrent shock (28%). Univariate and multivariate analyses and a preprocessing method were used to evaluate and select 14 clinical and laboratory signs recorded at shock onset. Five variables (admission day, purpura/ecchymosis, ascites/pleural effusion, blood platelet count and pulse pressure) were finally trained and validated by a 10-fold validation strategy with 10 times of repetition, using a logistic regression model. Results The results showed that shorter admission day (fewer days prior to admission), purpura/ecchymosis, ascites/pleural effusion, low platelet count and narrow pulse pressure were independently associated with recurrent shock. Our logistic prediction model was capable of predicting recurrent shock when compared to the null method (P < 0.05) and was not outperformed by other prediction models. Our final scoring rule provided relatively good accuracy (AUC, 0.73; sensitivity and specificity, 68%). Score points derived from the logistic prediction model revealed identical accuracy with AUCs at 0.73. Using a cutoff value greater than −154.5, our simple scoring rule showed a sensitivity of 68.3% and a specificity of 68.2%. Conclusions Our simple clinical rule is not to replace clinical judgment, but to help clinicians predict recurrent shock during a patient’s first dengue shock episode. PMID:24295509

How to translate therapeutic recommendations in clinical practice guidelines into rules for critiquing physician prescriptions? Methods and application to five guidelines

PubMed Central

2010-01-01

Background Clinical practice guidelines give recommendations about what to do in various medical situations, including therapeutical recommendations for drug prescription. An effective way to computerize these recommendations is to design critiquing decision support systems, i.e. systems that criticize the physician's prescription when it does not conform to the guidelines. These systems are commonly based on a list of "if conditions then criticism" rules. However, writing these rules from the guidelines is not a trivial task. The objective of this article is to propose methods that (1) simplify the implementation of guidelines' therapeutical recommendations in critiquing systems by automatically translating structured therapeutical recommendations into a list of "if conditions then criticize" rules, and (2) can generate an appropriate textual label to explain to the physician why his/her prescription is not recommended. Methods We worked on the therapeutic recommendations in five clinical practice guidelines concerning chronic diseases related to the management of cardiovascular risk. We evaluated the system using a test base of more than 2000 cases. Results Algorithms for automatically translating therapeutical recommendations into "if conditions then criticize" rules are presented. Eight generic recommendations are also proposed; they are guideline-independent, and can be used as default behaviour for handling various situations that are usually implicit in the guidelines, such as decreasing the dose of a poorly tolerated drug. Finally, we provide models and methods for generating a human-readable textual critique. The system was successfully evaluated on the test base. Conclusion We show that it is possible to criticize physicians' prescriptions starting from a structured clinical guideline, and to provide clear explanations. We are now planning a randomized clinical trial to evaluate the impact of the system on practices. PMID:20509903

Spontaneous Subarachnoid Hemorrhage: A Systematic Review and Meta-Analysis Describing the Diagnostic Accuracy of History, Physical Exam, Imaging, and Lumbar Puncture with an Exploration of Test Thresholds

PubMed Central

Carpenter, Christopher R.; Hussain, Adnan M.; Ward, Michael J.; Zipfel, Gregory J.; Fowler, Susan; Pines, Jesse M.; Sivilotti, Marco L.A.

2016-01-01

Background Spontaneous subarachnoid hemorrhage (SAH) is a rare, but serious etiology of headache. The diagnosis of SAH is especially challenging in alert, neurologically intact patients, as missed or delayed diagnosis can be catastrophic. Objectives To perform a diagnostic accuracy systematic review and meta-analysis of history, physical examination, cerebrospinal fluid (CSF) tests, computed tomography (CT), and clinical decision rules for spontaneous SAH. A secondary objective was to delineate probability of disease thresholds for imaging and lumbar puncture (LP). Methods PUBMED, EMBASE, SCOPUS, and research meeting abstracts were searched up to June 2015 for studies of emergency department (ED) patients with acute headache clinically concerning for spontaneous SAH. QUADAS-2 was used to assess study quality and, when appropriate, meta-analysis was conducted using random effects models. Outcomes were sensitivity, specificity, positive (LR+) and negative (LR−) likelihood ratios. To identify test- and treatment-thresholds, we employed the Pauker-Kassirer method with Bernstein test-indication curves using the summary estimates of diagnostic accuracy. Results A total of 5,022 publications were identified, of which 122 underwent full text-review; 22 studies were included (average SAH prevalence 7.5%). Diagnostic studies differed in assessment of history and physical exam findings, CT technology, analytical techniques used to identify xanthochromia, and criterion standards for SAH. Study quality by QUADAS-2 was variable; however, most had a relatively low-risk of biases. A history of neck pain (LR+ 4.1 [95% CI 2.2-7.6]) and neck stiffness on physical exam (LR+ 6.6 [4.0-11.0]) were the individual findings most strongly associated with SAH. Combinations of findings may rule out SAH, yet promising clinical decision rules await external validation. Non-contrast cranial CT within 6 hours of headache onset accurately ruled-in (LR+ 230 [6-8700]) and ruled-out SAH (LR− 0.01 [0-0.04]); CT beyond 6 hours had a LR− of 0.07 [0.01-0.61]. CSF analyses had lower diagnostic accuracy, whether using red blood cell (RBC) count or xanthochromia. At a threshold RBC count of 1,000 × 106/L, the LR+ was 5.7 [1.4-23] and LR− 0.21 [0.03-1.7]. Using the pooled estimates of diagnostic accuracy and testing risks and benefits, we estimate LP only benefits CT negative patients when the pre-LP probability of SAH is on the order of 5%, which corresponds to a pre-CT probability greater than 20%. Conclusions Less than one in ten headache patients concerning for SAH are ultimately diagnosed with SAH in recent studies. While certain symptoms and signs increase or decrease the likelihood of SAH, no single characteristic is sufficient to rule-in or rule-out SAH. Within 6 hours of symptom onset, non-contrast cranial CT is highly accurate, while a negative CT beyond 6 hours substantially reduces the likelihood of SAH. LP appears to benefit relatively few patients within a narrow pre-test probability range. With improvements in CT technology and an expanding body of evidence, test-thresholds for LP may become more precise, obviating the need for a post-CT LP in more acute headache patients. Existing SAH clinical decision rules await external validation, but offer the potential to identify subsets most likely to benefit from post-CT LP, angiography, or no further testing. PMID:27306497

46 CFR 201.159 - Decisions; contents and service.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 8 2012-10-01 2012-10-01 false Decisions; contents and service. 201.159 Section 201.159 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) § 201.159 Decisions; contents and service. All initial,...

Judgment and decision making.

PubMed

Mellers, B A; Schwartz, A; Cooke, A D

1998-01-01

For many decades, research in judgment and decision making has examined behavioral violations of rational choice theory. In that framework, rationality is expressed as a single correct decision shared by experimenters and subjects that satisfies internal coherence within a set of preferences and beliefs. Outside of psychology, social scientists are now debating the need to modify rational choice theory with behavioral assumptions. Within psychology, researchers are debating assumptions about errors for many different definitions of rationality. Alternative frameworks are being proposed. These frameworks view decisions as more reasonable and adaptive that previously thought. For example, "rule following." Rule following, which occurs when a rule or norm is applied to a situation, often minimizes effort and provides satisfying solutions that are "good enough," though not necessarily the best. When rules are ambiguous, people look for reasons to guide their decisions. They may also let their emotions take charge. This chapter presents recent research on judgment and decision making from traditional and alternative frameworks.

Extraneous factors in judicial decisions

PubMed Central

Danziger, Shai; Levav, Jonathan; Avnaim-Pesso, Liora

2011-01-01

Are judicial rulings based solely on laws and facts? Legal formalism holds that judges apply legal reasons to the facts of a case in a rational, mechanical, and deliberative manner. In contrast, legal realists argue that the rational application of legal reasons does not sufficiently explain the decisions of judges and that psychological, political, and social factors influence judicial rulings. We test the common caricature of realism that justice is “what the judge ate for breakfast” in sequential parole decisions made by experienced judges. We record the judges’ two daily food breaks, which result in segmenting the deliberations of the day into three distinct “decision sessions.” We find that the percentage of favorable rulings drops gradually from ≈65% to nearly zero within each decision session and returns abruptly to ≈65% after a break. Our findings suggest that judicial rulings can be swayed by extraneous variables that should have no bearing on legal decisions. PMID:21482790

Collective decision making and social interaction rules in mixed-species flocks of songbirds

PubMed Central

Farine, Damien R.; Aplin, Lucy M.; Garroway, Colin J.; Mann, Richard P.; Sheldon, Ben C.

2014-01-01

Associations in mixed-species foraging groups are common in animals, yet have rarely been explored in the context of collective behaviour. Despite many investigations into the social and ecological conditions under which individuals should form groups, we still know little about the specific behavioural rules that individuals adopt in these contexts, or whether these can be generalized to heterospecifics. Here, we studied collective behaviour in flocks in a community of five species of woodland passerine birds. We adopted an automated data collection protocol, involving visits by RFID-tagged birds to feeding stations equipped with antennae, over two winters, recording 91 576 feeding events by 1904 individuals. We demonstrated highly synchronized feeding behaviour within patches, with birds moving towards areas of the patch with the largest proportion of the flock. Using a model of collective decision making, we then explored the underlying decision rule birds may be using when foraging in mixed-species flocks. The model tested whether birds used a different decision rule for conspecifics and heterospecifics, and whether the rules used by individuals of different species varied. We found that species differed in their response to the distribution of conspecifics and heterospecifics across foraging patches. However, simulating decisions using the different rules, which reproduced our data well, suggested that the outcome of using different decision rules by each species resulted in qualitatively similar overall patterns of movement. It is possible that the decision rules each species uses may be adjusted to variation in mean species abundance in order for individuals to maintain the same overall flock-level response. This is likely to be important for maintaining coordinated behaviour across species, and to result in quick and adaptive flock responses to food resources that are patchily distributed in space and time. PMID:25214653

Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang

2015-01-01

Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

A pilot study of distributed knowledge management and clinical decision support in the cloud.

PubMed

Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

2013-09-01

Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable path toward achieving better support of clinical decision-making across the widest range of health care providers. Published by Elsevier B.V.

Cost-effectiveness of the PECARN rules in children with minor head trauma.

PubMed

Nishijima, Daniel K; Yang, Zhuo; Urbich, Michael; Holmes, James F; Zwienenberg-Lee, Marike; Melnikow, Joy; Kuppermann, Nathan

2015-01-01

To improve the efficiency and appropriateness of computed tomography (CT) use in children with minor head trauma, clinical prediction rules were derived and validated by the Pediatric Emergency Care Applied Research Network (PECARN). The objective of this study was to conduct a cost-effectiveness analysis comparing the PECARN traumatic brain injury prediction rules to usual care for selective CT use. We used decision analytic modeling to project the outcomes, costs, and cost-effectiveness of applying the PECARN rules compared with usual care in a hypothetical cohort of 1,000 children with minor blunt head trauma. Clinical management was directed by level of risk as specified by the presence or absence of variables in the PECARN traumatic brain injury prediction rules. Immediate costs of care (diagnostic testing, treatment [not including clinician time], and hospital stay) were derived on single-center data. Quality-adjusted life-year losses related to the sequelae of clinically important traumatic brain injuries and to radiation-induced cancers, number of CT scans, number of radiation-induced cancers, number of missed clinically important traumatic brain injury, and total costs were evaluated. Compared with the usual care strategy, the PECARN strategy was projected to miss slightly more children with clinically important traumatic brain injuries (0.26 versus 0.02 per 1,000 children) but used fewer cranial CT scans (274 versus 353), resulted in fewer radiation-induced cancers (0.34 versus 0.45), cost less ($904,940 versus $954,420), and had lower net quality-adjusted life-year loss (-4.64 versus -5.79). Because the PECARN strategy was more effective (less quality-adjusted life-year loss) and less costly, it dominated the usual care strategy. Results were robust under sensitivity analyses. Application of the PECARN traumatic brain injury prediction rules for children with minor head trauma would lead to beneficial outcomes and more cost-effective care. Copyright © 2014 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Impact of delay in clinical presentation on the diagnostic management and prognosis of patients with suspected pulmonary embolism.

PubMed

den Exter, Paul L; van Es, Josien; Erkens, Petra M G; van Roosmalen, Mark J G; van den Hoven, Pim; Hovens, Marcel M C; Kamphuisen, Pieter W; Klok, Frederikus A; Huisman, Menno V

2013-06-15

The nonspecific clinical presentation of pulmonary embolism (PE) frequently leads to delay in its diagnosis. This study aimed to assess the impact of delay in presentation on the diagnostic management and clinical outcome of patients with suspected PE. In 4,044 consecutive patients with suspected PE, patients presenting more than 7 days from the onset of symptoms were contrasted with those presenting within 7 days as regards the safety of excluding PE on the basis of a clinical decision rule combined with D-dimer testing. Patients were followed for 3 months to assess the rates of recurrent venous thromboembolism and mortality. A delayed presentation (presentation >7 d) was present in 754 (18.6%) of the patients. The failure rate of an unlikely clinical probability and normal D-dimer test was 0.5% (95% confidence interval [CI], 0.01-2.7) for patients with and 0.5% (95% CI, 0.2-1.2) for those without diagnostic delay. D-dimer testing yielded a sensitivity of 99% (95% CI, 96-99%) and 98% (95% CI, 97-99%) in these groups, respectively. Patients with PE with diagnostic delay more frequently had centrally located PE (41% vs. 26%; P < 0.001). The cumulative rates of recurrent venous thromboembolism (4.6% vs. 2.7%; P = 0.14) and mortality (7.6% vs. 6.6%; P = 0.31) were not different for patients with and without delayed presentation. PE can be safely excluded based on a clinical decision rule and D-dimer testing in patients with a delayed clinical presentation. A delayed presentation for patients who survived acute PE was associated with a more central PE location, although this did not affect the clinical outcome at 3 months.

[When should a patient with musculoskeletal trauma be referred to emergency ward?].

PubMed

Feiner, Adam-Scott; Duruz, Henri

2010-08-25

Standardized clinical examination can obviate the need for osteoarticular radiographs for trauma. This paper summarizes a number of decision rules that allow clinical exclusion of significant fracture of the cervical spine, elbow, knee or ankle, making radiographs unnecessary. These criteria were all derived from large cohort studies (Nexus, Ottawa, CCS, etc..., and have been prospectively validated. The rigorous use of these criteria in daily practice improves treatment times and costs with no adverse effect on treatment quality.

16 CFR 3.51 - Initial decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Initial decision. 3.51 Section 3.51 Commercial Practices FEDERAL TRADE COMMISSION ORGANIZATION, PROCEDURES AND RULES OF PRACTICE RULES OF PRACTICE FOR ADJUDICATIVE PROCEEDINGS Decision § 3.51 Initial decision. (a) When filed and when effective. The Administrative Law Judge shall file an...

16 CFR 3.52 - Appeal from initial decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Appeal from initial decision. 3.52 Section 3.52 Commercial Practices FEDERAL TRADE COMMISSION ORGANIZATION, PROCEDURES AND RULES OF PRACTICE RULES OF PRACTICE FOR ADJUDICATIVE PROCEEDINGS Decision § 3.52 Appeal from initial decision. (a) Automatic review of cases in which the Commission sough...

49 CFR 1503.631 - Interlocutory appeals.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Rules of Practice in TSA Civil Penalty Actions § 1503.631 Interlocutory appeals. (a) General. Unless otherwise provided in this subpart, a party may not appeal a ruling or decision of the ALJ to the TSA decision maker until the initial decision has been entered on the record. A decision or order of the TSA...

Pediatric Minor Head Injury 2.0: Moving from Injury Exclusion to Risk Stratification.

PubMed

Homme, James Jim L

2018-05-01

Visits for pediatric minor blunt head trauma continue to increase. Variability exists in clinician evaluation and management of this generally low-risk population. Clinical decision rules identify very low-risk children who can forgo neuroimaging. Observation before imaging decreases neuroimaging rates. Outcome data can be used to risk stratify children into more discrete categories. Decision aids improves knowledge and accuracy of risk perception and facilitates identification of caregiver preferences, allowing for shared decision making. For children in whom imaging is performed and is normal or shows isolated linear skull fractures, deterioration and neurosurgical intervention are rare and hospital admission can be avoided. Copyright © 2018 The Author. Published by Elsevier Inc. All rights reserved.

A detailed comparison of optimality and simplicity in perceptual decision-making

PubMed Central

Shen, Shan; Ma, Wei Ji

2017-01-01

Two prominent ideas in the study of decision-making have been that organisms behave near-optimally, and that they use simple heuristic rules. These principles might be operating in different types of tasks, but this possibility cannot be fully investigated without a direct, rigorous comparison within a single task. Such a comparison was lacking in most previous studies, because a) the optimal decision rule was simple; b) no simple suboptimal rules were considered; c) it was unclear what was optimal, or d) a simple rule could closely approximate the optimal rule. Here, we used a perceptual decision-making task in which the optimal decision rule is well-defined and complex, and makes qualitatively distinct predictions from many simple suboptimal rules. We find that all simple rules tested fail to describe human behavior, that the optimal rule accounts well for the data, and that several complex suboptimal rules are indistinguishable from the optimal one. Moreover, we found evidence that the optimal model is close to the true model: first, the better the trial-to-trial predictions of a suboptimal model agree with those of the optimal model, the better that suboptimal model fits; second, our estimate of the Kullback-Leibler divergence between the optimal model and the true model is not significantly different from zero. When observers receive no feedback, the optimal model still describes behavior best, suggesting that sensory uncertainty is implicitly represented and taken into account. Beyond the task and models studied here, our results have implications for best practices of model comparison. PMID:27177259

Decision technology.

PubMed

Edwards, W; Fasolo, B

2001-01-01

This review is about decision technology-the rules and tools that help us make wiser decisions. First, we review the three rules that are at the heart of most traditional decision technology-multi-attribute utility, Bayes' theorem, and subjective expected utility maximization. Since the inception of decision research, these rules have prescribed how we should infer values and probabilities and how we should combine them to make better decisions. We suggest how to make best use of all three rules in a comprehensive 19-step model. The remainder of the review explores recently developed tools of decision technology. It examines the characteristics and problems of decision-facilitating sites on the World Wide Web. Such sites now provide anyone who can use a personal computer with access to very sophisticated decision-aiding tools structured mainly to facilitate consumer decision making. It seems likely that the Web will be the mode by means of which decision tools will be distributed to lay users. But methods for doing such apparently simple things as winnowing 3000 options down to a more reasonable number, like 10, contain traps for unwary decision technologists. The review briefly examines Bayes nets and influence diagrams-judgment and decision-making tools that are available as computer programs. It very briefly summarizes the state of the art of eliciting probabilities from experts. It concludes that decision tools will be as important in the 21st century as spreadsheets were in the 20th.

A study of some nine-element decision rules. [for multispectral recognition of remote sensing

NASA Technical Reports Server (NTRS)

Richardson, W.

1974-01-01

A nine-element rule is one that makes a classification decision for each pixel based on data from that pixel and its eight immediate neighbors. Three such rules, all fast and simple to use, are defined and tested. All performed substantially better on field interiors than the best one-point rule. Qualitative results indicate that fine detail and contradictory testimony tend to be overlooked by the rules.

Distributive justice and infertility treatment in Canada.

PubMed

Nisker, Jeff

2008-05-01

An exploration of distributive justice in Canadian infertility treatment requires the integration of ethical, clinical, and economic principles. In 1971, American philosopher John Rawls proposed a theoretical model for fair decision-making in which "rational" and "self-interested" citizens are behind a "veil of ignorance" with respect to both their own position and the position of other decision-makers. Rawls proposed that these self-interested decision-makers, fearing that they are among the least advantaged persons who could be affected by the decision, will agree only upon rules that encode equality of opportunity and that bestow the greatest benefit on the least advantaged citizens. Regarding health policy decision-making, Rawls' model is best illustrated by Canadian philosopher Warren Bourgeois in his panel of "volunteers." These rational and self-interested volunteers receive an amnestic drug that renders them unaware of their health, social, and financial position, but they know that they are representative of diverse spheres of citizens whose well-being will be affected by their decision. After describing fair decision-making, Bourgeois considers the lack of a distributive justice imperative in Canada's Assisted Human Reproduction Act, in contrast to legislation in European nations and Australia, summarizes the economic and clinical considerations that must be provided to the decision-makers behind the "veil of ignorance" for fair decisions to occur, and considers altruism in relation to equality of access. He concludes by noting that among countries with legislation governing assisted reproduction Canada is alone in having legislation that is void of distributive justice in providing access to clinically appropriate infertility care.

A model-driven privacy compliance decision support for medical data sharing in Europe.

PubMed

Boussi Rahmouni, H; Solomonides, T; Casassa Mont, M; Shiu, S; Rahmouni, M

2011-01-01

Clinical practitioners and medical researchers often have to share health data with other colleagues across Europe. Privacy compliance in this context is very important but challenging. Automated privacy guidelines are a practical way of increasing users' awareness of privacy obligations and help eliminating unintentional breaches of privacy. In this paper we present an ontology-plus-rules based approach to privacy decision support for the sharing of patient data across European platforms. We use ontologies to model the required domain and context information about data sharing and privacy requirements. In addition, we use a set of Semantic Web Rule Language rules to reason about legal privacy requirements that are applicable to a specific context of data disclosure. We make the complete set invocable through the use of a semantic web application acting as an interactive privacy guideline system can then invoke the full model in order to provide decision support. When asked, the system will generate privacy reports applicable to a specific case of data disclosure described by the user. Also reports showing guidelines per Member State may be obtained. The advantage of this approach lies in the expressiveness and extensibility of the modelling and inference languages adopted and the ability they confer to reason with complex requirements interpreted from high level regulations. However, the system cannot at this stage fully simulate the role of an ethics committee or review board.

Silence That Can Be Dangerous: A Vignette Study to Assess Healthcare Professionals’ Likelihood of Speaking up about Safety Concerns

PubMed Central

Schwappach, David L. B.; Gehring, Katrin

2014-01-01

Purpose To investigate the likelihood of speaking up about patient safety in oncology and to clarify the effect of clinical and situational context factors on the likelihood of voicing concerns. Patients and Methods 1013 nurses and doctors in oncology rated four clinical vignettes describing coworkers’ errors and rule violations in a self-administered factorial survey (65% response rate). Multiple regression analysis was used to model the likelihood of speaking up as outcome of vignette attributes, responder’s evaluations of the situation and personal characteristics. Results Respondents reported a high likelihood of speaking up about patient safety but the variation between and within types of errors and rule violations was substantial. Staff without managerial function provided significantly higher levels of decision difficulty and discomfort to speak up. Based on the information presented in the vignettes, 74%−96% would speak up towards a supervisor failing to check a prescription, 45%−81% would point a coworker to a missed hand disinfection, 82%−94% would speak up towards nurses who violate a safety rule in medication preparation, and 59%−92% would question a doctor violating a safety rule in lumbar puncture. Several vignette attributes predicted the likelihood of speaking up. Perceived potential harm, anticipated discomfort, and decision difficulty were significant predictors of the likelihood of speaking up. Conclusions Clinicians’ willingness to speak up about patient safety is considerably affected by contextual factors. Physicians and nurses without managerial function report substantial discomfort with speaking up. Oncology departments should provide staff with clear guidance and trainings on when and how to voice safety concerns. PMID:25116338

Tips for Teachers of Evidence-based Medicine: Clinical Prediction Rules (CPRs) and Estimating Pretest Probability

PubMed Central

McGinn, Thomas; Jervis, Ramiro; Wisnivesky, Juan; Keitz, Sheri

2008-01-01

Background Clinical prediction rules (CPR) are tools that clinicians can use to predict the most likely diagnosis, prognosis, or response to treatment in a patient based on individual characteristics. CPRs attempt to standardize, simplify, and increase the accuracy of clinicians’ diagnostic and prognostic assessments. The teaching tips series is designed to give teachers advice and materials they can use to attain specific educational objectives. Educational Objectives In this article, we present 3 teaching tips aimed at helping clinical learners use clinical prediction rules and to more accurately assess pretest probability in every day practice. The first tip is designed to demonstrate variability in physician estimation of pretest probability. The second tip demonstrates how the estimate of pretest probability influences the interpretation of diagnostic tests and patient management. The third tip exposes learners to various examples and different types of Clinical Prediction Rules (CPR) and how to apply them in practice. Pilot Testing We field tested all 3 tips with 16 learners, a mix of interns and senior residents. Teacher preparatory time was approximately 2 hours. The field test utilized a board and a data projector; 3 handouts were prepared. The tips were felt to be clear and the educational objectives reached. Potential teaching pitfalls were identified. Conclusion Teaching with these tips will help physicians appreciate the importance of applying evidence to their every day decisions. In 2 or 3 short teaching sessions, clinicians can also become familiar with the use of CPRs in applying evidence consistently in everyday practice. PMID:18491194

Concurrent approach for evolving compact decision rule sets

NASA Astrophysics Data System (ADS)

Marmelstein, Robert E.; Hammack, Lonnie P.; Lamont, Gary B.

1999-02-01

The induction of decision rules from data is important to many disciplines, including artificial intelligence and pattern recognition. To improve the state of the art in this area, we introduced the genetic rule and classifier construction environment (GRaCCE). It was previously shown that GRaCCE consistently evolved decision rule sets from data, which were significantly more compact than those produced by other methods (such as decision tree algorithms). The primary disadvantage of GRaCCe, however, is its relatively poor run-time execution performance. In this paper, a concurrent version of the GRaCCE architecture is introduced, which improves the efficiency of the original algorithm. A prototype of the algorithm is tested on an in- house parallel processor configuration and the results are discussed.

The U.S. Army’s Health Risk Appraisal (HRA) Survey, Part I, History, Reliability, and Validity

DTIC Science & Technology

2003-08-01

reports as a clinical decision-making rule in deciding whether or not to administer the screening test. Second, accuracy of patient self-reports may...10): 1665-1669, 1997. 6. Baker, F., S. R. Ainsworth, J. T. Dye, C. Crammer , M. J. Thun, D. Hoffmann, J. L. Repace, J. E. Henningfield, J. Slade, J

Prediction of High-Grade Vesicoureteral Reflux after Pediatric Urinary Tract Infection: External Validation Study of Procalcitonin-Based Decision Rule

PubMed Central

Leroy, Sandrine; Bouissou, François; Fernandez-Lopez, Anna; Gurgoze, Metin K.; Karavanaki, Kyriaki; Ulinski, Tim; Bressan, Silvia; Vaos, Geogios; Leblond, Pierre; Coulais, Yvon; Cubells, Carlos Luaces; Aygun, A. Denizmen; Stefanidis, Constantinos J.; Bensman, Albert; DaDalt, Liviana; Gardikis, Stefanos; Bigot, Sandra; Gendrel, Dominique; Bréart, Gérard; Chalumeau, Martin

2011-01-01

Background Predicting vesico-ureteral reflux (VUR) ≥3 at the time of the first urinary tract infection (UTI) would make it possible to restrict cystography to high-risk children. We previously derived the following clinical decision rule for that purpose: cystography should be performed in cases with ureteral dilation and a serum procalcitonin level ≥0.17 ng/mL, or without ureteral dilatation when the serum procalcitonin level ≥0.63 ng/mL. The rule yielded a 86% sensitivity with a 46% specificity. We aimed to test its reproducibility. Study Design A secondary analysis of prospective series of children with a first UTI. The rule was applied, and predictive ability was calculated. Results The study included 413 patients (157 boys, VUR ≥3 in 11%) from eight centers in five countries. The rule offered a 46% specificity (95% CI, 41–52), not different from the one in the derivation study. However, the sensitivity significantly decreased to 64% (95%CI, 50–76), leading to a difference of 20% (95%CI, 17–36). In all, 16 (34%) patients among the 47 with VUR ≥3 were misdiagnosed by the rule. This lack of reproducibility might result primarily from a difference between derivation and validation populations regarding inflammatory parameters (CRP, PCT); the validation set samples may have been collected earlier than for the derivation one. Conclusions The rule built to predict VUR ≥3 had a stable specificity (ie. 46%), but a decreased sensitivity (ie. 64%) because of the time variability of PCT measurement. Some refinement may be warranted. PMID:22216314

Validation of the Oudega diagnostic decision rule for diagnosing deep vein thrombosis in frail older out-of-hospital patients.

PubMed

Schouten, Henrike J; Koek, Huiberdina L; Oudega, Ruud; van Delden, Johannes J M; Moons, Karel G M; Geersing, Geert-Jan

2015-02-01

We aimed to validate the Oudega diagnostic decision rule-which was developed and validated among younger aged primary care patients-to rule-out deep vein thrombosis (DVT) in frail older outpatients. In older patients (>60 years, either community dwelling or residing in nursing homes) with clinically suspected DVT, physicians recorded the score on the Oudega rule and d-dimer test. DVT was confirmed with a composite reference standard including ultrasonography examination and 3-month follow-up. The proportion of patients with a very low probability of DVT according to the Oudega rule (efficiency), and the proportion of patients with symptomatic venous thromboembolism during 3 months follow-up within this 'very low risk' group (failure rate) was calculated. DVT occurred in 164 (47%) of the 348 study participants (mean age 81 years, 85% residing in nursing homes). The probability of DVT was very low in 69 patients (Oudega score ≤3 points plus a normal d-dimer test; efficiency 20%) of whom four had non-fatal DVT (failure rate 5.8%; 2.3-14%). With a simple revised version of the Oudega rule for older suspected patients, 43 patients had a low risk of DVT (12% of the total population) of whom only one had DVT (failure rate 2.3%; 0.4-12%). In older suspected patients, application of the original Oudega rule to exclude DVT resulted in a higher failure rate as compared to previous studies. A revised and simplified Oudega strategy specifically developed for elderly suspected patients resulted in a lower failure rate though at the expense of a lower efficiency. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

PubMed

Raposo, Letícia M; Nobre, Flavio F

2017-08-30

Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

Application of Adaptive Design Methodology in Development of a Long-Acting Glucagon-Like Peptide-1 Analog (Dulaglutide): Statistical Design and Simulations

PubMed Central

Skrivanek, Zachary; Berry, Scott; Berry, Don; Chien, Jenny; Geiger, Mary Jane; Anderson, James H.; Gaydos, Brenda

2012-01-01

Background Dulaglutide (dula, LY2189265), a long-acting glucagon-like peptide-1 analog, is being developed to treat type 2 diabetes mellitus. Methods To foster the development of dula, we designed a two-stage adaptive, dose-finding, inferentially seamless phase 2/3 study. The Bayesian theoretical framework is used to adaptively randomize patients in stage 1 to 7 dula doses and, at the decision point, to either stop for futility or to select up to 2 dula doses for stage 2. After dose selection, patients continue to be randomized to the selected dula doses or comparator arms. Data from patients assigned the selected doses will be pooled across both stages and analyzed with an analysis of covariance model, using baseline hemoglobin A1c and country as covariates. The operating characteristics of the trial were assessed by extensive simulation studies. Results Simulations demonstrated that the adaptive design would identify the correct doses 88% of the time, compared to as low as 6% for a fixed-dose design (the latter value based on frequentist decision rules analogous to the Bayesian decision rules for adaptive design). Conclusions This article discusses the decision rules used to select the dula dose(s); the mathematical details of the adaptive algorithm—including a description of the clinical utility index used to mathematically quantify the desirability of a dose based on safety and efficacy measurements; and a description of the simulation process and results that quantify the operating characteristics of the design. PMID:23294775

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

14 CFR 14.27 - Decision.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...

14 CFR 14.27 - Decision.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...

14 CFR 14.27 - Decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...

14 CFR 14.27 - Decision.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...

14 CFR 14.27 - Decision.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Decision. 14.27 Section 14.27 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES IMPLEMENTING THE EQUAL ACCESS TO JUSTICE ACT OF 1980 Procedures for Considering Applications § 14.27 Decision...

Applying strategies from libertarian paternalism to decision making for prostate specific antigen (PSA) screening

PubMed Central

2011-01-01

Background Despite the recent publication of results from two randomized clinical trials, prostate specific antigen (PSA) screening for prostate cancer remains a controversial issue. There is lack of agreement across studies that PSA screening significantly reduces prostate cancer mortality. In spite of these facts, the widespread use of PSA testing in the United States leads to overdetection and overtreatment of clinically indolent prostate cancer, and its associated harms of incontinence and impotence. Discussion Given the inconclusive results from clinical trials and incongruent PSA screening guidelines, the decision to screen for prostate cancer with PSA testing is an uncertain one for patients and health care providers. Screening guidelines from some health organizations recommend an informed decision making (IDM) or shared decision making (SDM) approach for deciding on PSA screening. These approaches aim to empower patients to choose among the available options by making them active participants in the decision making process. By increasing involvement of patients in the clinical decision-making process, IDM/SDM places more of the responsibility for a complex decision on the patient. Research suggests, however, that patients are not well-informed of the harms and benefits associated with prostate cancer screening and are also subject to an assortment of biases, emotion, fears, and irrational thought that interferes with making an informed decision. In response, the IDM/SDM approaches can be augmented with strategies from the philosophy of libertarian paternalism (LP) to improve decision making. LP uses the insights of behavioural economics to help people better make better choices. Some of the main strategies of LP applicable to PSA decision making are a default decision rule, framing of decision aids, and timing of the decision. In this paper, we propose that applying strategies from libertarian paternalism can help with PSA screening decision-making. Summary Our proposal to augment IDM and SDM approaches with libertarian paternalism strategies is intended to guide patients toward a better decision about testing while maintaining personal freedom of choice. While PSA screening remains controversial and evidence conflicting, a libertarian-paternalism influenced approach to decision making can help prevent the overdiagnosis and overtreatment of prostate cancer. PMID:21510865

Applying strategies from libertarian paternalism to decision making for prostate specific antigen (PSA) screening.

PubMed

Wheeler, David C; Szymanski, Konrad M; Black, Amanda; Nelson, David E

2011-04-21

Despite the recent publication of results from two randomized clinical trials, prostate specific antigen (PSA) screening for prostate cancer remains a controversial issue. There is lack of agreement across studies that PSA screening significantly reduces prostate cancer mortality. In spite of these facts, the widespread use of PSA testing in the United States leads to overdetection and overtreatment of clinically indolent prostate cancer, and its associated harms of incontinence and impotence. Given the inconclusive results from clinical trials and incongruent PSA screening guidelines, the decision to screen for prostate cancer with PSA testing is an uncertain one for patients and health care providers. Screening guidelines from some health organizations recommend an informed decision making (IDM) or shared decision making (SDM) approach for deciding on PSA screening. These approaches aim to empower patients to choose among the available options by making them active participants in the decision making process. By increasing involvement of patients in the clinical decision-making process, IDM/SDM places more of the responsibility for a complex decision on the patient. Research suggests, however, that patients are not well-informed of the harms and benefits associated with prostate cancer screening and are also subject to an assortment of biases, emotion, fears, and irrational thought that interferes with making an informed decision. In response, the IDM/SDM approaches can be augmented with strategies from the philosophy of libertarian paternalism (LP) to improve decision making. LP uses the insights of behavioural economics to help people better make better choices. Some of the main strategies of LP applicable to PSA decision making are a default decision rule, framing of decision aids, and timing of the decision. In this paper, we propose that applying strategies from libertarian paternalism can help with PSA screening decision-making. Our proposal to augment IDM and SDM approaches with libertarian paternalism strategies is intended to guide patients toward a better decision about testing while maintaining personal freedom of choice. While PSA screening remains controversial and evidence conflicting, a libertarian-paternalism influenced approach to decision making can help prevent the overdiagnosis and overtreatment of prostate cancer.

Evaluation of RxNorm for Medication Clinical Decision Support.

PubMed

Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G

2014-01-01

We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS.

Evaluation of RxNorm for Medication Clinical Decision Support

PubMed Central

Freimuth, Robert R.; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G.

2014-01-01

We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS. PMID:25954360

Wisdom in clinical reasoning and medical practice.

PubMed

Edmondson, Ricca; Pearce, Jane; Woerner, Markus H

2009-01-01

Exploring informal components of clinical reasoning, we argue that they need to be understood via the analysis of professional wisdom. Wise decisions are needed where action or insight is vital, but neither everyday nor expert knowledge provides solutions. Wisdom combines experiential, intellectual, ethical, emotional and practical capacities; we contend that it is also more strongly social than is usually appreciated. But many accounts of reasoning specifically rule out such features as irrational. Seeking to illuminate how wisdom operates, we therefore build on Aristotle's work on informal reasoning. His account of rhetorical communication shows how non-formal components can play active parts in reasoning, retaining, or even enhancing its reasonableness. We extend this account, applying it to forms of healthcare-related reasoning which are characterised by the need for wise decision-making. We then go on to explore some of what clinical wise reasoning may mean, concluding with a case taken from psychotherapeutic practice.

Clinical Decision Support Knowledge Management: Strategies for Success.

PubMed

Khalifa, Mohamed; Alswailem, Osama

2015-01-01

Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

14 CFR 16.227 - Standard of proof.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...

14 CFR 16.227 - Standard of proof.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...

14 CFR 16.227 - Standard of proof.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...

14 CFR 16.227 - Standard of proof.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Standard of proof. 16.227 Section 16.227 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES RULES OF... hearing officer shall issue an initial decision or shall rule in a party's favor only if the decision or...

EDRN Breast and Ovary Cancer CVC, Study 2: Phase 3 retrospective validation of ovarian cancer early detection markers in serial preclinical samples from the PLCO trial — EDRN Public Portal

Cancer.gov

Over 70% of women with ovarian/fallopian tube cancer (OC) are diagnosed with advanced stage disease which has a 5-year relative survival rate of 30%. Five-year survival is 90% when disease is confined to the ovaries, but overall survival is poor because only 25% of cases are found early. Screening for ovarian cancer using tools with high sensitivity is potentially cost-effective, but because OC is so rare, very high specificity is needed to achieve an acceptable PPV. We have conducted preliminary work both in clinical and in preclinical (CARET) samples. We have identified candidate markers, developed assays for novel markers including HE4 and MSLN, and evaluated their diagnostic performance. We evaluated the markers’ contribution to a diagnostic panel in a standard set in order to identify the best of the candidates and developed methods for combining markers to define a decision rule for a marker panel. We found that our PEB rule yields comparable performance to the Single Threshold (ST) rule 2 years earlier, using the same two markers. The PEB makes an even larger contribution with the 4-marker panel. The 4-marker panel with the PEB rule represents a substantial improvement over any of the other decision rules as a first-line screen to select women for imaging. Our goal in the proposed work is to estimate the improvement in performance possible in the PLCO serial samples.

A simple threshold rule is sufficient to explain sophisticated collective decision-making.

PubMed

Robinson, Elva J H; Franks, Nigel R; Ellis, Samuel; Okuda, Saki; Marshall, James A R

2011-01-01

Decision-making animals can use slow-but-accurate strategies, such as making multiple comparisons, or opt for simpler, faster strategies to find a 'good enough' option. Social animals make collective decisions about many group behaviours including foraging and migration. The key to the collective choice lies with individual behaviour. We present a case study of a collective decision-making process (house-hunting ants, Temnothorax albipennis), in which a previously proposed decision strategy involved both quality-dependent hesitancy and direct comparisons of nests by scouts. An alternative possible decision strategy is that scouting ants use a very simple quality-dependent threshold rule to decide whether to recruit nest-mates to a new site or search for alternatives. We use analytical and simulation modelling to demonstrate that this simple rule is sufficient to explain empirical patterns from three studies of collective decision-making in ants, and can account parsimoniously for apparent comparison by individuals and apparent hesitancy (recruitment latency) effects, when available nests differ strongly in quality. This highlights the need to carefully design experiments to detect individual comparison. We present empirical data strongly suggesting that best-of-n comparison is not used by individual ants, although individual sequential comparisons are not ruled out. However, by using a simple threshold rule, decision-making groups are able to effectively compare options, without relying on any form of direct comparison of alternatives by individuals. This parsimonious mechanism could promote collective rationality in group decision-making.

Inside the black box: starting to uncover the underlying decision rules used in one-by-one expert assessment of occupational exposure in case-control studies

PubMed Central

Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Yu, Kai; Shortreed, Susan M.; Pronk, Anjoeka; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Silverman, Debra T.; Friesen, Melissa C.

2014-01-01

Objectives Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participants' reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time-consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review, and future use of these expert-based exposure decisions. Methods Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity, and frequency. Data were split into training (n=10,488 jobs), testing (n=2,247), and validation (n=2,248) data sets. Results The CART and random forest models' predictions agreed with 92–94% of the expert's binary probability assignments. For ordinal probability, intensity, and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86–90% and 57–85%, respectively) than for low or medium exposed jobs (7–71%). Conclusions CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent and creates a mechanism to efficiently replicate exposure decisions in future studies. PMID:23155187

Validation of consensus panel diagnosis in dementia.

PubMed

Gabel, Matthew J; Foster, Norman L; Heidebrink, Judith L; Higdon, Roger; Aizenstein, Howard J; Arnold, Steven E; Barbas, Nancy R; Boeve, Bradley F; Burke, James R; Clark, Christopher M; Dekosky, Steven T; Farlow, Martin R; Jagust, William J; Kawas, Claudia H; Koeppe, Robert A; Leverenz, James B; Lipton, Anne M; Peskind, Elaine R; Turner, R Scott; Womack, Kyle B; Zamrini, Edward Y

2010-12-01

The clinical diagnosis of dementing diseases largely depends on the subjective interpretation of patient symptoms. Consensus panels are frequently used in research to determine diagnoses when definitive pathologic findings are unavailable. Nevertheless, research on group decision making indicates that many factors can adversely affect panel performance. To determine conditions that improve consensus panel diagnosis. Comparison of neuropathologic diagnoses with individual and consensus panel diagnoses based on clinical scenarios only, fludeoxyglucose F 18 positron emission tomography images only, and scenarios plus images. Expert and trainee individual and consensus panel deliberations using a modified Delphi method in a pilot research study of the diagnostic utility of fludeoxyglucose F 18 positron emission tomography. Forty-five patients with pathologically confirmed Alzheimer disease or frontotemporal dementia. Statistical measures of diagnostic accuracy, agreement, and confidence for individual raters and panelists before and after consensus deliberations. The consensus protocol using trainees and experts surpassed the accuracy of individual expert diagnoses when clinical information elicited diverse judgments. In these situations, consensus was 3.5 times more likely to produce positive rather than negative changes in the accuracy and diagnostic certainty of individual panelists. A rule that forced group consensus was at least as accurate as majority and unanimity rules. Using a modified Delphi protocol to arrive at a consensus diagnosis is a reasonable substitute for pathologic information. This protocol improves diagnostic accuracy and certainty when panelist judgments differ and is easily adapted to other research and clinical settings while avoiding the potential pitfalls of group decision making.

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision was made. Unique to this work is the fuzzy set representation of the conditions or attributes upon which the decision make may base his fuzzy set decision. From our examples, we infer certain and possible rules containing fuzzy terms. It should be stressed that the procedure determines how closely the expert follows the conditions under consideration in making his decision. We offer two examples pertaining to the possible decision to close a customer service center of a public utility company. In the first example, the decision maker does not follow too closely the conditions. In the second example, the conditions are much more relevant to the decision of the expert.

Oregon Supreme Court Ruling Prohibits Hospital from Refusing a Sell Order.

PubMed

Chien, Joseph; Mobbs, Karl E

2016-03-01

In a recent decision involving a capital murder case, Oregon State Hospital v. Butts, the Oregon Supreme Court conducted a mandamus hearing to ascertain whether Oregon State Hospital (OSH) had a legal duty to comply with a Sell order from a county trial court to provide antipsychotic medications to an incompetent defendant, despite its belief, as an institution, that medication was not clinically indicated. The case is reviewed and important implications, including the court's being granted the ability to circumvent the medical decision-making process, are discussed. © 2016 American Academy of Psychiatry and the Law.

Boosting standard order sets utilization through clinical decision support.

PubMed

Li, Haomin; Zhang, Yinsheng; Cheng, Haixia; Lu, Xudong; Duan, Huilong

2013-01-01

Well-designed standard order sets have the potential to integrate and coordinate care by communicating best practices through multiple disciplines, levels of care, and services. However, there are several challenges which certainly affected the benefits expected from standard order sets. To boost standard order sets utilization, a problem-oriented knowledge delivery solution was proposed in this study to facilitate access of standard order sets and evaluation of its treatment effect. In this solution, standard order sets were created along with diagnostic rule sets which can trigger a CDS-based reminder to help clinician quickly discovery hidden clinical problems and corresponding standard order sets during ordering. Those rule set also provide indicators for targeted evaluation of standard order sets during treatment. A prototype system was developed based on this solution and will be presented at Medinfo 2013.

Heuristic reasoning and cognitive biases: Are they hindrances to judgments and decision making in orthodontics?

PubMed

Hicks, E Preston; Kluemper, G Thomas

2011-03-01

Studies show that our brains use 2 modes of reasoning: heuristic (intuitive, automatic, implicit processing) and analytic (deliberate, rule-based, explicit processing). The use of intuition often dominates problem solving when innovative, creative thinking is required. Under conditions of uncertainty, we default to an even greater reliance on the heuristic processing. In health care settings and other such environments of increased importance, this mode becomes problematic. Since choice heuristics are quickly constructed from fragments of memory, they are often biased by prior evaluations of and preferences for the alternatives being considered. Therefore, a rigorous and systematic decision process notwithstanding, clinical judgments under uncertainty are often flawed by a number of unwitting biases. Clinical orthodontics is as vulnerable to this fundamental failing in the decision-making process as any other health care discipline. Several of the more common cognitive biases relevant to clinical orthodontics are discussed in this article. By raising awareness of these sources of cognitive errors in our clinical decision making, our intent was to equip the clinician to take corrective action to avoid them. Our secondary goal was to expose this important area of empirical research and encourage those with expertise in the cognitive sciences to explore, through further research, the possible relevance and impact of cognitive heuristics and biases on the accuracy of orthodontic judgments and decision making. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Computer-aided diagnostic strategy selection.

PubMed

Greenes, R A

1986-03-01

Determination of the optimal diagnostic work-up strategy for the patient is becoming a major concern for the practicing physician. Overlap of the indications for various diagnostic procedures, differences in their invasiveness or risk, and high costs have made physicians aware of the need to consider the choice of procedure carefully, as well as its relation to management actions available. In this article, the author discusses research approaches that aim toward development of formal decision analytic methods to allow the physician to determine optimal strategy; clinical algorithms or rules as guides to physician decisions; improved measures for characterizing the performance of diagnostic tests; educational tools for increasing the familiarity of physicians with the concepts underlying these measures and analytic procedures; and computer-based aids for facilitating the employment of these resources in actual clinical practice.

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

14 CFR 302.607 - Decision by administrative law judge.

Code of Federal Regulations, 2014 CFR

2014-01-01

... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...

14 CFR 302.607 - Decision by administrative law judge.

Code of Federal Regulations, 2013 CFR

2013-01-01

... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...

14 CFR 302.607 - Decision by administrative law judge.

Code of Federal Regulations, 2010 CFR

2010-01-01

... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...

14 CFR 302.607 - Decision by administrative law judge.

Code of Federal Regulations, 2011 CFR

2011-01-01

... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...

14 CFR 302.607 - Decision by administrative law judge.

Code of Federal Regulations, 2012 CFR

2012-01-01

... (AVIATION PROCEEDINGS) PROCEDURAL REGULATIONS RULES OF PRACTICE IN PROCEEDINGS Rules Applicable to... judge shall issue a decision recommending a disposition of a complaint or request for determination...

Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care.

PubMed

Aerts, Marc; Minalu, Girma; Bösner, Stefan; Buntinx, Frank; Burnand, Bernard; Haasenritter, Jörg; Herzig, Lilli; Knottnerus, J André; Nilsson, Staffan; Renier, Walter; Sox, Carol; Sox, Harold; Donner-Banzhoff, Norbert

2017-01-01

To construct a clinical prediction rule for coronary artery disease (CAD) presenting with chest pain in primary care. Meta-Analysis using 3,099 patients from five studies. To identify candidate predictors, we used random forest trees, multiple imputation of missing values, and logistic regression within individual studies. To generate a prediction rule on the pooled data, we applied a regression model that took account of the differing standard data sets collected by the five studies. The most parsimonious rule included six equally weighted predictors: age ≥55 (males) or ≥65 (females) (+1); attending physician suspected a serious diagnosis (+1); history of CAD (+1); pain brought on by exertion (+1); pain feels like "pressure" (+1); pain reproducible by palpation (-1). CAD was considered absent if the prediction score is <2. The area under the ROC curve was 0.84. We applied this rule to a study setting with a CAD prevalence of 13.2% using a prediction score cutoff of <2 (i.e., -1, 0, or +1). When the score was <2, the probability of CAD was 2.1% (95% CI: 1.1-3.9%); when the score was ≥ 2, it was 43.0% (95% CI: 35.8-50.4%). Clinical prediction rules are a key strategy for individualizing care. Large data sets based on electronic health records from diverse sites create opportunities for improving their internal and external validity. Our patient-level meta-analysis from five primary care sites should improve external validity. Our strategy for addressing site-to-site systematic variation in missing data should improve internal validity. Using principles derived from decision theory, we also discuss the problem of setting the cutoff prediction score for taking action. Copyright © 2016 Elsevier Inc. All rights reserved.

Understanding Decision-Making, Communication Rules, and Communication Satisfaction as Culture: Implications for Organizational Effectiveness.

ERIC Educational Resources Information Center

Shockley-Zalabak, Pamela

A study of decision making processes and communication rules, in a corporate setting undergoing change as a result of organizational ineffectiveness, examined whether (1) decisions about formal communication reporting systems were linked to management assumptions about technical creativity/effectiveness, (2) assumptions about…

38 CFR 20.1401 - Rule 1401. Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2012-07-01 2012-07-01 false Rule 1401. Definitions... Unmistakable Error § 20.1401 Rule 1401. Definitions. (a) Issue. Unless otherwise specified, the term “issue” in this subpart means a matter upon which the Board made a final decision (other than a decision under...

38 CFR 20.1401 - Rule 1401. Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2011-07-01 2011-07-01 false Rule 1401. Definitions... Unmistakable Error § 20.1401 Rule 1401. Definitions. (a) Issue. Unless otherwise specified, the term “issue” in this subpart means a matter upon which the Board made a final decision (other than a decision under...

38 CFR 20.1401 - Rule 1401. Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 2 2014-07-01 2014-07-01 false Rule 1401. Definitions... Unmistakable Error § 20.1401 Rule 1401. Definitions. (a) Issue. Unless otherwise specified, the term “issue” in this subpart means a matter upon which the Board made a final decision (other than a decision under...

External Validation of the PECARN Head Trauma Prediction Rules in Japan.

PubMed

Ide, Kentaro; Uematsu, Satoko; Tetsuhara, Kenichi; Yoshimura, Satoshi; Kato, Takahiro; Kobayashi, Tohru

2017-03-01

The Pediatric Emergency Care Applied Research Network (PECARN) head trauma prediction rules are used to assist computed tomography (CT) decision-making for children with minor head trauma. Although the PECARN rules have been validated in North America and Europe, they have not yet been validated in Asia. In Japan, there are no clinical decision rules for children with minor head trauma. The rate of head CT for children with minor head trauma in Japan is high since CT is widely accessible across the country. The objective of this study was to evaluate the diagnostic accuracy of the PECARN rules for identifying clinically important traumatic brain injuries (ciTBI) in children with minor head trauma in Japan. We conducted a retrospective cohort study at a tertiary care pediatric hospital in Japan (30,000 patients/year). We enrolled all children younger than 18 years with minor head trauma (Glasgow Coma Scale ≥ 14) who presented to the emergency department within 24 hours of their injury between January and December 2013. We retrospectively classified the children into three risk categories according to the PECARN rules. The PECARN rules were considered negative when children were classified into the very-low-risk category. The primary outcome was considered positive when a child had ciTBI defined as head injury resulting in death, neurosurgery, intubation for > 24 hours, or hospital admission ≥ 2 nights with evidence of TBI on CT. Among 2,208 children included in the study, 24 (1.1%) had ciTBI. Sensitivities and specificities of the PECARN rules to predict ciTBI were 85.7% (12/14; 95% confidence interval [CI] = 57.2 to 98.2) and 73.5% (572/778; 95% CI = 70.3 to 76.6), respectively, for children < 2 years old, and 100% (10/10; 95% CI = 58.7 to 100) and 73.5% (1033/1406; 95% CI = 71.0 to 75.7) for children ≥ 2 years old, respectively. There were 10 cases of physically abused children < 2 years old, and six (60%) of them had ciTBI. Also, two cases of physically abused children with ciTBI were classified as very low risk. If we did not include physically abused children, the sensitivity of the PECARN rule for children < 2 years old improved from 85.7% to 100% (8/8). The PECARN rules were less sensitive for physically abused children, although the rules showed excellent applicability for the cohort without physical abuse. Thoughtful consideration may be needed for cases of nonaccidental trauma. Further prospective studies are required to verify the applicability of the PECARN rules for children with minor head trauma in Japan. © 2016 by the Society for Academic Emergency Medicine.

Prediction of risk of recurrence of venous thromboembolism following treatment for a first unprovoked venous thromboembolism: systematic review, prognostic model and clinical decision rule, and economic evaluation.

PubMed

Ensor, Joie; Riley, Richard D; Jowett, Sue; Monahan, Mark; Snell, Kym Ie; Bayliss, Susan; Moore, David; Fitzmaurice, David

2016-02-01

Unprovoked first venous thromboembolism (VTE) is defined as VTE in the absence of a temporary provoking factor such as surgery, immobility and other temporary factors. Recurrent VTE in unprovoked patients is highly prevalent, but easily preventable with oral anticoagulant (OAC) therapy. The unprovoked population is highly heterogeneous in terms of risk of recurrent VTE. The first aim of the project is to review existing prognostic models which stratify individuals by their recurrence risk, therefore potentially allowing tailored treatment strategies. The second aim is to enhance the existing research in this field, by developing and externally validating a new prognostic model for individual risk prediction, using a pooled database containing individual patient data (IPD) from several studies. The final aim is to assess the economic cost-effectiveness of the proposed prognostic model if it is used as a decision rule for resuming OAC therapy, compared with current standard treatment strategies. Standard systematic review methodology was used to identify relevant prognostic model development, validation and cost-effectiveness studies. Bibliographic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched using terms relating to the clinical area and prognosis. Reviewing was undertaken by two reviewers independently using pre-defined criteria. Included full-text articles were data extracted and quality assessed. Critical appraisal of included full texts was undertaken and comparisons made of model performance. A prognostic model was developed using IPD from the pooled database of seven trials. A novel internal-external cross-validation (IECV) approach was used to develop and validate a prognostic model, with external validation undertaken in each of the trials iteratively. Given good performance in the IECV approach, a final model was developed using all trials data. A Markov patient-level simulation was used to consider the economic cost-effectiveness of using a decision rule (based on the prognostic model) to decide on resumption of OAC therapy (or not). Three full-text articles were identified by the systematic review. Critical appraisal identified methodological and applicability issues; in particular, all three existing models did not have external validation. To address this, new prognostic models were sought with external validation. Two potential models were considered: one for use at cessation of therapy (pre D-dimer), and one for use after cessation of therapy (post D-dimer). Model performance measured in the external validation trials showed strong calibration performance for both models. The post D-dimer model performed substantially better in terms of discrimination (c = 0.69), better separating high- and low-risk patients. The economic evaluation identified that a decision rule based on the final post D-dimer model may be cost-effective for patients with predicted risk of recurrence of over 8% annually; this suggests continued therapy for patients with predicted risks ≥ 8% and cessation of therapy otherwise. The post D-dimer model performed strongly and could be useful to predict individuals' risk of recurrence at any time up to 2-3 years, thereby aiding patient counselling and treatment decisions. A decision rule using this model may be cost-effective for informing clinical judgement and patient opinion in treatment decisions. Further research may investigate new predictors to enhance model performance and aim to further externally validate to confirm performance in new, non-trial populations. Finally, it is essential that further research is conducted to develop a model predicting bleeding risk on therapy, to manage the balance between the risks of recurrence and bleeding. This study is registered as PROSPERO CRD42013003494. The National Institute for Health Research Health Technology Assessment programme.

Clinical Decision Rules for Pulmonary Embolism in Hospitalized Patients: A Systematic Literature Review and Meta-analysis.

PubMed

Bass, Anne R; Fields, Kara G; Goto, Rie; Turissini, Gregory; Dey, Shirin; Russell, Linda A

2017-11-01

Background  Clinical decision rules (CDRs) for pulmonary embolism (PE) have been validated in outpatients, but their performance in hospitalized patients is not well characterized. Objectives  The goal of this systematic literature review was to assess the performance of CDRs for PE in hospitalized patients. Methods  We performed a structured literature search using Medline, EMBASE and the Cochrane library for articles published on or before January 18, 2017. Two authors reviewed all titles, abstracts and full texts. We selected prospective studies of symptomatic hospitalized patients in which a CDR was used to estimate the likelihood of PE. The diagnosis of PE had to be confirmed using an accepted reference standard. Data on hospitalized patients were solicited from authors of studies in mixed populations of outpatients and hospitalized patients. Study characteristics, PE prevalence and CDR performance were extracted. The methodological quality of the studies was assessed using the QUADAS instrument. Results  Twelve studies encompassing 3,942 hospitalized patients were included. Studies varied in methodology (randomized controlled trials and observational studies) and reference standards used. The pooled sensitivity of the modified Wells rule (cut-off ≤ 4) in hospitalized patients was 72.1% (95% confidence interval [CI], 63.7-79.2) and the pooled specificity was 62.2% (95% CI, 52.6-70.9). The modified Wells rule (cut-off ≤ 4) plus D-dimer testing had a pooled sensitivity 99.7% (95% CI, 96.7-100) and pooled specificity 10.8% (95% CI, 6.7-16.9). The efficiency (proportion of patients stratified into the 'PE unlikely' group) was 8.4% (95% CI, 4.1-16.5), and the failure rate (proportion of low likelihood patients who were diagnosed with PE during follow-up) was 0.1% (95% CI, 0-5.3). Conclusion  In symptomatic hospitalized patients, use of the Wells rule plus D-dimer to rule out PE is safe, but allows very few patients to forgo imaging. Schattauer GmbH Stuttgart.

Imaging utilization commentary: a radiology perspective.

PubMed

Reed, Martin H

2008-11-01

To adhere to the ALARA concept, imaging should be limited to studies that actually contribute to the management of the patient. For example, by applying the Ottawa Ankle Rule and the Ottawa Knee Rule, fewer radiographs are required to evaluate ankle and knee trauma in children. Chest radiographs usually do not contribute to the management of children presenting with typical acute bronchiolitis or asthma, and they can be detrimental because consolidation resulting from retained secretions is interpreted as pneumonia and the child is started on antibiotics unnecessarily. Moreover, a radiograph of the abdomen has poor validity and reproducibility for the diagnosis of constipation. The Pediatric Emergency Care Applied Research Network (PECARN) and the Pediatric Emergency Research in Canada (PERC) are currently developing decision rules for the use of CT in the assessment of minor head injuries in children, which should reduce its utilization in this condition. PECARN is also developing a decision rule for the use of CT in the assessment of abdominal trauma in children. CT is frequently used for the diagnosis of appendicitis in children, but appendicitis can be diagnosed clinically. If imaging is required, appendicitis can often be diagnosed with US, and CT need only be used in the minority of cases where the diagnosis is still in doubt. Utilization guidelines for pediatric imaging studies obtained in children in the emergency setting can improve yield and help in the more efficient management of often scarce health care resources.

CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation.

PubMed

Whiffin, Nicola; Walsh, Roddy; Govind, Risha; Edwards, Matthew; Ahmad, Mian; Zhang, Xiaolei; Tayal, Upasana; Buchan, Rachel; Midwinter, William; Wilk, Alicja E; Najgebauer, Hanna; Francis, Catherine; Wilkinson, Sam; Monk, Thomas; Brett, Laura; O'Regan, Declan P; Prasad, Sanjay K; Morris-Rosendahl, Deborah J; Barton, Paul J R; Edwards, Elizabeth; Ware, James S; Cook, Stuart A

2018-01-25

PurposeInternationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier (http://www.cardioclassifier.org), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).MethodsCardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.ResultsWe benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher's P = 1.1  ×  10 -18 ), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.ConclusionCardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.GENETICS in MEDICINE advance online publication, 25 January 2018; doi:10.1038/gim.2017.258.

Gag rule is formally suspended as Title X renewal advances in House.

PubMed

1993-02-09

In February 1993, the US House of Representatives reintroduced a bill (HR 670) which was similar to an earlier bill introduced during the Bush Administration in late 1992 to override a Supreme Court decision upholding Reagan's executive order and vetoed by President Bush. This executive order restricted abortion counseling at federally funded clinics. Bill HR 670 clarified congressional intent of Title X. It also called for increased funding for Title X programs. The bill cleared the full Energy and Commerce Committee within 2 days. Family planning groups and the Clinton Administration strongly supported this bill. Acting Assistant Secretary for Health opposed a proposed restrictive parental notification amendment, however, which the full committee had defeated (18-25). The bill should have reached the Senate shortly after the winter recess. Also in February, the Clinton Administration suspended the Title X gag rule regulations implemented during the waning days of the Reagan Administration and upheld during the waning days of the Reagan Administration and upheld during the Bush Administration. The Clinton Administration did so by issuing an interim rule which returned oversight of federally supported family planning clinics to previous regulations and policies, e.g., US Department of Health and Human Services (DHHS) 1981 Program Guidelines for Family Planning Projects. It also issued a proposed rule which could become law after a 60-day comment period. Therefore the new rulings required federally supported clinics to provide nondirective counseling and abortion referrals upon request for women with unwanted pregnancies. DHHS' Office for Population Affairs continued to administer the Title X program.

How do community pharmacists make decisions? Results of an exploratory qualitative study in Ontario.

PubMed

Gregory, Paul A M; Whyte, Brenna; Austin, Zubin

2016-03-01

As the complexity of pharmacy practice increases, pharmacists are required to make more decisions under ambiguous or information-deficient conditions. There is scant literature examining how pharmacists make decisions and what factors or values influence their choices. The objective of this exploratory research was to characterize decision-making patterns in the clinical setting of community pharmacists in Ontario. The think-aloud decision-making method was used for this study. Community pharmacists with 3 or more years' experience were presented with 2 clinical case studies dealing with challenging situations and were asked to verbally reason through their decision-making process while being probed by an interviewer for clarification, justification and further explication. Verbatim transcripts were analyzed using a protocol analysis method. A total of 12 pharmacists participated in this study. Participants experienced cognitive dissonance in attempting to reconcile their desire for a clear and confrontation-free conclusion to the case discussion and the reality of the challenge presented within each case. Strategies for resolving this cognitive dissonance included strong emphasis on the educational (rather than decision-making) role of the pharmacist, the value of strong interpersonal relationships as a way to avoid conflict and achieve desired outcomes, the desire to seek external advice or defer to others' authority to avoid making a decision and the use of strict interpretations of rules to avoid ambiguity and contextual interpretation. This research was neither representative nor generalizable but was indicative of patterns of decisional avoidance and fear of assuming responsibility for outcomes that warrant further investigation. The think-aloud method functioned effectively in this context and provided insights into pharmacists' decision-making patterns in the clinical setting. Can Pharm J (Ott) 2016;149:90-98.

Clean Air Interstate Rule: Changes and Modeling in AEO2010 (released in AEO2010)

EIA Publications

2010-01-01

On December 23, 2008, the D.C. Circuit Court remanded but did not vacate the Clean Air Interstate Rule (CAIR), overriding its previous decision on February 8, 2008, to remand and vacate CAIR. The December decision, which is reflected in Annual Energy Outlook 2010 (AEO) , allows CAIR to remain in effect, providing time for the Environmental Protection Agency to modify the rule in order to address objections raised by the Court in its earlier decision. A similar rule, referred to as the Clean Air Mercury Rule (CAMR), which was to set up a cap-and-trade system for reducing mercury emissions by approximately 70%, is not represented in the AEO2010 projections, because it was vacated by the D.C. Circuit Court in February 2008.

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

18 CFR 385.2201 - Rules governing off-the-record communications (Rule 2201).

Code of Federal Regulations, 2010 CFR

2010-04-01

...) Relevant to the merits means capable of affecting the outcome of a proceeding, or of influencing a decision, or providing an opportunity to influence a decision, on any issue in the proceeding, but does not... Commission in a manner that permits fully informed decision making by the Commission while ensuring the...

18 CFR 385.704 - Rights of participants before initial decision (Rule 704).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Rights of participants... PROCEDURE Decisions § 385.704 Rights of participants before initial decision (Rule 704). After testimony is... good cause, deny opportunity for reply or limit the issues which may be addressed in any reply. ...

17 CFR 201.410 - Appeal of initial decisions by hearing officers.

Code of Federal Regulations, 2010 CFR

2010-04-01

... COMMISSION RULES OF PRACTICE Rules of Practice Appeal to the Commission and Commission Review § 201.410 Appeal of initial decisions by hearing officers. (a) Petition for review; when available. In any... would have been entitled to judicial review of the decision entered therein if the Commission itself had...

Considerations of net present value in policy making regarding diagnostic and therapeutic technologies.

PubMed

Califf, Robert M; Rasiel, Emma B; Schulman, Kevin A

2008-11-01

The pharmaceutical and medical device industries function in a business environment in which shareholders expect companies to optimize profit within legal and ethical standards. A fundamental tool used to optimize decision making is the net present value calculation, which estimates the current value of cash flows relating to an investment. We examined 3 prototypical research investment decisions that have been the source of public scrutiny to illustrate how policy decisions can be better understood when their impact on societally desirable investments by industry are viewed from the standpoint of their impact on net present value. In the case of direct, comparative clinical trials, a simple net present value calculation provides insight into why companies eschew such investments. In the case of pediatric clinical trials, the Pediatric Extension Rule changed the net present value calculation from unattractive to potentially very attractive by allowing patent extensions; thus, the dramatic increase in pediatric clinical trials can be explained by the financial return on investment. In the case of products for small markets, the fixed costs of development make this option financially unattractive. Policy decisions can be better understood when their impact on societally desirable investments by the pharmaceutical and medical device industries are viewed from the standpoint of their impact on net present value.

Collective intelligence meets medical decision-making: the collective outperforms the best radiologist.

PubMed

Wolf, Max; Krause, Jens; Carney, Patricia A; Bogart, Andy; Kurvers, Ralf H J M

2015-01-01

While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules ("majority", "quorum", and "weighted quorum") when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.

Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings.

PubMed

Eken, Cenker; Bilge, Ugur; Kartal, Mutlu; Eray, Oktay

2009-06-03

Logistic regression is the most common statistical model for processing multivariate data in the medical literature. Artificial intelligence models like an artificial neural network (ANN) and genetic algorithm (GA) may also be useful to interpret medical data. The purpose of this study was to perform artificial intelligence models on a medical data sheet and compare to logistic regression. ANN, GA, and logistic regression analysis were carried out on a data sheet of a previously published article regarding patients presenting to an emergency department with flank pain suspicious for renal colic. The study population was composed of 227 patients: 176 patients had a diagnosis of urinary stone, while 51 ultimately had no calculus. The GA found two decision rules in predicting urinary stones. Rule 1 consisted of being male, pain not spreading to back, and no fever. In rule 2, pelvicaliceal dilatation on bedside ultrasonography replaced no fever. ANN, GA rule 1, GA rule 2, and logistic regression had a sensitivity of 94.9, 67.6, 56.8, and 95.5%, a specificity of 78.4, 76.47, 86.3, and 47.1%, a positive likelihood ratio of 4.4, 2.9, 4.1, and 1.8, and a negative likelihood ratio of 0.06, 0.42, 0.5, and 0.09, respectively. The area under the curve was found to be 0.867, 0.720, 0.715, and 0.713 for all applications, respectively. Data mining techniques such as ANN and GA can be used for predicting renal colic in emergency settings and to constitute clinical decision rules. They may be an alternative to conventional multivariate analysis applications used in biostatistics.

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

MICE or NICE? An economic evaluation of clinical decision rules in the diagnosis of heart failure in primary care.

PubMed

Monahan, Mark; Barton, Pelham; Taylor, Clare J; Roalfe, Andrea K; Hobbs, F D Richard; Cowie, Martin; Davis, Russell; Deeks, Jon; Mant, Jonathan; McCahon, Deborah; McDonagh, Theresa; Sutton, George; Tait, Lynda

2017-08-15

Detection and treatment of heart failure (HF) can improve quality of life and reduce premature mortality. However, symptoms such as breathlessness are common in primary care, have a variety of causes and not all patients require cardiac imaging. In systems where healthcare resources are limited, ensuring those patients who are likely to have HF undergo appropriate and timely investigation is vital. A decision tree was developed to assess the cost-effectiveness of using the MICE (Male, Infarction, Crepitations, Edema) decision rule compared to other diagnostic strategies to identify HF patients presenting to primary care. Data from REFER (REFer for EchocaRdiogram), a HF diagnostic accuracy study, was used to determine which patients received the correct diagnosis decision. The model adopted a UK National Health Service (NHS) perspective. The current recommended National Institute for Health and Care Excellence (NICE) guidelines for identifying patients with HF was the most cost-effective option with a cost of £4400 per quality adjusted life year (QALY) gained compared to a "do nothing" strategy. That is, patients presenting with symptoms suggestive of HF should be referred straight for echocardiography if they had a history of myocardial infarction or if their NT-proBNP level was ≥400pg/ml. The MICE rule was more expensive and less effective than the other comparators. Base-case results were robust to sensitivity analyses. This represents the first cost-utility analysis comparing HF diagnostic strategies for symptomatic patients. Current guidelines in England were the most cost-effective option for identifying patients for confirmatory HF diagnosis. The low number of HF with Reduced Ejection Fraction patients (12%) in the REFER patient population limited the benefits of early detection. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Designing Real-time Decision Support for Trauma Resuscitations

PubMed Central

Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.

2016-01-01

Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed. Results Among 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert–video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low. Conclusions An eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians. PMID:26300010

Use of radiography in acute knee injuries: need for clinical decision rules.

PubMed

Stiell, I G; Wells, G A; McDowell, I; Greenberg, G H; McKnight, R D; Cwinn, A A; Quinn, J V; Yeats, A

1995-11-01

To study: 1) the efficiency of the current use of radiography in acute knee injuries, 2) the judgments and attitudes of experienced clinicians in their use of knee radiography, and 3) the potential for decision rules to improve efficiency. This two-stage study of adults with acute knee injuries involved: 1) a retrospective review of all 1,967 patients seen over a 12-month period in the EDs of one community and two teaching hospital, and 2) a prospective survey of another 1,040 patients seen by attending emergency physicians. The prospective survey assessed each clinician's estimate of the probability of a knee or patella fracture; 120 patients were independently assessed by two physicians. Of the 1,967 patients seen in the first stage, 74.1% underwent radiography but only 5.2% were found to have fractures. Of the 1,727 knee and patella radiographic series ordered, 92.4% were negative for fracture. In the second stage, experienced physicians predicted the probability of fracture to be 0 or 0.1 for 75.6% of the patients. The kappa value for this response was 0.51 (95% CI 0.34 to 0.68). The physicians also indicated that they would have been comfortable or very comfortable in not ordering radiography for 55.5% of the patients. The area under the receiver operating characteristics curve for the physicians' prediction of fracture was 0.87 (95% CI 0.82 to 0.91), reflecting good discrimination between fracture and nonfracture cases. Likelihood ratios for the physicians' prediction ranged from 0.09 at the 0 level to 42.9 at the 0.9-1.0 level. Emergency physicians order radiography for most patients with acute knee injuries, even though they can accurately discriminate between fracture and nonfracture cases and expect most of the radiographs to be normal. These findings suggest great potential for more efficient use of knee radiography, possibly through the use of a clinical decision rule.

The cost-effectiveness of diagnostic management strategies for adults with minor head injury.

PubMed

Holmes, M W; Goodacre, S; Stevenson, M D; Pandor, A; Pickering, A

2012-09-01

To estimate the cost-effectiveness of diagnostic management strategies for adults with minor head injury. A mathematical model was constructed to evaluate the incremental costs and effectiveness (Quality Adjusted Life years Gained, QALYs) of ten diagnostic management strategies for adults with minor head injuries. Secondary analyses were undertaken to determine the cost-effectiveness of hospital admission compared to discharge home and to explore the cost-effectiveness of strategies when no responsible adult was available to observe the patient after discharge. The apparent optimal strategy was based on the high and medium risk Canadian CT Head Rule (CCHRhm), although the costs and outcomes associated with each strategy were broadly similar. Hospital admission for patients with non-neurosurgical injury on CT dominated discharge home, whilst hospital admission for clinically normal patients with a normal CT was not cost-effective compared to discharge home with or without a responsible adult at £39 and £2.5 million per QALY, respectively. A selective CT strategy with discharge home if the CT scan was normal remained optimal compared to not investigating or CT scanning all patients when there was no responsible adult available to observe them after discharge. Our economic analysis confirms that the recent extension of access to CT scanning for minor head injury is appropriate. Liberal use of CT scanning based on a high sensitivity decision rule is not only effective but also cost-saving. The cost of CT scanning is very small compared to the estimated cost of caring for patients with brain injury worsened by delayed treatment. It is recommended therefore that all hospitals receiving patients with minor head injury should have unrestricted access to CT scanning for use in conjunction with evidence based guidelines. Provisionally the CCHRhm decision rule appears to be the best strategy although there is considerable uncertainty around the optimal decision rule. However, the CCHRhm rule appears to be the most widely validated and it therefore seems appropriate to conclude that the CCHRhm rule has the best evidence to support its use. Copyright © 2011 Elsevier Ltd. All rights reserved.

Combining tabular, rule-based, and procedural knowledge in computer-based guidelines for childhood immunization.

PubMed

Miller, P L; Frawley, S J; Sayward, F G; Yasnoff, W A; Duncan, L; Fleming, D W

1997-06-01

IMM/Serve is a computer program which implements the clinical guidelines for childhood immunization. IMM/Serve accepts as input a child's immunization history. It then indicates which vaccinations are due and which vaccinations should be scheduled next. The clinical guidelines for immunization are quite complex and are modified quite frequently. As a result, it is important that IMM/Serve's knowledge be represented in a format that facilitates the maintenance of that knowledge as the field evolves over time. To achieve this goal, IMM/Serve uses four representations for different parts of its knowledge base: (1) Immunization forecasting parameters that specify the minimum ages and wait-intervals for each dose are stored in tabular form. (2) The clinical logic that determines which set of forecasting parameters applies for a particular patient in each vaccine series is represented using if-then rules. (3) The temporal logic that combines dates, ages, and intervals to calculate recommended dates, is expressed procedurally. (4) The screening logic that checks each previous dose for validity is performed using a decision table that combines minimum ages and wait intervals with a small amount of clinical logic. A knowledge maintenance tool, IMM/Def, has been developed to help maintain the rule-based logic. The paper describes the design of IMM/Serve and the rationale and role of the different forms of knowledge used.

Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

NASA Astrophysics Data System (ADS)

Wang, M.; Hu, N. Q.; Qin, G. J.

2011-07-01

In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

38 CFR 20.1106 - Rule 1106. Claim for death benefits by survivor-prior unfavorable decisions during veteran's...

Code of Federal Regulations, 2010 CFR

2010-07-01

... of 38 U.S.C. 6104 and 6105, issues involved in a survivor's claim for death benefits will be decided... death benefits by survivor-prior unfavorable decisions during veteran's lifetime. 20.1106 Section 20... VETERANS' APPEALS: RULES OF PRACTICE Finality § 20.1106 Rule 1106. Claim for death benefits by survivor...

48 CFR 6101.26 - Reconsideration; amendment of decisions; new hearings [Rule 26].

Code of Federal Regulations, 2012 CFR

2012-10-01

... in 6101.27(a) (Rule 27(a)) and the reasons established by the rules of common law or equity... for granting a new hearing. Upon granting a motion for a new hearing, the Board will take additional testimony and, if a decision has been issued, either amend its findings of fact and conclusions or law or...

77 FR 65137 - Consideration of Environmental Impacts of Temporary Storage of Spent Fuel After Cessation of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-25

... provide input to decision-making for updating the Waste Confidence Decision and Rule and would not involve... Commission's tentative planning and decision-making schedule; g. Identify any cooperating agencies and, as... #0;notices is to give interested persons an opportunity to participate in #0;the rule making prior to...

Order of Verdict Consideration and Decision Rule Effects on Mock Jury Decision Making.

ERIC Educational Resources Information Center

Olaye, Imafidon M.

A study investigated the effects of order verdict consideration and decision rule on jury verdicts. After reading the summary of an actual trial, 240 mock jurors drawn from undergraduate communications classes were randomly assigned to six-member juries. Jury assignments were made under two verdict orders (ascending and descending order of…

Logical-Rule Models of Classification Response Times: A Synthesis of Mental-Architecture, Random-Walk, and Decision-Bound Approaches

ERIC Educational Resources Information Center

Fific, Mario; Little, Daniel R.; Nosofsky, Robert M.

2010-01-01

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli…

78 FR 19424 - Service Rules for the 698-746, 747-762 and 777-792 MHz Bands; Revision of the Commission's Rules...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-01

... Reconsideration (MO&O) denies or dismisses petitions seeking reconsideration of certain decisions made by the Commission in the 700 MHz Second Report and Order, relating to the 698-806 MHz Band, including decisions..., public safety narrowband relocation procedures, and the decisions not to impose wholesale requirements...

Acute asthma severity identification of expert system flow in emergency department

NASA Astrophysics Data System (ADS)

Sharif, Nurul Atikah Mohd; Ahmad, Norazura; Ahmad, Nazihah; Desa, Wan Laailatul Hanim Mat

2017-11-01

Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems.

PubMed

Szlosek, Donald A; Ferrett, Jonathan

2016-01-01

As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation. Modeled after the EMR system EPIC at Maine Medical Center, we developed a dummy data set containing physician notes in free text for 3,621 artificial patients records undergoing a head computed tomography (CT) scan for mild traumatic brain injury after the incorporation of an electronic best practice approach. We validated the accuracy of the Best Practice Advisories (BPA) using three machine learning algorithms-C-Support Vector Classification (SVC), Decision Tree Classifier (DecisionTreeClassifier), k-nearest neighbors classifier (KNeighborsClassifier)-by comparing their accuracy for adjudicating the occurrence of a mild traumatic brain injury against manual review. We then used the best of the three algorithms to evaluate the effectiveness of the BPA, and we compared the algorithm's evaluation of the BPA to that of manual review. The electronic best practice approach was found to have a sensitivity of 98.8 percent (96.83-100.0), specificity of 10.3 percent, PPV = 7.3 percent, and NPV = 99.2 percent when reviewed manually by abstractors. Though all the machine learning algorithms were observed to have a high level of prediction, the SVC displayed the highest with a sensitivity 93.33 percent (92.49-98.84), specificity of 97.62 percent (96.53-98.38), PPV = 50.00, NPV = 99.83. The SVC algorithm was observed to have a sensitivity of 97.9 percent (94.7-99.86), specificity 10.30 percent, PPV 7.25 percent, and NPV 99.2 percent for evaluating the best practice approach, after accounting for 17 cases (0.66 percent) where the patient records had to be reviewed manually due to the NPL systems inability to capture the proper diagnosis. CDSSs incorporated into EMRs can be evaluated in an automatic fashion by using NLP and machine learning techniques.

Mining the human genome after Association for Molecular Pathology v. Myriad Genetics

PubMed Central

Evans, Barbara J

2014-01-01

The Supreme Court's recent decision in Association for Molecular Pathology v. Myriad Genetics portrays the human genome as a product of nature. This frames medical genetics as an extractive industry that mines a natural resource to produce valuable goods and services. Natural resource law offers insights into problems medical geneticists can expect after this decision and suggests possible solutions. Increased competition among clinical laboratories offers various benefits but threatens to increase fragmentation of genetic data resources, potentially causing waste in the form of lost opportunities to discover the clinical significance of particular gene variants. The solution lies in addressing legal barriers to appropriate data sharing. Sustainable discovery in the field of medical genetics can best be achieved through voluntary data sharing rather than command-and-control tactics, but voluntary mechanisms must be conceived broadly to include market-based approaches as well as donative and publicly funded data commons. The recently revised Health Insurance Portability and Accountability Act Privacy Rule offers an improved—but still imperfect—framework for market-oriented data sharing. This article explores strategies for addressing the Privacy Rule's remaining defects. America is close to having a legal framework that can reward innovators, protect privacy, and promote needed data sharing to advance medical genetics. Genet Med 16 7, 504–509. PMID:24357850

Mining the human genome after Association for Molecular Pathology v. Myriad Genetics.

PubMed

Evans, Barbara J

2014-07-01

The Supreme Court's recent decision in Association for Molecular Pathology v. Myriad Genetics portrays the human genome as a product of nature. This frames medical genetics as an extractive industry that mines a natural resource to produce valuable goods and services. Natural resource law offers insights into problems medical geneticists can expect after this decision and suggests possible solutions. Increased competition among clinical laboratories offers various benefits but threatens to increase fragmentation of genetic data resources, potentially causing waste in the form of lost opportunities to discover the clinical significance of particular gene variants. The solution lies in addressing legal barriers to appropriate data sharing. Sustainable discovery in the field of medical genetics can best be achieved through voluntary data sharing rather than command-and-control tactics, but voluntary mechanisms must be conceived broadly to include market-based approaches as well as donative and publicly funded data commons. The recently revised Health Insurance Portability and Accountability Act Privacy Rule offers an improved--but still imperfect--framework for market-oriented data sharing. This article explores strategies for addressing the Privacy Rule's remaining defects. America is close to having a legal framework that can reward innovators, protect privacy, and promote needed data sharing to advance medical genetics.

Formalization of treatment guidelines using Fuzzy Cognitive Maps and semantic web tools.

PubMed

Papageorgiou, Elpiniki I; Roo, Jos De; Huszka, Csaba; Colaert, Dirk

2012-02-01

Therapy decision making and support in medicine deals with uncertainty and needs to take into account the patient's clinical parameters, the context of illness and the medical knowledge of the physician and guidelines to recommend a treatment therapy. This research study is focused on the formalization of medical knowledge using a cognitive process, called Fuzzy Cognitive Maps (FCMs) and semantic web approach. The FCM technique is capable of dealing with situations including uncertain descriptions using similar procedure such as human reasoning does. Thus, it was selected for the case of modeling and knowledge integration of clinical practice guidelines. The semantic web tools were established to implement the FCM approach. The knowledge base was constructed from the clinical guidelines as the form of if-then fuzzy rules. These fuzzy rules were transferred to FCM modeling technique and, through the semantic web tools, the whole formalization was accomplished. The problem of urinary tract infection (UTI) in adult community was examined for the proposed approach. Forty-seven clinical concepts and eight therapy concepts were identified for the antibiotic treatment therapy problem of UTIs. A preliminary pilot-evaluation study with 55 patient cases showed interesting findings; 91% of the antibiotic treatments proposed by the implemented approach were in fully agreement with the guidelines and physicians' opinions. The results have shown that the suggested approach formalizes medical knowledge efficiently and gives a front-end decision on antibiotics' suggestion for cystitis. Concluding, modeling medical knowledge/therapeutic guidelines using cognitive methods and web semantic tools is both reliable and useful. Copyright © 2011 Elsevier Inc. All rights reserved.

Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned.

PubMed

Press, Anne; McCullagh, Lauren; Khan, Sundas; Schachter, Andy; Pardo, Salvatore; McGinn, Thomas

2015-09-10

As the electronic health record (EHR) becomes the preferred documentation tool across medical practices, health care organizations are pushing for clinical decision support systems (CDSS) to help bring clinical decision support (CDS) tools to the forefront of patient-physician interactions. A CDSS is integrated into the EHR and allows physicians to easily utilize CDS tools. However, often CDSS are integrated into the EHR without an initial phase of usability testing, resulting in poor adoption rates. Usability testing is important because it evaluates a CDSS by testing it on actual users. This paper outlines the usability phase of a study, which will test the impact of integration of the Wells CDSS for pulmonary embolism (PE) diagnosis into a large urban emergency department, where workflow is often chaotic and high stakes decisions are frequently made. We hypothesize that conducting usability testing prior to integration of the Wells score into an emergency room EHR will result in increased adoption rates by physicians. The objective of the study was to conduct usability testing for the integration of the Wells clinical prediction rule into a tertiary care center's emergency department EHR. We conducted usability testing of a CDS tool in the emergency department EHR. The CDS tool consisted of the Wells rule for PE in the form of a calculator and was triggered off computed tomography (CT) orders or patients' chief complaint. The study was conducted at a tertiary hospital in Queens, New York. There were seven residents that were recruited and participated in two phases of usability testing. The usability testing employed a "think aloud" method and "near-live" clinical simulation, where care providers interacted with standardized patients enacting a clinical scenario. Both phases were audiotaped, video-taped, and had screen-capture software activated for onscreen recordings. Phase I: Data from the "think-aloud" phase of the study showed an overall positive outlook on the Wells tool in assessing a patient for a PE diagnosis. Subjects described the tool as "well-organized" and "better than clinical judgment". Changes were made to improve tool placement into the EHR to make it optimal for decision-making, auto-populating boxes, and minimizing click fatigue. Phase II: After incorporating the changes noted in Phase 1, the participants noted tool improvements. There was less toggling between screens, they had all the clinical information required to complete the tool, and were able to complete the patient visit efficiently. However, an optimal location for triggering the tool remained controversial. This study successfully combined "think-aloud" protocol analysis with "near-live" clinical simulations in a usability evaluation of a CDS tool that will be implemented into the emergency room environment. Both methods proved useful in the assessment of the CDS tool and allowed us to refine tool usability and workflow.

Spontaneous Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis Describing the Diagnostic Accuracy of History, Physical Examination, Imaging, and Lumbar Puncture With an Exploration of Test Thresholds.

PubMed

Carpenter, Christopher R; Hussain, Adnan M; Ward, Michael J; Zipfel, Gregory J; Fowler, Susan; Pines, Jesse M; Sivilotti, Marco L A

2016-09-01

Spontaneous subarachnoid hemorrhage (SAH) is a rare, but serious etiology of headache. The diagnosis of SAH is especially challenging in alert, neurologically intact patients, as missed or delayed diagnosis can be catastrophic. The objective was to perform a diagnostic accuracy systematic review and meta-analysis of history, physical examination, cerebrospinal fluid (CSF) tests, computed tomography (CT), and clinical decision rules for spontaneous SAH. A secondary objective was to delineate probability of disease thresholds for imaging and lumbar puncture (LP). PubMed, Embase, Scopus, and research meeting abstracts were searched up to June 2015 for studies of emergency department patients with acute headache clinically concerning for spontaneous SAH. QUADAS-2 was used to assess study quality and, when appropriate, meta-analysis was conducted using random effects models. Outcomes were sensitivity, specificity, and positive (LR+) and negative (LR-) likelihood ratios. To identify test and treatment thresholds, we employed the Pauker-Kassirer method with Bernstein test indication curves using the summary estimates of diagnostic accuracy. A total of 5,022 publications were identified, of which 122 underwent full-text review; 22 studies were included (average SAH prevalence = 7.5%). Diagnostic studies differed in assessment of history and physical examination findings, CT technology, analytical techniques used to identify xanthochromia, and criterion standards for SAH. Study quality by QUADAS-2 was variable; however, most had a relatively low risk of biases. A history of neck pain (LR+ = 4.1; 95% confidence interval [CI] = 2.2 to 7.6) and neck stiffness on physical examination (LR+ = 6.6; 95% CI = 4.0 to 11.0) were the individual findings most strongly associated with SAH. Combinations of findings may rule out SAH, yet promising clinical decision rules await external validation. Noncontrast cranial CT within 6 hours of headache onset accurately ruled in (LR+ = 230; 95% CI = 6 to 8,700) and ruled out SAH (LR- = 0.01; 95% CI = 0 to 0.04); CT beyond 6 hours had a LR- of 0.07 (95% CI = 0.01 to 0.61). CSF analyses had lower diagnostic accuracy, whether using red blood cell (RBC) count or xanthochromia. At a threshold RBC count of 1,000 × 10(6) /L, the LR+ was 5.7 (95% CI = 1.4 to 23) and LR- was 0.21 (95% CI = 0.03 to 1.7). Using the pooled estimates of diagnostic accuracy and testing risks and benefits, we estimate that LP only benefits CT-negative patients when the pre-LP probability of SAH is on the order of 5%, which corresponds to a pre-CT probability greater than 20%. Less than one in 10 headache patients concerning for SAH are ultimately diagnosed with SAH in recent studies. While certain symptoms and signs increase or decrease the likelihood of SAH, no single characteristic is sufficient to rule in or rule out SAH. Within 6 hours of symptom onset, noncontrast cranial CT is highly accurate, while a negative CT beyond 6 hours substantially reduces the likelihood of SAH. LP appears to benefit relatively few patients within a narrow pretest probability range. With improvements in CT technology and an expanding body of evidence, test thresholds for LP may become more precise, obviating the need for a post-CT LP in more acute headache patients. Existing SAH clinical decision rules await external validation, but offer the potential to identify subsets most likely to benefit from post-CT LP, angiography, or no further testing. © 2016 by the Society for Academic Emergency Medicine.

Rejecting the Baby Doe rules and defending a "negative" analysis of the Best Interests Standard.

PubMed

Kopelman, Loretta M

2005-08-01

Two incompatible policies exist for guiding medical decisions for extremely premature, sick, or terminally ill infants, the Best Interests Standard and the newer, 20-year old "Baby Doe" Rules. The background, including why there were two sets of Baby Doe Rules, and their differences with the Best Interests Standard, are illustrated. Two defenses of the Baby Doe Rules are considered and rejected. The first, held by Reagan, Koop, and others, is a "right-to-life" defense. The second, held by some leaders of the American Academy of Pediatrics, is that the Baby Doe Rules are benign and misunderstood. The Baby Doe Rules should be rejected since they can thwart compassionate and individualized decision-making, undercut duties to minimize unnecessary suffering, and single out one group for treatment adults would not want for themselves. In these ways, they are inferior to the older Best Interests Standard. A "negative" analysis of the Best Interests Standard is articulated and defended for decision-making for all incompetent individuals.

Age-related variance in decisions under ambiguity is explained by changes in reasoning, executive functions, and decision-making under risk.

PubMed

Schiebener, Johannes; Brand, Matthias

2017-06-01

Previous literature has explained older individuals' disadvantageous decision-making under ambiguity in the Iowa Gambling Task (IGT) by reduced emotional warning signals preceding decisions. We argue that age-related reductions in IGT performance may also be explained by reductions in certain cognitive abilities (reasoning, executive functions). In 210 participants (18-86 years), we found that the age-related variance on IGT performance occurred only in the last 60 trials. The effect was mediated by cognitive abilities and their relation with decision-making performance under risk with explicit rules (Game of Dice Task). Thus, reductions in cognitive functions in older age may be associated with both a reduced ability to gain explicit insight into the rules of the ambiguous decision situation and with failure to choose the less risky options consequently after the rules have been understood explicitly. Previous literature may have underestimated the relevance of cognitive functions for age-related decline in decision-making performance under ambiguity.

The Diagnosis of Urinary Tract Infection in Young Children (DUTY) Study Clinical Rule: Economic Evaluation.

PubMed

Hollingworth, William; Busby, John; Butler, Christopher C; O'Brien, Kathryn; Sterne, Jonathan A C; Hood, Kerenza; Little, Paul; Lawton, Michael; Birnie, Kate; Thomas-Jones, Emma; Harman, Kim; Hay, Alastair D

2017-04-01

To estimate the cost-effectiveness of a two-step clinical rule using symptoms, signs and dipstick testing to guide the diagnosis and antibiotic treatment of urinary tract infection (UTI) in acutely unwell young children presenting to primary care. Decision analytic model synthesising data from a multicentre, prospective cohort study (DUTY) and the wider literature to estimate the short-term and lifetime costs and healthcare outcomes (symptomatic days, recurrent UTI, quality adjusted life years) of eight diagnostic strategies. We compared GP clinical judgement with three strategies based on a 'coefficient score' combining seven symptoms and signs independently associated with UTI and four strategies based on weighted scores according to the presence/absence of five symptoms and signs. We compared dipstick testing versus laboratory culture in children at intermediate risk of UTI. Sampling, culture and antibiotic costs were lowest in high-specificity DUTY strategies (£1.22 and £1.08) compared to clinical judgement (£1.99). These strategies also approximately halved urine sampling (4.8% versus 9.1% in clinical judgement) without reducing sensitivity (58.2% versus 56.4%). Outcomes were very similar across all diagnostic strategies. High-specificity DUTY strategies were more cost-effective than clinical judgement in the short- (iNMB = £0.78 and £0.84) and long-term (iNMB =£2.31 and £2.50). Dipstick tests had poorer cost-effectiveness than laboratory culture in children at intermediate risk of UTI (iNMB = £-1.41). Compared to GPs' clinical judgement, high specificity clinical rules from the DUTY study could substantially reduce urine sampling, achieving lower costs and equivalent patient outcomes. Dipstick testing children for UTI is not cost-effective. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

30 CFR 290.107 - Where are the rules concerning the effect of the Department not issuing a decision in my appeal...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Where are the rules concerning the effect of the Department not issuing a decision in my appeal within the statutory time frame? 290.107 Section... PROCEDURES Minerals Revenue Management Appeal Procedures § 290.107 Where are the rules concerning the effect...

75 FR 19558 - Cancellation of Rule of Practice 41.200(b) Before the Board of Patent Appeals and Interferences...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-15

... package to OMB for its review and approval because the changes in this rule making do not affect the...: Final rule. SUMMARY: The United States Court of Appeals for the Federal Circuit issued a decision in Agilent Technologies, Inc. v. Affymetrix, Inc., 567 F.3d 1366 (Fed. Cir. 2009). That decision impacted the...

An overview of bipolar qualitative decision rules

NASA Astrophysics Data System (ADS)

Bonnefon, Jean-Francois; Dubois, Didier; Fargier, Hélène

Making a good decision is often a matter of listing and comparing positive and negative arguments, as studies in cognitive psychology have shown. In such cases, the evaluation scale should be considered bipolar, that is, negative and positive values are explicitly distinguished. Generally, positive and negative features are evaluated separately, as done in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, decisions are often made on the basis of an ordinal ranking of the pros and the cons, and focusing on the most salient features, i.e., the decision process is qualitative. In this paper, we report on a project aiming at characterizing several decision rules, based on possibilistic order of magnitude reasoning, and tailored for the joint handling of positive and negative affects, and at testing their empirical validity. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case and, like them, suffer from a lack of discrimination power. More decisive rules that refine them are also proposed. They account for both the principle of Pareto-efficiency and the notion of order of magnitude reasoning. The most decisive one uses a lexicographic ranking of the pros and cons. It comes down to a special case of Cumulative Prospect Theory, and subsumes the “Take the best” heuristic.

78 FR 5213 - Self-Regulatory Organizations; New York Stock Exchange LLC; Notice of Filing of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-24

... which is delegated the authority to review disciplinary decisions on behalf of the Exchange Board of... organization. Under the rule, the decision of a majority of the Hearing Panel is the decision of the Hearing..., may request a determination of guilt by default, and may recommend a penalty to be imposed. If the...

75 FR 39715 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-12

... that a refusal by a member to take action necessary to effectuate a final decision of a FINRA officer... necessary to effectuate a final decision of a FINRA officer or the UPC Committee under the UPC Code (FINRA Rule 11000 Series) or other FINRA rules that permit review of FINRA decisions by the UPC Committee...

48 CFR 6101.26 - Reconsideration; amendment of decisions; new hearings [Rule 26].

Code of Federal Regulations, 2010 CFR

2010-10-01

... amend a decision or order for any reason that would justify such action on motion of a party. (d) Effect... for granting a new hearing. Upon granting a motion for a new hearing, the Board will take additional... issue a new decision. (b) Procedure. Any motion under 6101.26 (Rule 26) shall comply with the provisions...

48 CFR 6101.26 - Reconsideration; amendment of decisions; new hearings [Rule 26].

Code of Federal Regulations, 2011 CFR

2011-10-01

... amend a decision or order for any reason that would justify such action on motion of a party. (d) Effect... for granting a new hearing. Upon granting a motion for a new hearing, the Board will take additional... issue a new decision. (b) Procedure. Any motion under 6101.26 (Rule 26) shall comply with the provisions...

An Autonomous Flight Safety System

DTIC Science & Technology

2008-11-01

are taken. AFSS can take vehicle navigation data from redundant onboard sensors and make flight termination decisions using software-based rules...implemented on redundant flight processors. By basing these decisions on actual Instantaneous Impact Predictions and by providing for an arbitrary...number of mission rules, it is the contention of the AFSS development team that the decision making process used by Missile Flight Control Officers

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.; Lea, Robert N.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. Simply stated, the problem reduces to the following: how can we capture the knowledge of an expert when the expert is unable to clearly formulate how he or she arrives at a decision? A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision may have been made. Unique to our work is the fuzzy set representation of the conditions or attributes upon which the expert may possibly base his fuzzy decision. From our examples, we infer certain and possible fuzzy rules for closing a customer service center and illustrate the importance of having the decision closely relate to the conditions under consideration.

Participatory Action Research in Public Mental Health and a School of Nursing: Qualitative Findings from an Academic-Community Partnership

PubMed Central

Mahone, Irma H.; Farrell, Sarah P.; Hinton, Ivora; Johnson, Robert; Moody, David; Rifkin, Karen; Moore, Kenneth; Becker, Marcia; Barker, Margaret

2011-01-01

Summary An academic-community partnership between a school of nursing (SON) at a public university (the University of Virginia, or UVA) and a public mental health clinic developed around a shared goal of finding an acceptable shared decision making (SDM) intervention targeting medication use by persons with serious mental illness. The planning meetings of the academic-community partnership were recorded and analyzed. Issues under the partnership process included 1) clinic values and priorities, 2) research agenda, 3) ground rules, and 4) communication. Issues under the SDM content included: 1) barriers, 2) information exchange, 3) positive aspects of shared decision making, and 4) technology. Using participatory-action research (PAR), the community clinic was able to raise questions and concerns throughout the process, be actively involved in research activities (such as identifying stakeholders and co-leading focus groups), participate in the reflective activities on the impact of SDM on practice and policy, and feel ownership of the SDM intervention. PMID:22163075

A business rules design framework for a pharmaceutical validation and alert system.

PubMed

Boussadi, A; Bousquet, C; Sabatier, B; Caruba, T; Durieux, P; Degoulet, P

2011-01-01

Several alert systems have been developed to improve the patient safety aspects of clinical information systems (CIS). Most studies have focused on the evaluation of these systems, with little information provided about the methodology leading to system implementation. We propose here an 'agile' business rule design framework (BRDF) supporting both the design of alerts for the validation of drug prescriptions and the incorporation of the end user into the design process. We analyzed the unified process (UP) design life cycle and defined the activities, subactivities, actors and UML artifacts that could be used to enhance the agility of the proposed framework. We then applied the proposed framework to two different sets of data in the context of the Georges Pompidou University Hospital (HEGP) CIS. We introduced two new subactivities into UP: business rule specification and business rule instantiation activity. The pharmacist made an effective contribution to five of the eight BRDF design activities. Validation of the two new subactivities was effected in the context of drug dosage adaption to the patients' clinical and biological contexts. Pilot experiment shows that business rules modeled with BRDF and implemented as an alert system triggered an alert for 5824 of the 71,413 prescriptions considered (8.16%). A business rule design framework approach meets one of the strategic objectives for decision support design by taking into account three important criteria posing a particular challenge to system designers: 1) business processes, 2) knowledge modeling of the context of application, and 3) the agility of the various design steps.

78 FR 36434 - Revisions to Rules of Practice

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-18

... federal holidays, make grammatical corrections, and remove the reference to part-day holidays. Rule 3001... section, the following categories of persons are designated ``decision-making personnel'': (i) The.... The following categories of person are designated ``non-decision-making personnel'': (i) All...

Extracting decision rules from police accident reports through decision trees.

PubMed

de Oña, Juan; López, Griselda; Abellán, Joaquín

2013-01-01

Given the current number of road accidents, the aim of many road safety analysts is to identify the main factors that contribute to crash severity. To pinpoint those factors, this paper shows an application that applies some of the methods most commonly used to build decision trees (DTs), which have not been applied to the road safety field before. An analysis of accidents on rural highways in the province of Granada (Spain) between 2003 and 2009 (both inclusive) showed that the methods used to build DTs serve our purpose and may even be complementary. Applying these methods has enabled potentially useful decision rules to be extracted that could be used by road safety analysts. For instance, some of the rules may indicate that women, contrary to men, increase their risk of severity under bad lighting conditions. The rules could be used in road safety campaigns to mitigate specific problems. This would enable managers to implement priority actions based on a classification of accidents by types (depending on their severity). However, the primary importance of this proposal is that other databases not used here (i.e. other infrastructure, roads and countries) could be used to identify unconventional problems in a manner easy for road safety managers to understand, as decision rules. Copyright © 2012 Elsevier Ltd. All rights reserved.

Learning temporal rules to forecast instability in continuously monitored patients

PubMed Central

Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R

2017-01-01

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. PMID:27274020

Form and Objective of the Decision Rule in Absolute Identification

NASA Technical Reports Server (NTRS)

Balakrishnan, J. D.

1997-01-01

In several conditions of a line length identification experiment, the subjects' decision making strategies were systematically biased against the responses on the edges of the stimulus range. When the range and number of the stimuli were small, the bias caused the percentage of correct responses to be highest in the center and lowest on the extremes of the range. Two general classes of decision rules that would explain these results are considered. The first class assumes that subjects intend to adopt an optimal decision rule, but systematically misrepresent one or more parameters of the decision making context. The second class assumes that subjects use a different measure of performance than the one assumed by the experimenter: instead of maximizing the chances of a correct response, the subject attempts to minimize the expected size of the response error (a "fidelity criterion"). In a second experiment, extended experience and feedback did not diminish the bias effect, but explicitly penalizing all response errors equally, regardless of their size, did reduce or eliminate it in some subjects. Both results favor the fidelity criterion over the optimal rule.

Concluding comments: maximizing good patient care and minimizing potential liability when considering complementary and alternative medicine.

PubMed

Gilmour, Joan; Harrison, Christine; Vohra, Sunita

2011-11-01

Our goal for this supplemental issue of Pediatrics was to consider what practitioners, parents, patients, institutions, and policy-makers need to take into account to make good decisions about using complementary and alternative medicine (CAM) to treat children and to develop guidelines for appropriate use. We began by explaining underlying concepts and principles in ethical, legal, and clinical reasoning and then used case scenarios to explore how they apply and identify gaps that remain in practice and policy. In this concluding article, we review our major findings, summarize our recommendations, and suggest further research. We focus on several key areas: practitioner and patient/parent relationships; decision-making; dispute resolution; standards of practice; hospital/health facility policies; patient safety; education; and research. Ethical principles, standards, and rules applicable when making decisions about conventional care for children apply to decision-making about CAM as well. The same is true of legal reasoning. Although CAM use has seldom led to litigation, general legal principles relied on in cases involving conventional medical care provide the starting point for analysis. Similarly, with respect to clinical decision-making, clinicians are guided by clinical judgment and the best interests of their patient. Whether a therapy is CAM or conventional, clinicians must weigh the relative risks and benefits of therapeutic options and take into account their patient's values, beliefs, and preferences. Consequently, many of our observations apply to conventional and CAM care and to both adult and pediatric patients.

Symbolic rule-based classification of lung cancer stages from free-text pathology reports.

PubMed

Nguyen, Anthony N; Lawley, Michael J; Hansen, David P; Bowman, Rayleen V; Clarke, Belinda E; Duhig, Edwina E; Colquist, Shoni

2010-01-01

To classify automatically lung tumor-node-metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification. By exploiting report substructure and the symbolic manipulation of systematized nomenclature of medicine-clinical terms (SNOMED CT) concepts in reports, statements in free text can be evaluated for relevance against factors relating to the staging guidelines. Post-coordinated SNOMED CT expressions based on templates were defined and populated by concepts in reports, and tested for subsumption by staging factors. The subsumption results were used to build logic according to the staging guidelines to calculate the TNM stage. The accuracy measure and confusion matrices were used to evaluate the TNM stages classified by the symbolic rule-based system. The system was evaluated against a database of multidisciplinary team staging decisions and a machine learning-based text classification system using support vector machines. Overall accuracy on a corpus of pathology reports for 718 lung cancer patients against a database of pathological TNM staging decisions were 72%, 78%, and 94% for T, N, and M staging, respectively. The system's performance was also comparable to support vector machine classification approaches. A system to classify lung TNM stages from free-text pathology reports was developed, and it was verified that the symbolic rule-based approach using SNOMED CT can be used for the extraction of key lung cancer characteristics from free-text reports. Future work will investigate the applicability of using the proposed methodology for extracting other cancer characteristics and types.

A Bayesian model averaging method for the derivation of reservoir operating rules

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai

2015-09-01

Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.

Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid: single biomarker re-derivation and external validation in three cohorts

PubMed Central

Body, Richard; Sperrin, Matthew; Lewis, Philip S; Burrows, Gillian; Carley, Simon; McDowell, Garry; Buchan, Iain; Greaves, Kim; Mackway-Jones, Kevin

2017-01-01

Background The original Manchester Acute Coronary Syndromes model (MACS) ‘rules in’ and ‘rules out’ acute coronary syndromes (ACS) using high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid binding protein (H-FABP) measured at admission. The latter is not always available. We aimed to refine and validate MACS as Troponin-only Manchester Acute Coronary Syndromes (T-MACS), cutting down the biomarkers to just hs-cTnT. Methods We present secondary analyses from four prospective diagnostic cohort studies including patients presenting to the ED with suspected ACS. Data were collected and hs-cTnT measured on arrival. The primary outcome was ACS, defined as prevalent acute myocardial infarction (AMI) or incident death, AMI or coronary revascularisation within 30 days. T-MACS was built in one cohort (derivation set) and validated in three external cohorts (validation set). Results At the ‘rule out’ threshold, in the derivation set (n=703), T-MACS had 99.3% (95% CI 97.3% to 99.9%) negative predictive value (NPV) and 98.7% (95.3%–99.8%) sensitivity for ACS, ‘ruling out’ 37.7% patients (specificity 47.6%, positive predictive value (PPV) 34.0%). In the validation set (n=1459), T-MACS had 99.3% (98.3%–99.8%) NPV and 98.1% (95.2%–99.5%) sensitivity, ‘ruling out’ 40.4% (n=590) patients (specificity 47.0%, PPV 23.9%). T-MACS would ‘rule in’ 10.1% and 4.7% patients in the respective sets, of which 100.0% and 91.3% had ACS. C-statistics for the original and refined rules were similar (T-MACS 0.91 vs MACS 0.90 on validation). Conclusions T-MACS could ‘rule out’ ACS in 40% of patients, while ‘ruling in’ 5% at highest risk using a single hs-cTnT measurement on arrival. As a clinical decision aid, T-MACS could therefore help to conserve healthcare resources. PMID:27565197

How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

PubMed

Van Norman, Ethan R; Christ, Theodore J

2016-10-01

Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.

PubMed

Cangelosi, Davide; Muselli, Marco; Parodi, Stefano; Blengio, Fabiola; Becherini, Pamela; Versteeg, Rogier; Conte, Massimo; Varesio, Luigi

2014-01-01

Cancer patient's outcome is written, in part, in the gene expression profile of the tumor. We previously identified a 62-probe sets signature (NB-hypo) to identify tissue hypoxia in neuroblastoma tumors and showed that NB-hypo stratified neuroblastoma patients in good and poor outcome 1. It was important to develop a prognostic classifier to cluster patients into risk groups benefiting of defined therapeutic approaches. Novel classification and data discretization approaches can be instrumental for the generation of accurate predictors and robust tools for clinical decision support. We explored the application to gene expression data of Rulex, a novel software suite including the Attribute Driven Incremental Discretization technique for transforming continuous variables into simplified discrete ones and the Logic Learning Machine model for intelligible rule generation. We applied Rulex components to the problem of predicting the outcome of neuroblastoma patients on the bases of 62 probe sets NB-hypo gene expression signature. The resulting classifier consisted in 9 rules utilizing mainly two conditions of the relative expression of 11 probe sets. These rules were very effective predictors, as shown in an independent validation set, demonstrating the validity of the LLM algorithm applied to microarray data and patients' classification. The LLM performed as efficiently as Prediction Analysis of Microarray and Support Vector Machine, and outperformed other learning algorithms such as C4.5. Rulex carried out a feature selection by selecting a new signature (NB-hypo-II) of 11 probe sets that turned out to be the most relevant in predicting outcome among the 62 of the NB-hypo signature. Rules are easily interpretable as they involve only few conditions. Our findings provided evidence that the application of Rulex to the expression values of NB-hypo signature created a set of accurate, high quality, consistent and interpretable rules for the prediction of neuroblastoma patients' outcome. We identified the Rulex weighted classification as a flexible tool that can support clinical decisions. For these reasons, we consider Rulex to be a useful tool for cancer classification from microarray gene expression data.

Application of decision rules for empowering of Indonesian telematics services SMEs

NASA Astrophysics Data System (ADS)

Tosida, E. T.; Hairlangga, O.; Amirudin, F.; Ridwanah, M.

2018-03-01

The independence of the field of telematics became one of Indonesia's vision in 2024. One effort to achieve it can be done by empowering SMEs in the field of telematics. Empowerment carried out need a practical mechanism by utilizing data centered, including through the National Economic Census database (Susenas). Based on the Susenas can be formulated the decision rules of determining the provision of assistance for SMEs in the field of telematics. The way it did by generating the rule base through the classification technique. The CART algorithm-based decision rule model performs better than C45 and ID3 models. The high level of performance model is also in line with the regulations applied by the government. This becomes one of the strengths of research, because the resulting model is consistent with the existing conditions in Indonesia. The rules base generated from the three classification techniques show different rules. The CART technique has pattern matching with the realization of activities in The Ministry of Cooperatives and SMEs. So far, the government has difficulty in referring data related to the empowerment of SMEs telematics services. Therefore, the findings resulting from this research can be used as an alternative decision support system related to the program of empowerment of SMEs in telematics.

Medicare Program; Prior Authorization Process for Certain Durable Medical Equipment, Prosthetics, Orthotics, and Supplies. Final rule.

PubMed

2015-12-30

This final rule establishes a prior authorization program for certain durable medical equipment, prosthetics, orthotics, and supplies (DMEPOS) items that are frequently subject to unnecessary utilization. This rule defines unnecessary utilization and creates a new requirement that claims for certain DMEPOS items must have an associated provisional affirmed prior authorization decision as a condition of payment. This rule also adds the review contractor's decision regarding prior authorization of coverage of DMEPOS items to the list of actions that are not initial determinations and therefore not appealable.

The Massachusetts abscess rule: a clinical decision rule using ultrasound to identify methicillin-resistant Staphylococcus aureus in skin abscesses.

PubMed

Gaspari, Romolo J; Blehar, David; Polan, David; Montoya, Anthony; Alsulaibikh, Amal; Liteplo, Andrew

2014-05-01

Treatment failure rates for incision and drainage (I&D) of skin abscesses have increased in recent years and may be attributable to an increased prevalence of community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA). Previous authors have described sonographic features of abscesses, such as the presence of interstitial fluid, characteristics of abscess debris, and depth of abscess cavity. It is possible that the sonographic features are associated with MRSA and can be used to predict the presence of MRSA. The authors describe a potential clinical decision rule (CDR) using sonographic images to predict the presence of CA-MRSA. This was a pilot CDR derivation study using databases from two emergency departments (EDs) of patients presenting to the ED with uncomplicated skin abscesses who underwent I&D and culture of the abscess contents. Patients underwent ultrasound (US) imaging of the abscesses prior to I&D. Abscess contents were sent for culture and sensitivity. Two independent physicians experienced in soft tissue US blinded to the culture results and clinical data reviewed the images in a standardized fashion for the presence or absence of the predetermined image characteristics. In the instance of a disagreement between the initial two investigators, a third reviewer adjudicated the findings prior to analysis. The association between the primary outcome (presence of MRSA) and each sonographic feature was assessed using univariate and multivariate analysis. The reliability of each sonographic feature was measured by calculating the kappa (κ) coefficient of interobserver agreement. The decision tree model for the CDR was created with recursive partitioning using variables that were both reliable and strongly associated with MRSA. Of the total of 2,167 patients who presented with skin and soft tissue infections during the study period, 605 patients met inclusion criteria with US imaging and culture and sensitivity of purulence. Among the pathogenic organisms, MRSA was the most frequently isolated, representing 50.1% of all patients. Six of the sonographic features were associated with the presence of MRSA, but only four of these features were reliable using the kappa analysis. Recursive partitioning identified three independent variables that were both associated with MRSA and reliable: 1) the lack of a well-defined edge, 2) small volume, and 3) irregular or indistinct shape. This decision rule demonstrates a sensitivity of 89.2% (95% confidence interval [CI] = 84.7% to 92.7%), a specificity of 44.7% (95% CI = 40.9% to 47.8%), a positive predictive value of 57.9 (95% CI = 55.0 to 60.2), a negative predictive value of 82.9 (95% CI = 75.9 to 88.5), and an odds ratio (OR) of 7.0 (95% CI = 4.0 to 12.2). According to our putative CDR, patients with skin abscesses that are small, irregularly shaped, or indistinct, with ill-defined edges, are seven times more likely to demonstrate MRSA on culture. © 2014 by the Society for Academic Emergency Medicine.

Failure detection system design methodology. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chow, E. Y.

1980-01-01

The design of a failure detection and identification system consists of designing a robust residual generation process and a high performance decision making process. The design of these two processes are examined separately. Residual generation is based on analytical redundancy. Redundancy relations that are insensitive to modelling errors and noise effects are important for designing robust residual generation processes. The characterization of the concept of analytical redundancy in terms of a generalized parity space provides a framework in which a systematic approach to the determination of robust redundancy relations are developed. The Bayesian approach is adopted for the design of high performance decision processes. The FDI decision problem is formulated as a Bayes sequential decision problem. Since the optimal decision rule is incomputable, a methodology for designing suboptimal rules is proposed. A numerical algorithm is developed to facilitate the design and performance evaluation of suboptimal rules.

Textural features for image classification

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Dinstein, I.; Shanmugam, K.

1973-01-01

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

19 CFR 177.13 - Inconsistent customs decisions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Inconsistent customs decisions. 177.13 Section 177.13 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.13 Inconsistent customs...

19 CFR 177.13 - Inconsistent customs decisions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Inconsistent customs decisions. 177.13 Section 177.13 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.13 Inconsistent customs...

19 CFR 177.13 - Inconsistent customs decisions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Inconsistent customs decisions. 177.13 Section 177.13 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) ADMINISTRATIVE RULINGS General Ruling Procedure § 177.13 Inconsistent customs...

Ethical safety of deep brain stimulation: A study on moral decision-making in Parkinson's disease.

PubMed

Fumagalli, Manuela; Marceglia, Sara; Cogiamanian, Filippo; Ardolino, Gianluca; Picascia, Marta; Barbieri, Sergio; Pravettoni, Gabriella; Pacchetti, Claudio; Priori, Alberto

2015-07-01

The possibility that deep brain stimulation (DBS) in Parkinson's disease (PD) alters patients' decisions and actions, even temporarily, raises important clinical, ethical and legal questions. Abnormal moral decision-making can lead to ethical rules violations. Previous experiments demonstrated the subthalamic (STN) activation during moral decision-making. Here we aim to study whether STN DBS can affect moral decision-making in PD patients. Eleven patients with PD and bilateral STN DBS implant performed a computerized moral task in ON and OFF stimulation conditions. A control group of PD patients without DBS implant performed the same experimental protocol. All patients underwent motor, cognitive and psychological assessments. STN stimulation was not able to modify neither reaction times nor responses to moral task both when we compared the ON and the OFF state in the same patient (reaction times, p = .416) and when we compared DBS patients with those treated only with the best medical treatment (reaction times: p = .408, responses: p = .776). Moral judgment is the result of a complex process, requiring cognitive executive functions, problem-solving, anticipations of consequences of an action, conflict processing, emotional evaluation of context and of possible outcomes, and involving different brain areas and neural circuits. Our data show that STN DBS leaves unaffected moral decisions thus implying relevant clinical and ethical implications for DBS consequences on patients' behavior, on decision-making and on judgment ability. In conclusion, the technique can be considered safe on moral behavior. Copyright © 2015 Elsevier Ltd. All rights reserved.

Learning stage-dependent effect of M1 disruption on value-based motor decisions.

PubMed

Derosiere, Gerard; Vassiliadis, Pierre; Demaret, Sophie; Zénon, Alexandre; Duque, Julie

2017-11-15

The present study aimed at characterizing the impact of M1 disruption on the implementation of implicit value information in motor decisions, at both early stages (during reinforcement learning) and late stages (after consolidation) of action value encoding. Fifty subjects performed, over three consecutive days, a task that required them to select between two finger responses according to the color (instruction) and to the shape (implicit, undisclosed rule) of an imperative signal: considering the implicit rule in addition to the instruction allowed subjects to earn more money. We investigated the functional contribution of M1 to the implementation of the implicit rule in subjects' motor decisions. Continuous theta burst stimulation (cTBS) was applied over M1 either on Day 1 or on Day 3, producing a temporary lesion either during reinforcement learning (cTBS Learning group) or after consolidation of the implicit rule, during decision-making (cTBS Decision group), respectively. Interestingly, disrupting M1 activity on Day 1 improved the reliance on the implicit rule, plausibly because M1 cTBS increased dopamine release in the putamen in an indirect way. This finding corroborates the view that cTBS may affect activity in unstimulated areas, such as the basal ganglia. Notably, this effect was short-lasting; it did not persist overnight, suggesting that the functional integrity of M1 during learning is a prerequisite for the consolidation of implicit value information to occur. Besides, cTBS over M1 did not impact the use of the implicit rule when applied on Day 3, although it did so when applied on Day 2 in a recent study where the reliance on the implicit rule declined following cTBS (Derosiere et al., 2017). Overall, these findings indicate that the human M1 is functionally involved in the consolidation and implementation of implicit value information underlying motor decisions. However, M1 contribution seems to vanish as subjects become more experienced in using the implicit value information to make their motor decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessing experience in the deliberate practice of running using a fuzzy decision-support system

PubMed Central

Roveri, Maria Isabel; Manoel, Edison de Jesus; Onodera, Andrea Naomi; Ortega, Neli R. S.; Tessutti, Vitor Daniel; Vilela, Emerson; Evêncio, Nelson

2017-01-01

The judgement of skill experience and its levels is ambiguous though it is crucial for decision-making in sport sciences studies. We developed a fuzzy decision support system to classify experience of non-elite distance runners. Two Mamdani subsystems were developed based on expert running coaches’ knowledge. In the first subsystem, the linguistic variables of training frequency and volume were combined and the output defined the quality of running practice. The second subsystem yielded the level of running experience from the combination of the first subsystem output with the number of competitions and practice time. The model results were highly consistent with the judgment of three expert running coaches (r>0.88, p<0.001) and also with five other expert running coaches (r>0.86, p<0.001). From the expert’s knowledge and the fuzzy model, running experience is beyond the so-called "10-year rule" and depends not only on practice time, but on the quality of practice (training volume and frequency) and participation in competitions. The fuzzy rule-based model was very reliable, valid, deals with the marked ambiguities inherent in the judgment of experience and has potential applications in research, sports training, and clinical settings. PMID:28817655

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

NASA Technical Reports Server (NTRS)

Anastasiadis, Stergios

1991-01-01

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.

Web-based Weather Expert System (WES) for Space Shuttle Launch

NASA Technical Reports Server (NTRS)

Bardina, Jorge E.; Rajkumar, T.

2003-01-01

The Web-based Weather Expert System (WES) is a critical module of the Virtual Test Bed development to support 'go/no go' decisions for Space Shuttle operations in the Intelligent Launch and Range Operations program of NASA. The weather rules characterize certain aspects of the environment related to the launching or landing site, the time of the day or night, the pad or runway conditions, the mission durations, the runway equipment and landing type. Expert system rules are derived from weather contingency rules, which were developed over years by NASA. Backward chaining, a goal-directed inference method is adopted, because a particular consequence or goal clause is evaluated first, and then chained backward through the rules. Once a rule is satisfied or true, then that particular rule is fired and the decision is expressed. The expert system is continuously verifying the rules against the past one-hour weather conditions and the decisions are made. The normal procedure of operations requires a formal pre-launch weather briefing held on Launch minus 1 day, which is a specific weather briefing for all areas of Space Shuttle launch operations. In this paper, the Web-based Weather Expert System of the Intelligent Launch and range Operations program is presented.

The Manchester Acute Coronary Syndromes (MACS) decision rule for suspected cardiac chest pain: derivation and external validation

PubMed Central

Body, Richard; Carley, Simon; McDowell, Garry; Pemberton, Philip; Burrows, Gillian; Cook, Gary; Lewis, Philip S; Smith, Alexander; Mackway-Jones, Kevin

2014-01-01

Objective We aimed to derive and validate a clinical decision rule (CDR) for suspected cardiac chest pain in the emergency department (ED). Incorporating information available at the time of first presentation, this CDR would effectively risk-stratify patients and immediately identify: (A) patients for whom hospitalisation may be safely avoided; and (B) high-risk patients, facilitating judicious use of resources. Methods In two sequential prospective observational cohort studies at heterogeneous centres, we included ED patients with suspected cardiac chest pain. We recorded clinical features and drew blood on arrival. The primary outcome was major adverse cardiac events (MACE) (death, prevalent or incident acute myocardial infarction, coronary revascularisation or new coronary stenosis >50%) within 30 days. The CDR was derived by logistic regression, considering reliable (κ>0.6) univariate predictors (p<0.05) for inclusion. Results In the derivation study (n=698) we derived a CDR including eight variables (high sensitivity troponin T; heart-type fatty acid binding protein; ECG ischaemia; diaphoresis observed; vomiting; pain radiation to right arm/shoulder; worsening angina; hypotension), which had a C-statistic of 0.95 (95% CI 0.93 to 0.97) implying near perfect diagnostic performance. On external validation (n=463) the CDR identified 27.0% of patients as ‘very low risk’ and potentially suitable for discharge from the ED. 0.0% of these patients had prevalent acute myocardial infarction and 1.6% developed MACE (n=2; both coronary stenoses without revascularisation). 9.9% of patients were classified as ‘high-risk’, 95.7% of whom developed MACE. Conclusions The Manchester Acute Coronary Syndromes (MACS) rule has the potential to safely reduce unnecessary hospital admissions and facilitate judicious use of high dependency resources. PMID:24780911

77 FR 32593 - Agency Information Collection Activities; Notice of Intent To Renew Collection: Rules Relating To...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-01

... Association decisions in disciplinary, membership denial, registration, and member responsibility actions... and disciplinary actions. The Commission estimates the burden of this collection of information as... Renew Collection: Rules Relating To Review of National Futures Association Decisions in Disciplinary...

19 CFR 177.1 - General ruling practice and definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... in applicable Treasury Decisions, rulings, opinions, or court decisions published in the Customs... in response to a written request therefor and set forth in a letter addressed to the person making... more than call attention to a well-established interpretation or principle of Customs law, without...

Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

PubMed

Bouaud, Jacques; Guézennec, Gilles; Séroussi, Brigitte

2018-01-01

The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources. The approach is developed for the guideline-based decision support module on breast cancer management within the DESIREE European project. The approach is based on the entity attribute value model and could be extended to other domains.

Clinical course in women undergoing termination of pregnancy within the legal time limit in French-speaking Switzerland.

PubMed

Perrin, Eliane; Berthoud, Marianne; Pott, Murielle; Toledo Vera, Anna G; Perrenoud, David; Bianchi-Demicheli, Francesco

2011-10-19

In 2002, Swiss citizens voted to accept new laws legalising the termination of pregnancy (TOP) up to 12th week of pregnancy. As a result the cantons formulated rules of implementation. Health institutions then had to modify their procedures and practices. One of the objectives of these changes was to simplify the clinical course for women who decide to terminate a pregnancy. Have the various health institutions in French-speaking Switzerland attained this goal? Are there differences between cantons? Are there any other differences, and if so, which ones? Comparative study of cantonal rules of implementation. Study by questionnaire of what happened to 281 women having undergone a TOP in French-speaking Switzerland. Quantitative and qualitative method. The comparative legal study of the six cantonal rules of implementation showed differences between cantons. The clinical course for women are defined by four quantifiable facts: 1) the number of days delay between the woman's decision (first step) and TOP; 2) the number of appointments attended before TOP; 3) the method of TOP; 4) the cost of TOP. On average, the waiting time was 12 days and the number of appointments was 3. The average cost of TOP was 1360 CHF. The differences, sometimes quite large, are explained by the size of the institutions (large university hospitals; average-sized, non-university hospitals; private doctors' offices). The cantonal rules of implementation and the size of the health care institutions play an important role in these courses for women in French-speaking Switzerland.

Development and use of active clinical decision support for preemptive pharmacogenomics

PubMed Central

Bell, Gillian C; Crews, Kristine R; Wilkinson, Mark R; Haidar, Cyrine E; Hicks, J Kevin; Baker, Donald K; Kornegay, Nancy M; Yang, Wenjian; Cross, Shane J; Howard, Scott C; Freimuth, Robert R; Evans, William E; Broeckel, Ulrich; Relling, Mary V; Hoffman, James M

2014-01-01

Background Active clinical decision support (CDS) delivered through an electronic health record (EHR) facilitates gene-based drug prescribing and other applications of genomics to patient care. Objective We describe the development, implementation, and evaluation of active CDS for multiple pharmacogenetic test results reported preemptively. Materials and methods Clinical pharmacogenetic test results accompanied by clinical interpretations are placed into the patient's EHR, typically before a relevant drug is prescribed. Problem list entries created for high-risk phenotypes provide an unambiguous trigger for delivery of post-test alerts to clinicians when high-risk drugs are prescribed. In addition, pre-test alerts are issued if a very-high risk medication is prescribed (eg, a thiopurine), prior to the appropriate pharmacogenetic test result being entered into the EHR. Our CDS can be readily modified to incorporate new genes or high-risk drugs as they emerge. Results Through November 2012, 35 customized pharmacogenetic rules have been implemented, including rules for TPMT with azathioprine, thioguanine, and mercaptopurine, and for CYP2D6 with codeine, tramadol, amitriptyline, fluoxetine, and paroxetine. Between May 2011 and November 2012, the pre-test alerts were electronically issued 1106 times (76 for thiopurines and 1030 for drugs metabolized by CYP2D6), and the post-test alerts were issued 1552 times (1521 for TPMT and 31 for CYP2D6). Analysis of alert outcomes revealed that the interruptive CDS appropriately guided prescribing in 95% of patients for whom they were issued. Conclusions Our experience illustrates the feasibility of developing computational systems that provide clinicians with actionable alerts for gene-based drug prescribing at the point of care. PMID:23978487

Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.

PubMed

Tsipouras, Markos G; Exarchos, Themis P; Fotiadis, Dimitrios I; Kotsia, Anna P; Vakalis, Konstantinos V; Naka, Katerina K; Michalis, Lampros K

2008-07-01

A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.

The impact of the Rasouli decision: a Survey of Canadian intensivists.

PubMed

Cape, David; Fox-Robichaud, Alison; Turgeon, Alexis F; Seely, Andrew; Hall, Richard; Burns, Karen; Singal, Rohit K; Dodek, Peter; Bagshaw, Sean; Sibbald, Robert; Downar, James

2016-03-01

In a landmark 2013 decision, the Supreme Court of Canada (SCC) ruled that the withdrawal of life support in certain circumstances is a treatment requiring patient or substitute decision maker (SDM) consent. How intensive care unit (ICU) physicians perceive this ruling is unknown. To determine physician knowledge of and attitudes towards the SCC decision, as well as the self-reported changes in practice attributed to the decision. We surveyed intensivists at university hospitals across Canada. We used a knowledge test and Likert-scale questions to measure respondent knowledge of and attitudes towards the ruling. We used vignettes to assess decision making in cases of intractable physician-SDM conflict over the management of patients with very poor prognoses. We compared management choices pre-SCC decision versus post-SCC decision versus the subjective, respondent-defined most appropriate choice. Responses were compared across predefined subgroups. We performed qualitative analysis on free-text responses. We received 82 responses (response rate=42%). Respondents reported providing high levels of self-defined inappropriate treatment. Although most respondents reported no change in practice, there was a significant overall shift towards higher intensity and less subjectively appropriate management after the SCC decision. Attitudes to the SCC decision and approaches to disputes over end-of-life (EoL) care in the ICU were highly variable. There were no significant differences among predefined subgroups. Many Canadian ICU physicians report providing a higher intensity of treatment, and less subjectively appropriate treatment, in situations of dispute over EoL care after the Supreme Court of Canada's ruling in Cuthbertson versus Rasouli. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Mock jury trials in Taiwan--paving the ground for introducing lay participation.

PubMed

Huang, Kuo-Chang; Lin, Chang-Ching

2014-08-01

The first mock jury study in Taiwan, in which 279 community members watched a videotaped trial, investigated how jurors' estimates of the relative undesirability of wrongful conviction versus wrongful acquittal predicted individual decisions and how decision rules affected outcomes. The percentage of jurors who viewed wrongful conviction as more undesirable increased from 50.9% to 60.9% after deliberation and jurors' postdeliberation acquittal rate (71.7%) was higher than predeliberation acquittal rate (58.8%). Jurors' estimates of the undesirability of wrongful conviction were not correlated with their predeliberation votes but became positively correlated with their postdeliberation decisions. The unanimous rule facilitated jurors' change of vote, predominantly from conviction to acquittal, than the simple majority rule. Jurors reaching a verdict under the unanimous rule viewed deliberation and the verdict more positively. This study indicates that deliberation can ameliorate the problem of most Taiwanese citizens not viewing wrongful conviction as more undesirable than wrongful acquittal. It also suggests that Taiwan should adopt a unanimous rule for its proposed lay participation system.

12 CFR 263.38 - Recommended decision and filing of record.

Code of Federal Regulations, 2010 CFR

2010-01-01

... FEDERAL RESERVE SYSTEM RULES OF PRACTICE FOR HEARINGS Uniform Rules of Practice and Procedure § 263.38... expiration of the time allowed for filing reply briefs under § 263.37(b), the administrative law judge shall... the administrative law judge's recommended decision, recommended findings of fact, recommended...

49 CFR 1115.1 - Scope of rule.

Code of Federal Regulations, 2010 CFR

2010-10-01

... other than initial decisions. For each category, this rule describes the types of appeal permitted, the requirements to be observed in filing an appeal, provisions for stay of the action, and the status of the action in the absence of a stay. (c) Appeals from the decisions of employees acting under authority...

12 CFR 622.12 - Proposed findings and conclusions; recommended decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Proposed findings and conclusions; recommended decision. 622.12 Section 622.12 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM RULES OF PRACTICE AND PROCEDURE Rules Applicable to Formal Hearings § 622.12 Proposed findings and conclusions...

10 CFR 110.50 - Terms.

Code of Federal Regulations, 2010 CFR

2010-01-01

... provisions of the Atomic Energy Act and to all applicable rules, regulations, decisions and orders of the... conditions when required by amendments of the Atomic Energy Act or other applicable law, or by other rules, regulations, decisions or orders issued in accordance with the terms of the Atomic Energy Act or other...

19 CFR 177.2 - Submission of ruling requests.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Headquarters Office will prepare final decisions under § 177.11 (Requests for Advice by Field Officers), or § 174.23 (Further Review of Protests), § 177.10 (Change of Practice), decisions under part 175 of this... Carrier rulings should be addressed to the Commissioner of Customs and Border Protection, Attention...

17 CFR 201.411 - Commission consideration of initial decisions by hearing officers.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false Commission consideration of initial decisions by hearing officers. 201.411 Section 201.411 Commodity and Securities Exchanges SECURITIES AND EXCHANGE COMMISSION RULES OF PRACTICE Rules of Practice Appeal to the Commission and...

76 FR 37274 - Outer Continental Shelf Air Regulations Consistency Update for Alaska

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-27

... and prevents EPA from making substantive changes to the requirements it incorporates. As a result, EPA... narrative discussing how EPA made the decision to include or exclude rules. The Alaska Eskimo Whaling Commission expressed specific concern with EPA's decision to exclude administrative and procedural rules and...

An automated approach to the design of decision tree classifiers

NASA Technical Reports Server (NTRS)

Argentiero, P.; Chin, R.; Beaudet, P.

1982-01-01

An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

Primary motor cortex contributes to the implementation of implicit value-based rules during motor decisions.

PubMed

Derosiere, Gerard; Zénon, Alexandre; Alamia, Andrea; Duque, Julie

2017-02-01

In the present study, we investigated the functional contribution of the human primary motor cortex (M1) to motor decisions. Continuous theta burst stimulation (cTBS) was used to alter M1 activity while participants performed a decision-making task in which the reward associated with the subjects' responses (right hand finger movements) depended on explicit and implicit value-based rules. Subjects performed the task over two consecutive days and cTBS occurred in the middle of Day 2, once the subjects were just about to implement implicit rules, in addition to the explicit instructions, to choose their responses, as evident in the control group (cTBS over the right somatosensory cortex). Interestingly, cTBS over the left M1 prevented subjects from implementing the implicit value-based rule while its implementation was enhanced in the group receiving cTBS over the right M1. Hence, cTBS had opposite effects depending on whether it was applied on the contralateral or ipsilateral M1. The use of the explicit value-based rule was unaffected by cTBS in the three groups of subject. Overall, the present study provides evidence for a functional contribution of M1 to the implementation of freshly acquired implicit rules, possibly through its involvement in a cortico-subcortical network controlling value-based motor decisions. Copyright © 2016 Elsevier Inc. All rights reserved.

Linking clinical measurements and kinematic gait patterns of toe-walking using fuzzy decision trees.

PubMed

Armand, Stéphane; Watelain, Eric; Roux, Emmanuel; Mercier, Moïse; Lepoutre, François-Xavier

2007-03-01

Toe-walking is one of the most prevalent gait deviations and has been linked to many diseases. Three major ankle kinematic patterns have been identified in toe-walkers, but the relationships between the causes of toe-walking and these patterns remain unknown. This study aims to identify these relationships. Clearly, such knowledge would increase our understanding of this gait deviation, and could help clinicians plan treatment. The large quantity of data provided by gait analysis often makes interpretation a difficult task. Artificial intelligence techniques were used in this study to facilitate interpretation as well as to decrease subjective interpretation. Of the 716 limbs evaluated, 240 showed signs of toe-walking and met inclusion criteria. The ankle kinematic pattern of the evaluated limbs during gait was assigned to one of three toe-walking pattern groups to build the training data set. Toe-walker clinical measurements (range of movement, muscle spasticity and muscle strength) were coded in fuzzy modalities, and fuzzy decision trees were induced to create intelligible rules allowing toe-walkers to be assigned to one of the three groups. A stratified 10-fold cross validation situated the classification accuracy at 81%. Twelve rules depicting the causes of toe-walking were selected, discussed and characterized using kinematic, kinetic and EMG charts. This study proposes an original approach to linking the possible causes of toe-walking with gait patterns.

18 CFR 385.702 - Definitions (Rule 702).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Definitions (Rule 702). 385.702 Section 385.702 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES RULES OF PRACTICE AND PROCEDURE Decisions § 385.702 Definitions (Rule...

[CT scans in children with head/brain injury: five years after the revision of the guideline on "mild traumatic head/brain injury"].

PubMed

Hageman, G Gerard

2015-01-01

In 2010 the guideline on mild traumatic head/ brain injury for both adults and children was revised under the supervision of the Dutch Neurology Society. The revised guideline endorsed rules for decisions on whether to carry out diagnostic imaging investigations (brain CT scanning) and formulates indications for admission. Unfortunately, 5 years after its introduction, it is clear that the guideline rules result in excessive brain CT scanning, in which no more serious head injury is diagnosed. Brain injury may be present in (small) children even if symptoms are absent at first presentation. Also, clinical signs do not predict intracranial complications. This was nicely demonstrated in a study by Tilma, Bekhof and Brand of 410 children with mTBI: no clinical symptom or sign reliably predicted the risk of intracranial bleeding. They advise hospitalisation for observation instead of brain CT scanning. It may be necessary to review part of the Dutch guideline on mTBI.

Knowledge discovery for pancreatic cancer using inductive logic programming.

PubMed

Qiu, Yushan; Shimada, Kazuaki; Hiraoka, Nobuyoshi; Maeshiro, Kensei; Ching, Wai-Ki; Aoki-Kinoshita, Kiyoko F; Furuta, Koh

2014-08-01

Pancreatic cancer is a devastating disease and predicting the status of the patients becomes an important and urgent issue. The authors explore the applicability of inductive logic programming (ILP) method in the disease and show that the accumulated clinical laboratory data can be used to predict disease characteristics, and this will contribute to the selection of therapeutic modalities of pancreatic cancer. The availability of a large amount of clinical laboratory data provides clues to aid in the knowledge discovery of diseases. In predicting the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer, using the ILP model, three rules are developed that are consistent with descriptions in the literature. The rules that are identified are useful to detect the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer and therefore contributed significantly to the decision of therapeutic strategies. In addition, the proposed method is compared with the other typical classification techniques and the results further confirm the superiority and merit of the proposed method.

A prospective cluster-randomized trial to implement the Canadian CT Head Rule in emergency departments

PubMed Central

Stiell, Ian G.; Clement, Catherine M.; Grimshaw, Jeremy M.; Brison, Robert J.; Rowe, Brian H.; Lee, Jacques S.; Shah, Amit; Brehaut, Jamie; Holroyd, Brian R.; Schull, Michael J.; McKnight, R. Douglas; Eisenhauer, Mary A.; Dreyer, Jonathan; Letovsky, Eric; Rutledge, Tim; MacPhail, Iain; Ross, Scott; Perry, Jeffrey J.; Ip, Urbain; Lesiuk, Howard; Bennett, Carol; Wells, George A.

2010-01-01

Background The Canadian CT Head Rule was developed to allow physicians to be more selective when ordering computed tomography (CT) imaging for patients with minor head injury. We sought to evaluate the effectiveness of implementing this validated decision rule at multiple emergency departments. Methods We conducted a matched-pair cluster-randomized trial that compared the outcomes of 4531 patients with minor head injury during two 12-month periods (before and after) at hospital emergency departments in Canada, six of which were randomly allocated as intervention sites and six as control sites. At the intervention sites, active strategies, including education, changes to policy and real-time reminders on radiologic requisitions were used to implement the Canadian CT Head Rule. The main outcome measure was referral for CT scan of the head. Results Baseline characteristics of patients were similar when comparing control to intervention sites. At the intervention sites, the proportion of patients referred for CT imaging increased from the “before” period (62.8%) to the “after” period (76.2%) (difference +13.3%, 95% CI 9.7%–17.0%). At the control sites, the proportion of CT imaging usage also increased, from 67.5% to 74.1% (difference +6.7%, 95% CI 2.6%–10.8%). The change in mean imaging rates from the “before” period to the “after” period for intervention versus control hospitals was not significant (p = 0.16). There were no missed brain injuries or adverse outcomes. Interpretation Our knowledge–translation-based trial of the Canadian CT Head Rule did not reduce rates of CT imaging in Canadian emergency departments. Future studies should identify strategies to deal with barriers to implementation of this decision rule and explore more effective approaches to knowledge translation. (ClinicalTrials.gov trial register no. NCT00993252) PMID:20732978

Supporting clinical rules engine in the adjustment of medication (SCREAM): protocol of a multicentre, prospective, randomised study.

PubMed

Mestres Gonzalvo, Carlota; de Wit, Hugo A J M; van Oijen, Brigit P C; Hurkens, Kim P G M; Janknegt, Rob; Schols, Jos M G A; Mulder, Wubbo J; Verhey, Frans R; Winkens, Bjorn; van der Kuy, Paul-Hugo M

2017-01-26

In the nursing home population, it is estimated that 1 in every 3 patients is polymedicated and given their considerable frailty, these patients are especially prone to adverse drug reactions. Clinical pharmacist-led medication reviews are considered successful interventions to improve medication safety in the inpatient setting. Due to the limited available evidence concerning the benefits of medication reviews performed in the nursing home setting, we propose a study aiming to demonstrate a positive effect that a clinical decision support system, as a health care intervention, may have on the target population. The primary objective of this study is to reduce the number of patients with at least one event when using the clinical decision support system compared to the regular care. These events consist of hospital referrals, delirium, falls, and/or deaths. This study is a multicentre, prospective, randomised study with a cluster group design. The randomisation will be per main nursing home physician and stratified per ward (somatic and psychogeriatric). In the intervention group the clinical decision support system will be used to screen medication list, laboratory values and medical history in order to obtain potential clinical relevant remarks. The remarks will be sent to the main physician and feedback will be provided whether the advice was followed or not. In the control group regular care will be applied. We strongly believe that by using a clinical decision support system, medication reviews are performed in a standardised way which leads to comparable results between patients. In addition, using a clinical decision support system eliminates the time factor to perform medication reviews as the major problems related to medication, laboratory values, indications and/or established patient characteristics will be directly available. In this way, and in order to make the medication review process complete, consultation within healthcare professionals and/or the patient itself will be time effective and the medication surveillance could be performed around the clock. The Netherlands National Trial Register NTR5165 . Registered 2nd April 2015.

Measuring agreement between decision support reminders: the cloud vs. the local expert.

PubMed

Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford

2014-04-10

A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web service and local CDSS. The clinical reminders returned by both services were captured for analysis. Cohen's Kappa coefficient was calculated to compare the two sets of reminders. Kappa statistics were further adjusted for prevalence and bias due to the potential effects of bias in the CDS logic and prevalence in the relative small sample of patients. The cloud-based CDSS generated 965 clinical reminders for 405 patient visits over 3 months. The local CDSS returned 889 reminders for the same patient visit data. When adjusted for prevalence and bias, observed agreement varied by reminder from 0.33 (95% CI 0.24 - 0.42) to 0.99 (95% CI 0.97 - 1.00) and demonstrated almost perfect agreement for 7 of the 11 reminders. Preventive care reminders delivered by two disparate CDS systems show substantial agreement. Subtle differences in rule logic and terminology mapping appear to account for much of the discordance. Cloud-based CDSS therefore show promise, opening the door for future development and implementation in support of health care providers with limited resources for knowledge management of complex logic and rules.

Measuring agreement between decision support reminders: the cloud vs. the local expert

PubMed Central

2014-01-01

Background A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web service and local CDSS. The clinical reminders returned by both services were captured for analysis. Cohen’s Kappa coefficient was calculated to compare the two sets of reminders. Kappa statistics were further adjusted for prevalence and bias due to the potential effects of bias in the CDS logic and prevalence in the relative small sample of patients. Results The cloud-based CDSS generated 965 clinical reminders for 405 patient visits over 3 months. The local CDSS returned 889 reminders for the same patient visit data. When adjusted for prevalence and bias, observed agreement varied by reminder from 0.33 (95% CI 0.24 – 0.42) to 0.99 (95% CI 0.97 – 1.00) and demonstrated almost perfect agreement for 7 of the 11 reminders. Conclusions Preventive care reminders delivered by two disparate CDS systems show substantial agreement. Subtle differences in rule logic and terminology mapping appear to account for much of the discordance. Cloud-based CDSS therefore show promise, opening the door for future development and implementation in support of health care providers with limited resources for knowledge management of complex logic and rules. PMID:24720863

Clinical decision support alert malfunctions: analysis and empirically derived taxonomy.

PubMed

Wright, Adam; Ai, Angela; Ash, Joan; Wiesen, Jane F; Hickman, Thu-Trang T; Aaron, Skye; McEvoy, Dustin; Borkowsky, Shane; Dissanayake, Pavithra I; Embi, Peter; Galanter, William; Harper, Jeremy; Kassakian, Steve Z; Ramoni, Rachel; Schreiber, Richard; Sirajuddin, Anwar; Bates, David W; Sittig, Dean F

2018-05-01

To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions. We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions. We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common. Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS. CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

The utility of decision support, clinical guidelines, and financial incentives as tools to achieve improved clinical performance.

PubMed

Goldfarb, S

1999-03-01

Whether one seeks to reduce inappropriate utilization of resources, improve diagnostic accuracy, increase utilization of effective therapies, or reduce the incidence of complications, the key to change is physician involvement in change. Unfortunately, a simple approach to the problem of inducing change in physician behavior is not available. There is a generally accepted view that expert, best-practice guidelines will improve clinical performance. However, there may be a bias to report positive results and a lack of careful analysis of guideline usage in routine practice in a "postmarketing" study akin to that seen in the pharmaceutical industry. Systems that allow the reliable assessment of quality of outcomes, efficiency of resource utilization, and accurate assessment of the risks associated with the care of given patient populations must be widely available before deciding whether an incentive-based system for providing the full range of medical care is feasible. Decision support focuses on providing information, ideally at the "point of service" and in the context of a particular clinical situation. Rules are self-imposed by physicians and are therefore much more likely to be adopted. As health care becomes corporatized, with increasing numbers of physicians employed by large organizations with the capacity to provide detailed information on the nature and quality of clinical care, it is possible that properly constructed guidelines, appropriate financial incentives, and robust forms of decision support will lead to a physician-led, process improvement approach to more rational and affordable health care.

Application of a diagnosis-based clinical decision guide in patients with low back pain.

PubMed

Murphy, Donald R; Hurwitz, Eric L

2011-10-21

Low back pain (LBP) is common and costly. Development of accurate and efficacious methods of diagnosis and treatment has been identified as a research priority. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule) has been proposed which attempts to provide the clinician with a systematic, evidence-based means to apply the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with LBP. Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of LBP patients examined by one of three examiners trained in the application of the DBCDG. Data were gathered on 264 patients. Signs of visceral disease or potentially serious illness were found in 2.7%. Centralization signs were found in 41%, lumbar and sacroiliac segmental signs in 23% and 27%, respectively and radicular signs were found in 24%. Clinically relevant myofascial signs were diagnosed in 10%. Dynamic instability was diagnosed in 63%, fear beliefs in 40%, central pain hypersensitivity in 5%, passive coping in 3% and depression in 3%. The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability and efficacy of treatment based on the DBCDG.

Are electronic health records ready for genomic medicine?

PubMed

Scheuner, Maren T; de Vries, Han; Kim, Benjamin; Meili, Robin C; Olmstead, Sarah H; Teleki, Stephanie

2009-07-01

The goal of this project was to assess genetic/genomic content in electronic health records. Semistructured interviews were conducted with key informants. Questions addressed documentation, organization, display, decision support and security of family history and genetic test information, and challenges and opportunities relating to integrating genetic/genomics content in electronic health records. There were 56 participants: 10 electronic health record specialists, 18 primary care clinicians, 16 medical geneticists, and 12 genetic counselors. Few clinicians felt their electronic record met their current genetic/genomic medicine needs. Barriers to integration were mostly related to problems with family history data collection, documentation, and organization. Lack of demand for genetics content and privacy concerns were also mentioned as challenges. Data elements and functionality requirements that clinicians see include: pedigree drawing; clinical decision support for familial risk assessment and genetic testing indications; a patient portal for patient-entered data; and standards for data elements, terminology, structure, interoperability, and clinical decision support rules. Although most said that there is little impact of genetics/genomics on electronic records today, many stated genetics/genomics would be a driver of content in the next 5-10 years. Electronic health records have the potential to enable clinical integration of genetic/genomic medicine and improve delivery of personalized health care; however, structured and standardized data elements and functionality requirements are needed.

Design of a decision-support architecture for management of remotely monitored patients.

PubMed

Basilakis, Jim; Lovell, Nigel H; Redmond, Stephen J; Celler, Branko G

2010-09-01

Telehealth is the provision of health services at a distance. Typically, this occurs in unsupervised or remote environments, such as a patient's home. We describe one such telehealth system and the integration of extracted clinical measurement parameters with a decision-support system (DSS). An enterprise application-server framework, combined with a rules engine and statistical analysis tools, is used to analyze the acquired telehealth data, searching for trends and shifts in parameter values, as well as identifying individual measurements that exceed predetermined or adaptive thresholds. An overarching business process engine is used to manage the core DSS knowledge base and coordinate workflow outputs of the DSS. The primary role for such a DSS is to provide an effective means to reduce the data overload and to provide a means of health risk stratification to allow appropriate targeting of clinical resources to best manage the health of the patient. In this way, the system may ultimately influence changes in workflow by targeting scarce clinical resources to patients of most need. A single case study extracted from an initial pilot trial of the system, in patients with chronic obstructive pulmonary disease and chronic heart failure, will be reviewed to illustrate the potential benefit of integrating telehealth and decision support in the management of both acute and chronic disease.

Cooperation and Defection in Ghetto

NASA Astrophysics Data System (ADS)

Kułakowski, Krzysztof

We consider ghetto as a community of people ruled against their will by an external power. Members of the community feel that their laws are broken. However, attempts to leave ghetto makes their situation worse. We discuss the relation of the ghetto inhabitants to the ruling power in context of their needs, organized according to the Maslow hierarchy. Decisions how to satisfy successive needs are undertaken in cooperation with or defection the ruling power. This issue allows to construct the tree of decisions and to adopt the pruning technique from the game theory. Dynamics of decisions can be described within the formalism of fundamental equations. The result is that the strategy of defection is stabilized by the estimated payoff.

Law & psychiatry: mental retardation and the death penalty: after Atkins.

PubMed

Appelbaum, Paul S

2009-10-01

In Atkins v. Virginia the U.S. Supreme Court declared execution of persons with mental retardation to constitute cruel and unusual punishment, and thus to be unconstitutional under the Eighth Amendment. However, the Court left all considerations regarding how to implement the decision explicitly to the states. Since Atkins was decided in 2002, legislatures, courts, and mental health experts have struggled with its implementation, highlighting the complexities that can arise when the courts base legal rules on clinical findings. This column reviews the Atkins case and considers the challenges associated with a clinical determination that can have life-or-death consequences for capital defendants.

Should all acutely ill children in primary care be tested with point-of-care CRP: a cluster randomised trial.

PubMed

Verbakel, Jan Y; Lemiengre, Marieke B; De Burghgraeve, Tine; De Sutter, An; Aertgeerts, Bert; Shinkins, Bethany; Perera, Rafael; Mant, David; Van den Bruel, Ann; Buntinx, Frank

2016-10-06

Point-of-care blood C-reactive protein (CRP) testing has diagnostic value in helping clinicians rule out the possibility of serious infection. We investigated whether it should be offered to all acutely ill children in primary care or restricted to those identified as at risk on clinical assessment. Cluster randomised controlled trial involving acutely ill children presenting to 133 general practitioners (GPs) at 78 GP practices in Belgium. Practices were randomised to undertake point-of-care CRP testing in all children (1730 episodes) or restricted to children identified as at clinical risk (1417 episodes). Clinical risk was assessed by a validated clinical decision rule (presence of one of breathlessness, temperature ≥ 40 °C, diarrhoea and age 12-30 months, or clinician concern). The main trial outcome was hospital admission with serious infection within 5 days. No specific guidance was given to GPs on interpreting CRP levels but diagnostic performance is reported at 5, 20, 80 and 200 mg/L. Restricting CRP testing to those identified as at clinical risk substantially reduced the number of children tested by 79.9 % (95 % CI, 77.8-82.0 %). There was no significant difference between arms in the number of children with serious infection who were referred to hospital immediately (0.16 % vs. 0.14 %, P = 0.88). Only one child with a CRP < 5 mg/L had an illness requiring admission (a child with viral gastroenteritis admitted for rehydration). However, of the 80 children referred to hospital to rule out serious infection, 24 (30.7 %, 95 % CI, 19.6-45.6 %) had a CRP < 5 mg/L. CRP testing should be restricted to children at higher risk after clinical assessment. A CRP < 5 mg/L rules out serious infection and could be used by GPs to avoid unnecessary hospital referrals. ClinicalTrials.gov Identifier: NCT02024282 (registered on 14 th September 2012).

Minor head injury in children.

PubMed

Klig, Jean E; Kaplan, Carl P

2010-06-01

This review will examine mild closed head injury (CHI) and the current evidence on head computed tomography (CT) imaging risks in children, prediction rules to guide decisions on CT scan use, and issues of concussion after initial evaluation. The current literature offers preliminary evidence on the risks of radiation exposure from CT scans in children. A recent study introduces a validated prediction rule for use in mild CHI, to limit the number of CT scans performed. Concurrent with this progress, fast (or short sequence) MRI represents an emerging technology that may prove to be a viable alternative to CT scan use in certain cases of mild CHI where imaging is desired. The initial emergency department evaluation for mild CHI is the start point for a sequence of follow-up to assure that postconcussive symptoms fully resolve. The literature on sports-related concussion offers some information that may be used for patients with non-sports-related concussion. It is clear that CT scan use should be as safe and limited in scope as possible for children. Common decisions on the use of CT imaging for mild head injury can now be guided by a prediction rule for clinically important traumatic brain injury. Parameters for the follow-up care of patients with mild CHI after emergency department discharge are needed in the future to assure that postconcussive symptoms are adequately screened for full resolution.

4 CFR 22.4 - Appeal File [Rule 4].

Code of Federal Regulations, 2010 CFR

2010-01-01

... contracting officer relied in making the decision, and any correspondence relating thereto; (v) Transcripts of... 4 Accounts 1 2010-01-01 2010-01-01 false Appeal File [Rule 4]. 22.4 Section 22.4 Accounts... consisting of all documents pertinent to the appeal, including: (i) The decision from which the appeal is...

29 CFR 18.103 - Rulings on evidence.

Code of Federal Regulations, 2010 CFR

2010-07-01

... is more probably true than not true that the error did not materially contribute to the decision or... if explicitly not relied upon by the judge in support of the decision or order. (b) Record of offer... making of an offer in question and answer form. (c) Plain error. Nothing in this rule precludes taking...

34 CFR 31.8 - Rules of decision.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 1 2010-07-01 2010-07-01 false Rules of decision. 31.8 Section 31.8 Education Office of the Secretary, Department of Education SALARY OFFSET FOR FEDERAL EMPLOYEES WHO ARE INDEBTED TO THE.... (3) The act or omission of an institution of higher education at which the employee was enrolled does...

Student Expression: The Uncertain Future

ERIC Educational Resources Information Center

Bathon, Justin M.; McCarthy, Martha M.

2008-01-01

On June 25, 2007, the United States Supreme Court rendered its decision in "Morse v. Frederick", a long-awaited ruling regarding student speech in public schools. For nearly twenty years, the Supreme Court had been silent on the issue while lower courts attempted to apply the rules announced in previous Supreme Court decisions. It is…

Individual versus Household Migration Decision Rules: Gender and Marital Status Differences in Intentions to Migrate in South Africa.

PubMed

Gubhaju, Bina; De Jong, Gordon F

2009-03-01

This research tests the thesis that the neoclassical micro-economic and the new household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame of intention to migrate. Comparative tests of both theories within the same study design are relatively rare. Utilizing data from the Causes of Migration in South Africa national migration survey, we analyze how individually held "own-future" versus alternative "household well-being" migration decision rules effect the intentions to migrate of male and female adults in South Africa. Results from the gender and marital status specific logistic regressions models show consistent support for the different gender-marital status decision rule thesis. Specifically, the "maximizing one's own future" neoclassical microeconomic theory proposition is more applicable for never married men and women, the "maximizing household income" proposition for married men with short-term migration intentions, and the "reduce household risk" proposition for longer time horizon migration intentions of married men and women. Results provide new evidence on the way household strategies and individual goals jointly affect intentions to move or stay.

Ventral striatum and the evaluation of memory retrieval strategies.

PubMed

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M; Scimeca, Jason M

2014-09-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant's subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies.

Making sense of information in noisy networks: human communication, gossip, and distortion.

PubMed

Laidre, Mark E; Lamb, Alex; Shultz, Susanne; Olsen, Megan

2013-01-21

Information from others can be unreliable. Humans nevertheless act on such information, including gossip, to make various social calculations, thus raising the question of whether individuals can sort through social information to identify what is, in fact, true. Inspired by empirical literature on people's decision-making when considering gossip, we built an agent-based simulation model to examine how well simple decision rules could make sense of information as it propagated through a network. Our simulations revealed that a minimalistic decision-rule 'Bit-wise mode' - which compared information from multiple sources and then sought a consensus majority for each component bit within the message - was consistently the most successful at converging upon the truth. This decision rule attained high relative fitness even in maximally noisy networks, composed entirely of nodes that distorted the message. The rule was also superior to other decision rules regardless of its frequency in the population. Simulations carried out with variable agent memory constraints, different numbers of observers who initiated information propagation, and a variety of network types suggested that the single most important factor in making sense of information was the number of independent sources that agents could consult. Broadly, our model suggests that despite the distortion information is subject to in the real world, it is nevertheless possible to make sense of it based on simple Darwinian computations that integrate multiple sources. Copyright © 2012 Elsevier Ltd. All rights reserved.

Combined rule extraction and feature elimination in supervised classification.

PubMed

Liu, Sheng; Patel, Ronak Y; Daga, Pankaj R; Liu, Haining; Fu, Gang; Doerksen, Robert J; Chen, Yixin; Wilkins, Dawn E

2012-09-01

There are a vast number of biology related research problems involving a combination of multiple sources of data to achieve a better understanding of the underlying problems. It is important to select and interpret the most important information from these sources. Thus it will be beneficial to have a good algorithm to simultaneously extract rules and select features for better interpretation of the predictive model. We propose an efficient algorithm, Combined Rule Extraction and Feature Elimination (CRF), based on 1-norm regularized random forests. CRF simultaneously extracts a small number of rules generated by random forests and selects important features. We applied CRF to several drug activity prediction and microarray data sets. CRF is capable of producing performance comparable with state-of-the-art prediction algorithms using a small number of decision rules. Some of the decision rules are biologically significant.

Age differences in understanding precedent-setting decisions and authorities' responses to violations of deontic rules.

PubMed

Klaczynski, Paul A

2011-05-01

To examine age trends in precedent-setting decisions and the effects of these decisions on perceptions of authorities, preadolescents and adolescents were presented with deontic rule infractions that occurred in the absence or presence of mitigating circumstances. In Study 1, in the absence of mitigating circumstances, adolescents recommended punishing rule violations more than preadolescents; when mitigating circumstances were present, adolescents recommended punishing infractions less than preadolescents. In Study 2, before and after receiving information that authorities had punished or permitted rule violations, participants indicated their beliefs in authority legitimacy, rule strength, and rule deterrence value. In the absence of mitigating circumstances, beliefs strengthened when infractions were punished and beliefs weakened when infractions were permitted. When mitigating circumstances were present and authorities punished violations, preadolescents' legitimacy and deterrence beliefs strengthened. Adolescents' deterrence beliefs strengthened, but their beliefs in authority legitimacy weakened. When justifiable infractions were permitted, preadolescents' legitimacy and deterrence beliefs weakened, whereas adolescents' beliefs strengthened. Discussion focuses on age differences in legitimacy beliefs and understanding the consequences of setting precedents and on the relevance of the findings to theories of deontic reasoning, moral judgments, and epistemological development. Copyright © 2010 Elsevier Inc. All rights reserved.

Heuristics: foundations for a novel approach to medical decision making.

PubMed

Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V

2015-03-01

Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.

A Recommendation Algorithm for Automating Corollary Order Generation

PubMed Central

Klann, Jeffrey; Schadow, Gunther; McCoy, JM

2009-01-01

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards. PMID:20351875

A recommendation algorithm for automating corollary order generation.

PubMed

Klann, Jeffrey; Schadow, Gunther; McCoy, J M

2009-11-14

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards.

Clinical decision making in a high-risk primary care environment: a qualitative study in the UK.

PubMed

Balla, John; Heneghan, Carl; Thompson, Matthew; Balla, Margaret

2012-01-01

Examine clinical reasoning and decision making in an out of hours (OOH) primary care setting to gain insights into how general practitioners (GPs) make clinical decisions and manage risk in this environment. Semi-structured interviews using open-ended questions. A 2-month qualitative interview study conducted in Oxfordshire, UK. 21 GPs working in OOH primary care. The most powerful themes to emerge related to dealing with urgent potentially high-risk cases, keeping patients safe and responding to their needs, while trying to keep patients out of hospital and the concept of 'fire fighting'. There were a number of well-defined characteristics that GPs reported making presentations easy or difficult to deal with. Severely ill patients were straightforward, while the older people, with complex multisystem diseases, were often difficult. GPs stopped collecting clinical information and came to clinical decisions when high-risk disease and severe illness requiring hospital attention has been excluded; they had responded directly to the patient's needs and there was a reliable safety net in place. Learning points that GPs identified as important for trainees in the OOH setting included the importance of developing rapport in spite of time pressures, learning to deal with uncertainty and learning about common presentations with a focus on critical cues to exclude severe illness. The findings support suggestions that improvements in primary care OOH could be achieved by including automated and regular timely feedback system for GPs and individual peer and expert clinician support for GPs with regular meetings to discuss recent cases. In addition, trainee support and mentoring to focus on clinical skills, knowledge and risk management issues specific to OOH is currently required. Investigating the stopping rules used for diagnostic closure may provide new insights into the root causes of clinical error in such a high-risk setting.

Collaborative Brain-Computer Interface for Aiding Decision-Making

PubMed Central

Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

2014-01-01

We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

Does the cost function matter in Bayes decision rule?

PubMed

Schlü ter, Ralf; Nussbaum-Thom, Markus; Ney, Hermann

2012-02-01

In many tasks in pattern recognition, such as automatic speech recognition (ASR), optical character recognition (OCR), part-of-speech (POS) tagging, and other string recognition tasks, we are faced with a well-known inconsistency: The Bayes decision rule is usually used to minimize string (symbol sequence) error, whereas, in practice, we want to minimize symbol (word, character, tag, etc.) error. When comparing different recognition systems, we do indeed use symbol error rate as an evaluation measure. The topic of this work is to analyze the relation between string (i.e., 0-1) and symbol error (i.e., metric, integer valued) cost functions in the Bayes decision rule, for which fundamental analytic results are derived. Simple conditions are derived for which the Bayes decision rule with integer-valued metric cost function and with 0-1 cost gives the same decisions or leads to classes with limited cost. The corresponding conditions can be tested with complexity linear in the number of classes. The results obtained do not make any assumption w.r.t. the structure of the underlying distributions or the classification problem. Nevertheless, the general analytic results are analyzed via simulations of string recognition problems with Levenshtein (edit) distance cost function. The results support earlier findings that considerable improvements are to be expected when initial error rates are high.

Flu Diagnosis System Using Jaccard Index and Rough Set Approaches

NASA Astrophysics Data System (ADS)

Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip

2018-04-01

Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.

Orthogonal search-based rule extraction for modelling the decision to transfuse.

PubMed

Etchells, T A; Harrison, M J

2006-04-01

Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search-based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100-mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on-going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb < 94 g x l(-1); 2. ROTH > 13 mm and Hb < 87 g x l(-1); 3. ROTH > 38 mm, Hb < 102 g x l(-1) and OGH; 4. Hb < 78 g x l(-1).

Court upholds limits on second-trimester abortions.

PubMed

1979-08-01

On May 21 a New Jersey superior court ruled that regulations limiting the performance of 2nd trimester abortions on an outpatient basis are within a state's purview. This decision upholds the "termination of pregnancy rule" issued by the New Jersey State Board of Medical Examiners in 1978. This rule provides that beyond the 1st trimester and within a period not exceeding 16 menstrual weeks and/or 14 gestational weeks, abortions by the dilation and evacuation method may be performed in a hopsital or licensed clinic on an outpatient basis. 2nd trimester abortions performed by any other method or beyond the specific period must be performed in a hospital on an inpatient basis. Responding to the argument that the regulation unconstitutionally infringed on a woman's right to seek an abortion, the court maintained, pursuant to Roe v. Wade, that beyond the 1st trimester, the state has a "compelling" interest in safeguarding the woman's health and safety and may issue regulations "reasonably related" to realizing that interest.

How power influences moral thinking.

PubMed

Lammers, Joris; Stapel, Diederik A

2009-08-01

The authors conducted 5 studies to test the idea that both thinking about and having power affects the way in which people resolve moral dilemmas. It is shown that high power increases the use of rule-based (deontological) moral thinking styles, whereas low power increases reliance on outcome-based (consequentialist) moral thinking. Stated differently, in determining whether an act is right or wrong, the powerful focus on whether rules and principles are violated, whereas the powerless focus on the consequences. For this reason, the powerful are also more inclined to stick to the rules, irrespective of whether this has positive or negative effects, whereas the powerless are more inclined to make exceptions. The first 3 experiments show that thinking about power increases rule-based thinking and decreases outcome-based thinking in participants' moral decision making. A 4th experiment shows the mediating role of moral orientation in the effect of power on moral decisions. The 5th experiment demonstrates the role of self-interest by showing that the power-moral link is reversed when rule-based decisions threaten participants' own self-interests.

Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.

PubMed

Benaliouche, Houda; Touahria, Mohamed

2014-01-01

This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint

PubMed Central

Benaliouche, Houda; Touahria, Mohamed

2014-01-01

This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results. PMID:24605065

75 FR 57188 - Rhode Island: Final Authorization of State Hazardous Waste Management Program Revisions

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-20

... regarding EPA's Zinc Fertilizer Rule in a separate final rule (following the proposed rule) as it... the Zinc Fertilizer Rule. Today's action responds to that comment but does not agree with it and, thus, finalizes the Agency's decision to authorize Rhode Island for EPA's Zinc Fertilizer Rule. In addition, the...

Clinical evaluation of the first medical whole blood, point-of-care testing device for detection of myocardial infarction.

PubMed

Apple, F S; Anderson, F P; Collinson, P; Jesse, R L; Kontos, M C; Levitt, M A; Miller, E A; Murakami, M M

2000-10-01

Validation of whole blood, point-of-care testing devices for monitoring cardiac markers to aid clinicians in ruling in and ruling out myocardial infarction (MI) is necessary for both laboratory and clinical acceptance. This study evaluated the clinical diagnostic sensitivity and specificity of the First Medical Cardiac Test device operated by nursing and laboratory personnel that simultaneously measures cardiac troponin I (cTnI), creatine kinase (CK) MB, myoglobin, and total CK on the Alpha Dx analyzer in whole blood for detection of MI. Over a 6-month period, 369 patients initially presenting to the emergency department with chest pain were evaluated for MI using modified WHO criteria. Eighty-nine patients (24%) were diagnosed with MI. In whole blood samples collected at admission and at 3- to 6-h intervals over 24 h, ROC curve-determined MI decision limits were as follows: cTnI, 0.4 microgram/L; CKMB, 7.0 microgram/L; myoglobin, 180 microgram/L; total CK, 190 microgram/L. Based on peak concentrations within 24 h after presentation, the following sensitivities (+/- 95% confidence intervals) were found: cTnI, 93% +/- 5.5%; myoglobin, 81% +/- 9.7%; CKMB, 90% +/- 6.3%; total CK, 86% +/- 7.5%. Sensitivities were maximal at >90% for both cTnI and CKMB at >12 h in MI patients, without differences between ST-segment elevation and non-ST-segment elevation MI patients. The First Medical point-of-care device provides cardiac marker assays that can be used by laboratories and clinicians in a variety of hospital settings for ruling in and ruling out MI.

Differentiated Jurisprudence? Examining Students' Fourth Amendment Court Decisions by Region of Country

ERIC Educational Resources Information Center

Torres, Mario S., Jr.

2012-01-01

This study examined federal and state court decisions related to student Fourth Amendment rights following the "New Jersey v. T.L.O." ruling in 1985. There has been minimal research in judicial treatment of students' Fourth Amendment rights across regions of the country and less to what extent regional rulings implicitly or explicitly…

An Intelligent Decision Support System for Workforce Forecast

DTIC Science & Technology

2011-01-01

ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models

Brain Regions Involved in the Learning and Application of Reward Rules in a Two-Deck Gambling Task

ERIC Educational Resources Information Center

Hartstra, E.; Oldenburg, J. F. E.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

2010-01-01

Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits…

EDRN Breast and Ovary Cancer CVC, Study 3: Phase 3 Validation of screening decision rules in preclinical UKCTOCS serial samples — EDRN Public Portal

Cancer.gov

We will collaborate with investigators from University College London to test a screening decision rule in preclinical serial samples from the U.K. Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) to learn if the panel can do better than CA125 alone. The UKCTOCS is an ideal setting for retrospective validation of an early detection marker panel and decision rule because it offers serial samples collected annually and use of imaging in women with rising CA125. Multi-modal strategies using serum markers HE4, MSLN, MMP7, and CA125 will be compared to strategies relying exclusively on CA125 and transvaginal sonography (TVS).

Decision rules for unbiased inventory estimates

NASA Technical Reports Server (NTRS)

Argentiero, P. D.; Koch, D.

1979-01-01

An efficient and accurate procedure for estimating inventories from remote sensing scenes is presented. In place of the conventional and expensive full dimensional Bayes decision rule, a one-dimensional feature extraction and classification technique was employed. It is shown that this efficient decision rule can be used to develop unbiased inventory estimates and that for large sample sizes typical of satellite derived remote sensing scenes, resulting accuracies are comparable or superior to more expensive alternative procedures. Mathematical details of the procedure are provided in the body of the report and in the appendix. Results of a numerical simulation of the technique using statistics obtained from an observed LANDSAT scene are included. The simulation demonstrates the effectiveness of the technique in computing accurate inventory estimates.

Development, Evaluation and Implementation of Chief Complaint Groupings to Activate Data Collection: A Multi-Center Study of Clinical Decision Support for Children with Head Trauma.

PubMed

Deakyne, S J; Bajaj, L; Hoffman, J; Alessandrini, E; Ballard, D W; Norris, R; Tzimenatos, L; Swietlik, M; Tham, E; Grundmeier, R W; Kuppermann, N; Dayan, P S

2015-01-01

Overuse of cranial computed tomography scans in children with blunt head trauma unnecessarily exposes them to radiation. The Pediatric Emergency Care Applied Research Network (PECARN) blunt head trauma prediction rules identify children who do not require a computed tomography scan. Electronic health record (EHR) based clinical decision support (CDS) may effectively implement these rules but must only be provided for appropriate patients in order to minimize excessive alerts. To develop, implement and evaluate site-specific groupings of chief complaints (CC) that accurately identify children with head trauma, in order to activate data collection in an EHR. As part of a 13 site clinical trial comparing cranial computed tomography use before and after implementation of CDS, four PECARN sites centrally developed and locally implemented CC groupings to trigger a clinical trial alert (CTA) to facilitate the completion of an emergency department head trauma data collection template. We tested and chose CC groupings to attain high sensitivity while maintaining at least moderate specificity. Due to variability in CCs available, identical groupings across sites were not possible. We noted substantial variability in the sensitivity and specificity of seemingly similar CC groupings between sites. The implemented CC groupings had sensitivities greater than 90% with specificities between 75-89%. During the trial, formal testing and provider feedback led to tailoring of the CC groupings at some sites. CC groupings can be successfully developed and implemented across multiple sites to accurately identify patients who should have a CTA triggered to facilitate EHR data collection. However, CC groupings will necessarily vary in order to attain high sensitivity and moderate-to-high specificity. In future trials, the balance between sensitivity and specificity should be considered based on the nature of the clinical condition, including prevalence and morbidity, in addition to the goals of the intervention being considered.

The Ottawa Knee Rule: Examining Use in an Academic Emergency Department

PubMed Central

Beutel, Bryan G.; Trehan, Samir K.; Shalvoy, Robert M.; Mello, Michael J.

2012-01-01

Introduction: The Ottawa Knee Rule is a validated clinical decision rule for determining whether knee radiographs should be obtained in the setting of acute knee trauma. The objectives of this study were to assess physician knowledge of, barriers to implementation of, and compliance with the Ottawa Knee Rule in academic emergency departments (EDs), and evaluate whether patient characteristics predict guideline noncompliance. Methods: A 10 question online survey was distributed to all attending ED physicians working at three affiliated academic EDs to assess knowledge, attitudes and self-reported practice behaviors related to the Ottawa Knee Rule. We also performed a retrospective ED record review of patients 13 years of age and older who presented with acute knee trauma to the 3 study EDs during the 2009 calendar year, and we analyzed ED records for 19 variables. Results: ED physicians (n = 47) correctly answered 73.2% of questions assessing knowledge of the Ottawa Knee Rule. The most commonly cited barriers to implementation were “patient expectations” and system issues, such as “orthopedics referral requirement.” We retrospectively reviewed 838 records, with 260 eligible for study inclusion. The rate of Ottawa Knee Rule compliance was retrospectively determined to be 63.1%. We observed a statistically significant correlation between Ottawa Knee Rule compliance and patient age, but not gender, insurance status, or provider type, among others. Conclusion: Compliance with the Ottawa Knee Rule among academic ED healthcare providers is poor, which was predicted by patient age and not other physician or patient variables. Improving compliance will require comprehensive educational and systemic interventions. PMID:23251717

Simply criminal: predicting burglars' occupancy decisions with a simple heuristic.

PubMed

Snook, Brent; Dhami, Mandeep K; Kavanagh, Jennifer M

2011-08-01

Rational choice theories of criminal decision making assume that offenders weight and integrate multiple cues when making decisions (i.e., are compensatory). We tested this assumption by comparing how well a compensatory strategy called Franklin's Rule captured burglars' decision policies regarding residence occupancy compared to a non-compensatory strategy (i.e., Matching Heuristic). Forty burglars each decided on the occupancy of 20 randomly selected photographs of residences (for which actual occupancy was known when the photo was taken). Participants also provided open-ended reports on the cues that influenced their decisions in each case, and then rated the importance of eight cues (e.g., deadbolt visible) over all decisions. Burglars predicted occupancy beyond chance levels. The Matching Heuristic was a significantly better predictor of burglars' decisions than Franklin's Rule, and cue use in the Matching Heuristic better corresponded to the cue ecological validities in the environment than cue use in Franklin's Rule. The most important cue in burglars' models was also the most ecologically valid or predictive of actual occupancy (i.e., vehicle present). The majority of burglars correctly identified the most important cue in their models, and the open-ended technique showed greater correspondence between self-reported and captured cue use than the rating over decision technique. Our findings support a limited rationality perspective to understanding criminal decision making, and have implications for crime prevention.

Exploring perceptions and experiences of patients who have chronic pain as state prescription opioid policies change: a qualitative study in Indiana

PubMed Central

Al Achkar, Morhaf; Revere, Debra; Dennis, Barbara; MacKie, Palmer; Gupta, Sumedha; Grannis, Shaun

2017-01-01

Objectives The misuse and abuse of prescription opioids (POs) is an epidemic in the USA today. Many states have implemented legislation to curb the use of POs resulting from inappropriate prescribing. Indiana legislated opioid prescribing rules that went into effect in December 2013. The rules changed how chronic pain is managed by healthcare providers. This qualitative study aims to evaluate the impact of Indiana’s opioid prescription legislation on the patient experiences around pain management. Setting This is a qualitative study using interviews of patient and primary care providers to obtain triangulated data sources. The patients were recruited from an integrated pain clinic to which chronic pain patients were referred from federally qualified health clinics (FQHCs). The primacy care providers were recruited from the same FQHCs. The study used inductive, emergent thematic analysis. Participants Nine patient participants and five primary care providers were included in the study. Results Living with chronic pain is disruptive to patients’ lives on multiple dimensions. The established pain management practices were disrupted by the change in prescription rules. Patient–provider relationships, which involve power dynamics and decision making, shifted significantly in parallel to the rule change. Conclusions As a result of the changes in pain management practice, some patients experienced significant challenges. Further studies into the magnitude of this change are necessary. In addition, exploring methods for regulating prescribing while assuring adequate access to pain management is crucial. PMID:29133312

Implementation science: a role for parallel dual processing models of reasoning?

PubMed Central

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-01-01

Background A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Discussion Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. Summary It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice. PMID:16725023

Implementation science: a role for parallel dual processing models of reasoning?

PubMed

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-05-25

A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice.

Integration of Hospital Information and Clinical Decision Support Systems to Enable the Reuse of Electronic Health Record Data.

PubMed

Kopanitsa, Georgy

2017-05-18

The efficiency and acceptance of clinical decision support systems (CDSS) can increase if they reuse medical data captured during health care delivery. High heterogeneity of the existing legacy data formats has become the main barrier for the reuse of data. Thus, we need to apply data modeling mechanisms that provide standardization, transformation, accumulation and querying medical data to allow its reuse. In this paper, we focus on the interoperability issues of the hospital information systems (HIS) and CDSS data integration. Our study is based on the approach proposed by Marcos et al. where archetypes are used as a standardized mechanism for the interaction of a CDSS with an electronic health record (EHR). We build an integration tool to enable CDSSs collect data from various institutions without a need for modifications in the implementation. The approach implies development of a conceptual level as a set of archetypes representing concepts required by a CDSS. Treatment case data from Regional Clinical Hospital in Tomsk, Russia was extracted, transformed and loaded to the archetype database of a clinical decision support system. Test records' normalization has been performed by defining transformation and aggregation rules between the EHR data and the archetypes. These mapping rules were used to automatically generate openEHR compliant data. After the transformation, archetype data instances were loaded into the CDSS archetype based data storage. The performance times showed acceptable performance for the extraction stage with a mean of 17.428 s per year (3436 case records). The transformation times were also acceptable with 136.954 s per year (0.039 s per one instance). The accuracy evaluation showed the correctness and applicability of the method for the wide range of HISes. These operations were performed without interrupting the HIS workflow to prevent the HISes from disturbing the service provision to the users. The project results have proven that archetype based technologies are mature enough to be applied in routine operations that require extraction, transformation, loading and querying medical data from heterogeneous EHR systems. Inference models in clinical research and CDSS can benefit from this by defining queries to a valid data set with known structure and constraints. The standard based nature of the archetype approach allows an easy integration of CDSSs with existing EHR systems.

Empirical study on voting power in participatory forest planning.

PubMed

Vainikainen, N; Kangas, A; Kangas, J

2008-07-01

Multicriteria decision support systems are applied in natural resource management in order to clarify the planning process for the stakeholders, to make all available information usable and all objectives manageable. Especially when the public is involved in planning, the decision support system should be easy to comprehend, transparent and fair. Social choice theory has recently been applied to group decision-making in natural resources management to accomplish these objectives. Although voting forms the basis of democracy, and is usually taken as a fair method, the influence of voters over the outcome may vary. It is also possible to vote strategically to improve the results from each stakeholder's point of view. This study examines the use of social choice theory in revealing stakeholders' preferences in participatory forest planning, and the influence of different voters on the outcome. The positional voting rules examined were approval voting and Borda count, but both rules were slightly modified for the purposes of this study. The third rule examined, cumulative rule, resembles utilitarian voting rules. The voting rules were tested in a real participatory forest planning situation in eastern Lapland, Finland. All voting rules resulted in a different joint order of importance of the criteria. Yet, the preference orders produced had also a lot in common and the criteria could be divided into three quite distinct groups according to their importance. The influence of individual voters varied between the voting rules, and in each case different voter was the most influential.

Minimum Equipment Lists, Flight Rules and ... Past, Present and Future of Safety Pre-Determined Decisions for Operations

NASA Astrophysics Data System (ADS)

Herd, A.; Wolff, M.

2012-01-01

Extended mission operations, such as human spaceflight to Mars provide an opportunity for take current human exploration beyond Low Earth Orbit, such as the operations undertaken on the International Space Station (ISS). This opportunity also presents a challenge in terms of extending what we currently understand as "remote operations" performed on ISS, offering learning beyond that gained from the successful moon- lander expeditions. As such there is a need to assess how the existing operations concept of ground support teams directing (and supporting) on-orbit ISS operations can be applied in the extended mission concept. The current mission support concept involves three interacting operations products - a short term plan, crew procedures and flight rules. Flight rules (for ISS operations) currently provide overall planning, engineering and operations constraints (including those derived from a safety perspective) in the form of a rule book. This paper will focus specifically on flight rules, and describe the current use of them, and assess the future role of flight rules to support exploration, including the deployment of decision support tools (DSTs) to ensure flight rule compliancy for missions with minimal ground support. Taking consideration of the historical development of pre-planned decisions, and their manifestation within the operations environment, combined with the extended remoteness of human exploration missions, we will propose a future development of this product and a platform on which it could be presented.

75 FR 492 - Self-Regulatory Organizations; Municipal Securities Rulemaking Board; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-05

... decisions. The MSRB is firmly of the belief that the proposed rule change is within its statutory authority... Proposed Rule Change Relating to Rule G-32, on Disclosures in Connection With Primary Offerings, Form G-32... proposed rule change relating to Rule G-32, on disclosures in connection with primary offerings, Form G-32...

Discrepant feeling rules and unscripted emotion work: women coping with termination for fetal anomaly.

PubMed

McCoyd, Judith L M

2009-10-01

The sociology of emotion is rapidly evolving and has implications for medical settings. Advancing medical technologies create new contexts for decision-making and emotional reaction that are framed by "feeling rules." Feeling rules guide not only behavior, but also how one believes one should feel, thereby causing one to attempt to bring one's authentic feelings into line with perceived feeling rules. Using qualitative data, the theoretical existence of feeling rules in pregnancy and prenatal testing is confirmed. Further examination extends this analysis: at times of technological development feeling rules are often discrepant, leaving patients with unscripted emotion work. Data from a study of women who interrupted anomalous pregnancies indicate that feeling rules are unclear when competing feeling rules are operating during times of societal and technological change. Because much of this occurs below the level of consciousness, medical and psychological services providers need to be aware of potential discrepancies in feeling rules and assist patients in identifying the salient feeling rules. Patients' struggles ease when they can recognize the discrepancies and assess their implications for decision-making and emotional response. (c) 2009 APA, all rights reserved.

75 FR 55842 - Self-Regulatory Organizations; Financial Industry Regulatory Authority; Order Granting Approval...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-14

... specified in the proposed rule: i. Clarify the time frames within which members must take action to effect... a final decision of a FINRA officer or the UPC Committee under NASD Rule 11890 (Clearly Erroneous... refusal by a member to take action necessary to effectuate a final decision of a FINRA officer or the UPC...

The Supreme Court Spanking Ruling: An Issue in Debate.

ERIC Educational Resources Information Center

Welsh, Ralph S.; And Others

Few issues have polarized the educational community so completely as the 1975 and 1977 decisions by the U.S. Supreme Court to allow corporal punishment in the schools. The symposium reported here was organized and conducted following the 1975 decision but prior to the 1977 one. Three papers in support and three papers against the ruling were read,…

10 CFR 501.102 - OFE evaluation of the record, decision and order for modification or rescission of a rule or order.

Code of Federal Regulations, 2010 CFR

2010-01-01

... a conference will advance its evaluation of the request. (b) Criteria. Except where modification or... rule or order. (a) OFE will consider the entire administrative record in its evaluation of the decision... request under this subpart and all interested persons will be afforded an opportunity to respond to these...

Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models.

PubMed

Garibaldi, Jonathan M; Zhou, Shang-Ming; Wang, Xiao-Ying; John, Robert I; Ellis, Ian O

2012-06-01

It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variability when making difficult decisions. In contrast, the vast majority of computerized models that aim to provide automated support for such decisions do not explicitly recognize or replicate this variability. Furthermore, the perfect consistency of computerized models is often presented as a de facto benefit. In this paper, we describe a novel approach to incorporate variability within a fuzzy inference system using non-stationary fuzzy sets in order to replicate human variability. We apply our approach to a decision problem concerning the recommendation of post-operative breast cancer treatment; specifically, whether or not to administer chemotherapy based on assessment of five clinical variables: NPI (the Nottingham Prognostic Index), estrogen receptor status, vascular invasion, age and lymph node status. In doing so, we explore whether such explicit modeling of variability provides any performance advantage over a more conventional fuzzy approach, when tested on a set of 1310 unselected cases collected over a fourteen year period at the Nottingham University Hospitals NHS Trust, UK. The experimental results show that the standard fuzzy inference system (that does not model variability) achieves overall agreement to clinical practice around 84.6% (95% CI: 84.1-84.9%), while the non-stationary fuzzy model can significantly increase performance to around 88.1% (95% CI: 88.0-88.2%), p<0.001. We conclude that non-stationary fuzzy models provide a valuable new approach that may be applied to clinical decision support systems in any application domain. Copyright © 2012 Elsevier Inc. All rights reserved.

Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.

PubMed

Naso, David; Turchiano, Biagio

2005-04-01

In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.

Working dogs cooperate among one another by generalised reciprocity.

PubMed

Gfrerer, Nastassja; Taborsky, Michael

2017-03-06

Cooperation by generalised reciprocity implies that individuals apply the decision rule "help anyone if helped by someone". This mechanism has been shown to generate evolutionarily stable levels of cooperation, but as yet it is unclear how widely this cooperation mechanism is applied among animals. Dogs (Canis familiaris) are highly social animals with considerable cognitive potential and the ability to differentiate between individual social partners. But although dogs can solve complex problems, they may use simple rules for behavioural decisions. Here we show that dogs trained in an instrumental cooperative task to provide food to a social partner help conspecifics more often after receiving help from a dog before. Remarkably, in so doing they show no distinction between partners that had helped them before and completely unfamiliar conspecifics. Apparently, dogs use the simple decision rule characterizing generalised reciprocity, although they are probably capable of using the more complex decision rule of direct reciprocity: "help someone who has helped you". However, generalized reciprocity involves lower information processing costs and is therefore a cheaper cooperation strategy. Our results imply that generalised reciprocity might be applied more commonly than direct reciprocity also in other mutually cooperating animals.

Working dogs cooperate among one another by generalised reciprocity

PubMed Central

Gfrerer, Nastassja; Taborsky, Michael

2017-01-01

Cooperation by generalised reciprocity implies that individuals apply the decision rule “help anyone if helped by someone”. This mechanism has been shown to generate evolutionarily stable levels of cooperation, but as yet it is unclear how widely this cooperation mechanism is applied among animals. Dogs (Canis familiaris) are highly social animals with considerable cognitive potential and the ability to differentiate between individual social partners. But although dogs can solve complex problems, they may use simple rules for behavioural decisions. Here we show that dogs trained in an instrumental cooperative task to provide food to a social partner help conspecifics more often after receiving help from a dog before. Remarkably, in so doing they show no distinction between partners that had helped them before and completely unfamiliar conspecifics. Apparently, dogs use the simple decision rule characterizing generalised reciprocity, although they are probably capable of using the more complex decision rule of direct reciprocity: “help someone who has helped you”. However, generalized reciprocity involves lower information processing costs and is therefore a cheaper cooperation strategy. Our results imply that generalised reciprocity might be applied more commonly than direct reciprocity also in other mutually cooperating animals. PMID:28262722

Individual versus Household Migration Decision Rules: Gender and Marital Status Differences in Intentions to Migrate in South Africa

PubMed Central

Gubhaju, Bina; De Jong, Gordon F.

2009-01-01

This research tests the thesis that the neoclassical micro-economic and the new household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame of intention to migrate. Comparative tests of both theories within the same study design are relatively rare. Utilizing data from the Causes of Migration in South Africa national migration survey, we analyze how individually held “own-future” versus alternative “household well-being” migration decision rules effect the intentions to migrate of male and female adults in South Africa. Results from the gender and marital status specific logistic regressions models show consistent support for the different gender-marital status decision rule thesis. Specifically, the “maximizing one’s own future” neoclassical microeconomic theory proposition is more applicable for never married men and women, the “maximizing household income” proposition for married men with short-term migration intentions, and the “reduce household risk” proposition for longer time horizon migration intentions of married men and women. Results provide new evidence on the way household strategies and individual goals jointly affect intentions to move or stay. PMID:20161187

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

PubMed

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Learning temporal rules to forecast instability in continuously monitored patients.

PubMed

Guillame-Bert, Mathieu; Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R

2017-01-01

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Failsafe automation of Phase II clinical trial interim monitoring for stopping rules.

PubMed

Day, Roger S

2010-02-01

In Phase II clinical trials in cancer, preventing the treatment of patients on a study when current data demonstrate that the treatment is insufficiently active or too toxic has obvious benefits, both in protecting patients and in reducing sponsor costs. Considerable efforts have gone into experimental designs for Phase II clinical trials with flexible sample size, usually implemented by early stopping rules. The intended benefits will not ensue, however, if the design is not followed. Despite the best intentions, failures can occur for many reasons. The main goal is to develop an automated system for interim monitoring, as a backup system supplementing the protocol team, to ensure that patients are protected. A secondary goal is to stimulate timely recording of patient assessments. We developed key concepts and performance needs, then designed, implemented, and deployed a software solution embedded in the clinical trials database system. The system has been in place since October 2007. One clinical trial tripped the automated monitor, resulting in e-mails that initiated statistician/investigator review in timely fashion. Several essential contributing activities still require human intervention, institutional policy decisions, and institutional commitment of resources. We believe that implementing the concepts presented here will provide greater assurance that interim monitoring plans are followed and that patients are protected from inadequate response or excessive toxicity. This approach may also facilitate wider acceptance and quicker implementation of new interim monitoring algorithms.

Access control based on attribute certificates for medical intranet applications.

PubMed

Mavridis, I; Georgiadis, C; Pangalos, G; Khair, M

2001-01-01

Clinical information systems frequently use intranet and Internet technologies. However these technologies have emphasized sharing and not security, despite the sensitive and private nature of much health information. Digital certificates (electronic documents which recognize an entity or its attributes) can be used to control access in clinical intranet applications. To outline the need for access control in distributed clinical database systems, to describe the use of digital certificates and security policies, and to propose the architecture for a system using digital certificates, cryptography and security policy to control access to clinical intranet applications. We have previously developed a security policy, DIMEDAC (Distributed Medical Database Access Control), which is compatible with emerging public key and privilege management infrastructure. In our implementation approach we propose the use of digital certificates, to be used in conjunction with DIMEDAC. Our proposed access control system consists of two phases: the ways users gain their security credentials; and how these credentials are used to access medical data. Three types of digital certificates are used: identity certificates for authentication; attribute certificates for authorization; and access-rule certificates for propagation of access control policy. Once a user is identified and authenticated, subsequent access decisions are based on a combination of identity and attribute certificates, with access-rule certificates providing the policy framework. Access control in clinical intranet applications can be successfully and securely managed through the use of digital certificates and the DIMEDAC security policy.

Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

PubMed

Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A

2016-09-01

Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

Yield of computed tomography of the cervical spine in cases of simple assault.

PubMed

Uriell, Matthew L; Allen, Jason W; Lovasik, Brendan P; Benayoun, Marc D; Spandorfer, Robert M; Holder, Chad A

2017-01-01

Computed tomography (CT) of the cervical spine (C-spine) is routinely ordered for low-impact, non-penetrating or "simple" assault at our institution and others. Common clinical decision tools for C-spine imaging in the setting of trauma include the National Emergency X-Radiography Utilization Study (NEXUS) and the Canadian Cervical Spine Rule for Radiography (CCR). While NEXUS and CCR have served to decrease the amount of unnecessary imaging of the C-spine, overutilization of CT is still of concern. A retrospective, cross-sectional study was performed of the electronic medical record (EMR) database at an urban, Level I Trauma Center over a 6-month period for patients receiving a C-spine CT. The primary outcome of interest was prevalence of cervical spine fracture. Secondary outcomes of interest included appropriateness of C-spine imaging after retrospective application of NEXUS and CCR. The hypothesis was that fracture rates within this patient population would be extremely low. No C-spine fractures were identified in the 460 patients who met inclusion criteria. Approximately 29% of patients did not warrant imaging by CCR, and 25% by NEXUS. Of note, approximately 44% of patients were indeterminate for whether imaging was warranted by CCR, with the most common reason being lack of assessment for active neck rotation. Cervical spine CT is overutilized in the setting of simple assault, despite established clinical decision rules. With no fractures identified regardless of other factors, the likelihood that a CT of the cervical spine will identify clinically significant findings in the setting of "simple" assault is extremely low, approaching zero. At minimum, adherence to CCR and NEXUS within this patient population would serve to reduce both imaging costs and population radiation dose exposure. Copyright © 2016 Elsevier Ltd. All rights reserved.

"Send & hold" clinical decision support rules improvement to reduce unnecessary testing of vitamins A, E, K, B1, B2, B3, B6 and C.

PubMed

Rodriguez-Borja, Enrique; Corchon-Peyrallo, Africa; Barba-Serrano, Esther; Villalba Martínez, Celia; Carratala Calvo, Arturo

2018-06-27

We assessed the impact of several "send & hold" clinical decision support rules (CDSRs) within the electronical request system for vitamins A, E, K, B1, B2, B3, B6 and C for all outpatients at a large health department. When ordered through electronical request, providers (except for all our primary care physicians who worked as a non-intervention control group) were always asked to answer several compulsory questions regarding main indication, symptomatology, suspected diagnosis, vitamin active treatments, etc., for each vitamin test using a drop-down list format. After samples arrival, tests were later put on hold internally by our laboratory information system (LIS) until review for their appropriateness was made by two staff pathologists according to the provided answers and LIS records (i.e. "send & hold"). The number of tests for each analyte was compared between the 10-month period before and after CDSRs implementation in both groups. After implementation, vitamins test volumes decreased by 40% for vitamin A, 29% for vitamin E, 42% for vitamin K, 37% for vitamin B1, 85% for vitamin B2, 68% for vitamin B3, 65% for vitamin B6 and 59% for vitamin C (all p values 0.03 or lower except for vitamin B3), whereas in control group, the majority increased or remained stable. In patients with rejected vitamins, no new requests and/or adverse clinical outcome comments due to this fact were identified. "Send & hold" CDSRs are a promising informatics tool that can support in utilization management and enhance the pathologist's leadership role as tests specialist.

Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.

PubMed

Wilk, Szymon; Kezadri-Hamiaz, Mounira; Rosu, Daniela; Kuziemsky, Craig; Michalowski, Wojtek; Amyot, Daniel; Carrier, Marc

2016-02-01

In healthcare organizations, clinical workflows are executed by interdisciplinary healthcare teams (IHTs) that operate in ways that are difficult to manage. Responding to a need to support such teams, we designed and developed the MET4 multi-agent system that allows IHTs to manage patients according to presentation-specific clinical workflows. In this paper, we describe a significant extension of the MET4 system that allows for supporting rich team dynamics (understood as team formation, management and task-practitioner allocation), including selection and maintenance of the most responsible physician and more complex rules of selecting practitioners for the workflow tasks. In order to develop this extension, we introduced three semantic components: (1) a revised ontology describing concepts and relations pertinent to IHTs, workflows, and managed patients, (2) a set of behavioral rules describing the team dynamics, and (3) an instance base that stores facts corresponding to instances of concepts from the ontology and to relations between these instances. The semantic components are represented in first-order logic and they can be automatically processed using theorem proving and model finding techniques. We employ these techniques to find models that correspond to specific decisions controlling the dynamics of IHT. In the paper, we present the design of extended MET4 with a special focus on the new semantic components. We then describe its proof-of-concept implementation using the WADE multi-agent platform and the Z3 solver (theorem prover/model finder). We illustrate the main ideas discussed in the paper with a clinical scenario of an IHT managing a patient with chronic kidney disease.

76 FR 18383 - Extension of Sunset Date for Attorney Advisor Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-04

... rule. SUMMARY: We are extending for 2 years our rule authorizing attorney advisors to conduct certain prehearing procedures and to issue fully favorable decisions. The current rule will expire on August 10, 2011... would end on August 10, 2009, unless we decided either to terminate the rule earlier or to extend it...

Ventral Striatum and the Evaluation of Memory Retrieval Strategies

PubMed Central

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M.; Scimeca, Jason M.

2015-01-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant’s subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies. PMID:24564466

General practitioner diagnosis and management of acute knee injuries: summary of an evidence-based guideline.

PubMed

Robb, Gillian; Reid, Duncan; Arroll, Bruce; Jackson, Rod T; Goodyear-Smith, Felicity

2007-02-16

To summarise evidence and key recommendations for general practitioner diagnosis and management of acute soft-tissue knee injuries, based on the New Zealand guideline. A multidisciplinary team developed the guideline by critically appraising and grading retrieved literature using the Graphic Appraisal Tools for Epidemiology, Clinical decision rules and the Scottish Intercollegiate Guideline Network. Recommendations were derived from resulting evidence tables. For both diagnosis and management there is a paucity of good evidence to support diagnosis and treatment of internal derangements of the knee, hence some aspects of the guideline are guideline team consensus. Good evidence supports the use of the Ottawa Knee rules to guide decisions about the use of X-ray, and the Lachman test in diagnosing anterior cruciate ligament (ACL) tears. Evidence supports inclusion of proprioceptive training in rehabilitation programmes following ACL reconstruction and in people with ACL-deficient knees. There is good evidence that ultrasound is of little benefit, and there is no evidence that physiotherapy be routinely advocated following meniscectomy. This guideline provides an evidence-based framework for diagnosis and management of internal derangements of the knee following acute injury. Moreover, its development highlights significant gaps in the evidence base and identifies priorities for new research.

[Mild head injury in children and adults: Diagnostic challenges in the emergency department].

PubMed

Leidel, B A; Lindner, T; Wolf, S; Bogner, V; Steinbeck, A; Börner, N; Peiser, C; Audebert, H J; Biberthaler, P; Kanz, K-G

2015-06-01

Mild head injuries are one of the most frequent reasons for attending emergency departments and are particularly challenging in different ways. While clinically important injuries are infrequent, delayed or missed injuries may lead to fatal consequences. The initial mostly inconspicuous appearance may not reflect the degree of intracranial injury and computed tomography (CT) is necessary to rule out covert injuries. Furthermore, infants and young children with a lack of or rudimentary cognitive and language development are challenging, especially for those examiners not familiar with pediatric care. Established check lists of clinical risk factors for children and adults regarding traumatic brain injuries allow specific and rational decision-making for cranial CT imaging. Clinically important intracranial injuries can be reliably detected and unnecessary radiation exposure avoided at the same time.

[Mild head injury in children and adults. Diagnostic challenges in the emergency department].

PubMed

Leidel, B A; Lindner, T; Wolf, S; Bogner, V; Steinbeck, A; Börner, N; Peiser, C; Audebert, H J; Biberthaler, P; Kanz, K-G

2015-01-01

Mild head injuries are one of the most frequent reasons for attending emergency departments and are particularly challenging in different ways. While clinically important injuries are infrequent, delayed or missed injuries may lead to fatal consequences. The initial mostly inconspicuous appearance may not reflect the degree of intracranial injury and computed tomography (CT) is necessary to rule out covert injuries. Furthermore, infants and young children with a lack of or rudimentary cognitive and language development are challenging, especially for those examiners not familiar with pediatric care. Established check lists of clinical risk factors for children and adults regarding traumatic brain injuries allow specific and rational decision-making for cranial CT imaging. Clinically important intracranial injuries can be reliably detected and unnecessary radiation exposure avoided at the same time.

Supreme Court refuses to review clinic access law; Second Appeals Court upholds statute.

PubMed

1995-06-30

On June 19, the US Supreme Court refused to review "Woodall v. Reno," a challenge to the Freedom of Access to Clinic Entrances Act (FACE) filed in Virginia by an anti-choice individual. FACE prohibits the use of force, threat of force, or physical obstruction to intentionally injure, intimidate, or interfere with anyone providing or obtaining reproductive health services. By denying the petition for "certiorari," the High Court let stand the US Court of Appeals for the Fourth Circuit decision in February. In that ruling, the midlevel federal court affirmed a lower court's dismissal of two of the eight anti-choice lawsuits challenging FACE, "Woodall v. Reno" and "American Life League v. Reno," which were consolidated by the appeals panel. Although plaintiffs in the first case filed a request for review by the High Court within days of the appellate court ruling, plaintiffs in the latter case waited until May to do so. The Department of Justice, which is defending the federal statute, and CRLP and the NOW Legal Defense and Education Fund, who are intervening on behalf of women and health care providers, will file their opposition to the review by July 26. The Justices will then decide to hear the case. On June 23, a three-judge panel for the US Court of Appeals for the Eleventh Circuit affirmed a lower court's decision to dismiss "Cheffer v. Reno," a facial challenge by Florida anti-choice activists seeking to invalidate FACE. The appeals court had ruled the law did not infringe on First Amendment rights, and the panel rejected the argument that Congress had exceeded its authority under the Commerce Clause of the US Constitution by finding that the measure "protects and regulates commercial enterprises." The appeals court accepted an "amicus" brief filed by CRLP and NOW Legal Defense and Education Fund on behalf of the National Abortion Federation, the National Organization of Women, physicians, and women's health clinics, but denied their request to intervene in the case. Seven federal courts in addition to the US Courts of Appeals for the Fourth and Eleventh Circuits, have found FACE to be constitutional; one has not.

Decision support from local data: creating adaptive order menus from past clinician behavior.

PubMed

Klann, Jeffrey G; Szolovits, Peter; Downs, Stephen M; Schadow, Gunther

2014-04-01

Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based Clinical Decision Support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian Network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the Urgent Visit Clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. A short order menu on average contained the next order (weighted average length 3.91-5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714-.844 (depending on domain). However, AUC had high variance (.50-.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an Association Rule Mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. Copyright © 2013 Elsevier Inc. All rights reserved.

Decision Support from Local Data: Creating Adaptive Order Menus from Past Clinician Behavior

PubMed Central

Klann, Jeffrey G.; Szolovits, Peter; Downs, Stephen; Schadow, Gunther

2014-01-01

Objective Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based clinical decision support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. Materials and Methods We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the urgent visit clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. Results A short order menu on average contained the next order (weighted average length 3.91–5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714–.844 (depending on domain). However, AUC had high variance (.50–.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an association rule mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. Discussion and Conclusion This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. PMID:24355978

Choosing the Rules: Distinct and Overlapping Frontoparietal Representations of Task Rules for Perceptual Decisions

PubMed Central

Kriegeskorte, Nikolaus; Carlin, Johan D.; Rowe, James B.

2013-01-01

Behavior is governed by rules that associate stimuli with responses and outcomes. Human and monkey studies have shown that rule-specific information is widely represented in the frontoparietal cortex. However, it is not known how establishing a rule under different contexts affects its neural representation. Here, we use event-related functional MRI (fMRI) and multivoxel pattern classification methods to investigate the human brain's mechanisms of establishing and maintaining rules for multiple perceptual decision tasks. Rules were either chosen by participants or specifically instructed to them, and the fMRI activation patterns representing rule-specific information were compared between these contexts. We show that frontoparietal regions differ in the properties of their rule representations during active maintenance before execution. First, rule-specific information maintained in the dorsolateral and medial frontal cortex depends on the context in which it was established (chosen vs specified). Second, rule representations maintained in the ventrolateral frontal and parietal cortex are independent of the context in which they were established. Furthermore, we found that the rule-specific coding maintained in anticipation of stimuli may change with execution of the rule: representations in context-independent regions remain invariant from maintenance to execution stages, whereas rule representations in context-dependent regions do not generalize to execution stage. The identification of distinct frontoparietal systems with context-independent and context-dependent task rule representations, and the distinction between anticipatory and executive rule representations, provide new insights into the functional architecture of goal-directed behavior. PMID:23864675

Simultaneous Optimization of Decisions Using a Linear Utility Function.

ERIC Educational Resources Information Center

Vos, Hans J.

1990-01-01

An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)

49 CFR 1503.655 - Initial decision.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Rules of Practice in TSA Civil Penalty Actions § 1503.655 Initial decision. (a) Contents. The ALJ may... copies of that initial decision available to all parties and the TSA decision maker. (b) Written decision... ALJ is persuasive authority in any other civil penalty action, unless appealed and reversed by the TSA...

20 CFR 501.6 - Decisions and orders.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Decisions and orders. 501.6 Section 501.6 Employees' Benefits EMPLOYEES' COMPENSATION APPEALS BOARD, DEPARTMENT OF LABOR RULES OF PROCEDURE § 501.6 Decisions and orders. (a) Decisions. A decision of the Board will contain a written opinion setting forth...

Decentralisation of Health Services in Fiji: A Decision Space Analysis.

PubMed

Mohammed, Jalal; North, Nicola; Ashton, Toni

2015-11-15

Decentralisation aims to bring services closer to the community and has been advocated in the health sector to improve quality, access and equity, and to empower local agencies, increase innovation and efficiency and bring healthcare and decision-making as close as possible to where people live and work. Fiji has attempted two approaches to decentralisation. The current approach reflects a model of deconcentration of outpatient services from the tertiary level hospital to the peripheral health centres in the Suva subdivision. Using a modified decision space approach developed by Bossert, this study measures decision space created in five broad categories (finance, service organisation, human resources, access rules, and governance rules) within the decentralised services. Fiji's centrally managed historical-based allocation of financial resources and management of human resources resulted in no decision space for decentralised agents. Narrow decision space was created in the service organisation category where, with limited decision space created over access rules, Fiji has seen greater usage of its decentralised health centres. There remains limited decision space in governance. The current wave of decentralisation reveals that, whilst the workload has shifted from the tertiary hospital to the peripheral health centres, it has been accompanied by limited transfer of administrative authority, suggesting that Fiji's deconcentration reflects the transfer of workload only with decision-making in the five functional areas remaining largely centralised. As such, the benefits of decentralisation for users and providers are likely to be limited. © 2016 by Kerman University of Medical Sciences.

Impact of managed care on physicians' decisions to manipulate reimbursement rules: an explanatory model.

PubMed

VanGeest, Jonathan; Weiner, Saul; Johnson, Timothy; Cummins, Deborah

2007-07-01

To develop and test an explanatory model of the impact of managed care on physicians' decisions to manipulate reimbursement rules for patients. A self-administered mailed questionnaire of a national random sample of 1124 practicing physicians in the USA. Structural equation modelling was used. The main outcome measure assessed whether or not physicians had manipulated reimbursement rules (such as exaggerated the severity of patients conditions, changed billing diagnoses, or reported signs or symptoms that the patients did not have) to help patients secure coverage for needed treatment or services. The response rate was 64% (n = 720). Physicians' decisions to manipulate reimbursement rules for patients are directly driven not only by ethical beliefs about gaming the system but also by requests from patients, the perception of insufficient time to deliver care, and the proportion of Medicaid patients. Covert advocacy is also the indirect result of utilization review hassles, primary care specialty, and practice environment. Managed care is not just a set of rules that physicians choose to follow or disobey, but an environment of competing pressures from patients, purchasers, and high workload. Reimbursement manipulation is a response to that environment, rather than simply a reflection of individual physicians' values.

77 FR 46686 - Steel Nails From the People's Republic of China: Notice of Court Decision Not in Harmony With...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-06

...'s Republic of China: Notice of Court Decision Not in Harmony With Final Scope Ruling and Notice of... Corporation's toolkits from the People's Republic of China (``PRC''), pursuant to the CIT's remand order in... judgment in this case is not in harmony with the Department's final scope ruling and is amending its final...

A Comparison of Common and Novel Curriculum-Based Measurement of Reading Decision Rules to Predict Spring Performance for Students Receiving Supplemental Interventions

ERIC Educational Resources Information Center

Van Norman, Ethan R.; Parker, David C.

2018-01-01

Recent simulations suggest that trend line decision rules applied to curriculum-based measurement of reading progress monitoring data may lead to inaccurate interpretations unless data are collected for upward of 3 months. The authors of those studies did not manipulate goal line slope or account for a student's level of initial performance when…

Neuropsychologist experts and neurolaw: cases, controversies, and admissibility challenges.

PubMed

Kaufmann, Paul M

2013-01-01

Clinical neuropsychologists engage increasingly in forensic consulting activities because such expert opinions are generally relevant, reliable and helpful in resolving certain legal claims, especially those related to traumatic brain injury. Consequently, practitioners of law, medicine and psychology would benefit from understanding the nature of neuropsychological evidence, the standards for its admissibility, and its expanding role in neurolaw. This article reviews important evidentiary rules regulating relevance, preliminary questions, and expert testimony, while tracing federal key court decisions and progeny. Civil and criminal cases are detailed to illustrate the application of these rules and case law to neuropsychological evidence, with suggestions for overcoming motions to exclude such evidence. Expert neuropsychologists have a role in forensic consultation on brain trauma cases, even as the interdisciplinary dialog and understanding among law, medicine, and psychology continues to expand. Copyright © 2013 John Wiley & Sons, Ltd.

Likelihood Ratio, Optimal Decision Rules, and Relationship between Proportion Correct and d' in the Dual-Pair AB vs BA identification Paradigm

PubMed Central

Micheyl, Christophe; Dai, Huanping

2010-01-01

The equal-variance Gaussian signal-detection-theory (SDT) decision model for the dual-pair change-detection (or “4IAX”) paradigm has been described in earlier publications. In this note, we consider the equal-variance Gaussian SDT model for the related dual-pair AB vs BA identification paradigm. The likelihood ratios, optimal decision rules, receiver operating characteristics (ROCs), and relationships between d' and proportion-correct (PC) are analyzed for two special cases: that of statistically independent observations, which is likely to apply in constant-stimuli experiments, and that of highly correlated observations, which is likely to apply in experiments where stimuli are roved widely across trials or pairs. A surprising outcome of this analysis is that although these two situations lead to different optimal decision rules, the predicted ROCs and proportions of correct responses (PCs) for these two cases are not substantially different, and are either identical or similar to those observed in the basic Yes-No paradigm. PMID:19633356

Using Participatory Action Research to Develop a Working Model That Enhances Psychiatric Nurses' Professionalism: The Architecture of Stability.

PubMed

Salzmann-Erikson, Martin

2017-11-01

Ward rules in psychiatric care aim to promote safety for both patients and staff. Simultaneously, ward rules are associated with increased patient violence, leading to neither a safe work environment nor a safe caring environment. Although ward rules are routinely used, few studies have explicitly accounted for their impact. To describe the process of a team development project considering ward rule issues, and to develop a working model to empower staff in their daily in-patient psychiatric nursing practices. The design of this study is explorative and descriptive. Participatory action research methodology was applied to understand ward rules. Data consists of audio-recorded group discussions, observations and field notes, together creating a data set of 556 text pages. More than 100 specific ward rules were identified. In this process, the word rules was relinquished in favor of adopting the term principles, since rules are inconsistent with a caring ideology. A linguistic transition led to the development of a framework embracing the (1) Principle of Safety, (2) Principle of Structure and (3) Principle of Interplay. The principles were linked to normative guidelines and applied ethical theories: deontology, consequentialism and ethics of care. The work model reminded staff about the principles, empowered their professional decision-making, decreased collegial conflicts because of increased acceptance for individual decisions, and, in general, improved well-being at work. Furthermore, the work model also empowered staff to find support for their decisions based on principles that are grounded in the ethics of totality.

Advancing reservoir operation description in physically based hydrological models

NASA Astrophysics Data System (ADS)

Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

2016-04-01

Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir operating strategies.

Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.

PubMed

Klabunde, Anna; Willekens, Frans

We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

The Manchester Acute Coronary Syndromes (MACS) decision rule for suspected cardiac chest pain: derivation and external validation.

PubMed

Body, Richard; Carley, Simon; McDowell, Garry; Pemberton, Philip; Burrows, Gillian; Cook, Gary; Lewis, Philip S; Smith, Alexander; Mackway-Jones, Kevin

2014-09-15

We aimed to derive and validate a clinical decision rule (CDR) for suspected cardiac chest pain in the emergency department (ED). Incorporating information available at the time of first presentation, this CDR would effectively risk-stratify patients and immediately identify: (A) patients for whom hospitalisation may be safely avoided; and (B) high-risk patients, facilitating judicious use of resources. In two sequential prospective observational cohort studies at heterogeneous centres, we included ED patients with suspected cardiac chest pain. We recorded clinical features and drew blood on arrival. The primary outcome was major adverse cardiac events (MACE) (death, prevalent or incident acute myocardial infarction, coronary revascularisation or new coronary stenosis >50%) within 30 days. The CDR was derived by logistic regression, considering reliable (κ>0.6) univariate predictors (p<0.05) for inclusion. In the derivation study (n=698) we derived a CDR including eight variables (high sensitivity troponin T; heart-type fatty acid binding protein; ECG ischaemia; diaphoresis observed; vomiting; pain radiation to right arm/shoulder; worsening angina; hypotension), which had a C-statistic of 0.95 (95% CI 0.93 to 0.97) implying near perfect diagnostic performance. On external validation (n=463) the CDR identified 27.0% of patients as 'very low risk' and potentially suitable for discharge from the ED. 0.0% of these patients had prevalent acute myocardial infarction and 1.6% developed MACE (n=2; both coronary stenoses without revascularisation). 9.9% of patients were classified as 'high-risk', 95.7% of whom developed MACE. The Manchester Acute Coronary Syndromes (MACS) rule has the potential to safely reduce unnecessary hospital admissions and facilitate judicious use of high dependency resources. 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.

22 CFR 224.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... limited to any advantage, preference, privilege, license, permit, favorable decision, ruling, status, or... United States Government. Individual means a natural person. Initial decision means the written decision of the ALJ required by § 224.10 or § 224.37, and includes a revised initial decision issued following...

38 CFR 42.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... advantage, preference, privilege, license, permit, favorable decision, ruling, status, or loan guarantee.... Initial Decision means the written decision of the ALJ required by § 42.10 or § 42.37 of this part, and includes a revised initial decision issued following a remand or a motion for reconsideration...

76 FR 28209 - Committee on Regulation

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-16

... #0; #0;Notices #0; Federal Register #0; #0; #0;This section of the FEDERAL REGISTER contains documents other than rules #0;or proposed rules that are applicable to the public. Notices of hearings #0;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority...

78 FR 22842 - Nicolet Resource Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-17

... #0; #0;Notices #0; Federal Register #0; #0; #0;This section of the FEDERAL REGISTER contains documents other than rules #0;or proposed rules that are applicable to the public. Notices of hearings #0;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority...

Thoughtful nursing practice: reflections on nurse delegation decision-making.

PubMed

McInnis, Leigh Ann; Parsons, Lynn C

2009-12-01

This article discusses delegation challenges and legal and regulatory oversight associated with delegation in the clinical practice setting. The authors address moral and legal attributes of the roles and responsibilities of health care providers regarding delegating health care interventions. The article also explores guiding principles and rules of delegation within professional standards, national practice guidelines, and state nurse practice acts. Nurse experts provide thoughtful reflection on nursing models and the role of delegation, emphasizing the critical role of delegation in extending the role of the health care professional in patient care services.

Agile Acceptance Test–Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software

PubMed Central

Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-01-01

Background Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test–driven development and automated regression testing promotes reliability. Test–driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a “safety net” for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and “living” design documentation. Rapid-cycle development or “agile” methods are being successfully applied to CDS development. The agile practice of automated test–driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as “executable requirements.” Objective We aimed to establish feasibility of acceptance test–driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Methods Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory’s expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite. Results We used test–driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the “executable requirements” are shown prior to building the CDS alert, during build, and after successful build. Conclusions Automated acceptance test–driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test–driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization. PMID:29653922

Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

PubMed

Basit, Mujeeb A; Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-04-13

Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements." We aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite. We used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build. Automated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization. ©Mujeeb A Basit, Krystal L Baldwin, Vaishnavi Kannan, Emily L Flahaven, Cassandra J Parks, Jason M Ott, Duwayne L Willett. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.04.2018.

Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

PubMed

Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie

2018-05-18

Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented. © 2018, The International Biometric Society.

Decision making under internal uncertainty: the case of multiple-choice tests with different scoring rules.

PubMed

Bereby-Meyer, Yoella; Meyer, Joachim; Budescu, David V

2003-02-01

This paper assesses framing effects on decision making with internal uncertainty, i.e., partial knowledge, by focusing on examinees' behavior in multiple-choice (MC) tests with different scoring rules. In two experiments participants answered a general-knowledge MC test that consisted of 34 solvable and 6 unsolvable items. Experiment 1 studied two scoring rules involving Positive (only gains) and Negative (only losses) scores. Although answering all items was the dominating strategy for both rules, the results revealed a greater tendency to answer under the Negative scoring rule. These results are in line with the predictions derived from Prospect Theory (PT) [Econometrica 47 (1979) 263]. The second experiment studied two scoring rules, which allowed respondents to exhibit partial knowledge. Under the Inclusion-scoring rule the respondents mark all answers that could be correct, and under the Exclusion-scoring rule they exclude all answers that might be incorrect. As predicted by PT, respondents took more risks under the Inclusion rule than under the Exclusion rule. The results illustrate that the basic process that underlies choice behavior under internal uncertainty and especially the effect of framing is similar to the process of choice under external uncertainty and can be described quite accurately by PT. Copyright 2002 Elsevier Science B.V.

Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences.

PubMed

Latty, Tanya; Beekman, Madeleine

2011-01-22

Most models of animal foraging and consumer choice assume that individuals make choices based on the absolute value of items and are therefore 'economically rational'. However, frequent violations of rationality by animals, including humans, suggest that animals use comparative valuation rules. Are comparative valuation strategies a consequence of the way brains process information, or are they an intrinsic feature of biological decision-making? Here, we examine the principles of rationality in an organism with radically different information-processing mechanisms: the brainless, unicellular, slime mould Physarum polycephalum. We offered P. polycephalum amoebas a choice between food options that varied in food quality and light exposure (P. polycephalum is photophobic). The use of an absolute valuation rule will lead to two properties: transitivity and independence of irrelevant alternatives (IIA). Transitivity is satisfied if preferences have a consistent, linear ordering, while IIA states that a decision maker's preference for an item should not change if the choice set is expanded. A violation of either of these principles suggests the use of comparative rather than absolute valuation rules. Physarum polycephalum satisfied transitivity by having linear preference rankings. However, P. polycephalum's preference for a focal alternative increased when a third, inferior quality option was added to the choice set, thus violating IIA and suggesting the use of a comparative valuation process. The discovery of comparative valuation rules in a unicellular organism suggests that comparative valuation rules are ubiquitous, if not universal, among biological decision makers.

Sex-specific performance of pre-imaging diagnostic algorithms for pulmonary embolism.

PubMed

van Mens, T E; van der Pol, L M; van Es, N; Bistervels, I M; Mairuhu, A T A; van der Hulle, T; Klok, F A; Huisman, M V; Middeldorp, S

2018-05-01

Essentials Decision rules for pulmonary embolism are used indiscriminately despite possible sex-differences. Various pre-imaging diagnostic algorithms have been investigated in several prospective studies. When analysed at an individual patient data level the algorithms perform similarly in both sexes. Estrogen use and male sex were associated with a higher prevalence in suspected pulmonary embolism. Background In patients suspected of pulmonary embolism (PE), clinical decision rules are combined with D-dimer testing to rule out PE, avoiding the need for imaging in those at low risk. Despite sex differences in several aspects of the disease, including its diagnosis, these algorithms are used indiscriminately in women and men. Objectives To compare the performance, defined as efficiency and failure rate, of three pre-imaging diagnostic algorithms for PE between women and men: the Wells rule with fixed or with age-adjusted D-dimer cut-off, and a recently validated algorithm (YEARS). A secondary aim was to determine the sex-specific prevalence of PE. Methods Individual patient data were obtained from six studies using the Wells rule (fixed D-dimer, n = 5; age adjusted, n = 1) and from one study using the YEARS algorithm. All studies prospectively enrolled consecutive patients with suspected PE. Main outcomes were efficiency (proportion of patients in which the algorithm ruled out PE without imaging) and failure rate (proportion of patients with PE not detected by the algorithm). Outcomes were estimated using (multilevel) logistic regression models. Results The main outcomes showed no sex differences in any of the separate algorithms. With all three, the prevalence of PE was lower in women (OR, 0.66, 0.68 and 0.74). In women, estrogen use, adjusted for age, was associated with lower efficiency and higher prevalence and D-dimer levels. Conclusions The investigated pre-imaging diagnostic algorithms for patients suspected of PE show no sex differences in performance. Male sex and estrogen use are both associated with a higher probability of having the disease. © 2018 International Society on Thrombosis and Haemostasis.

International lessons in new methods for grading and integrating cost effectiveness evidence into clinical practice guidelines.

PubMed

Antioch, Kathryn M; Drummond, Michael F; Niessen, Louis W; Vondeling, Hindrik

2017-01-01

Economic evidence is influential in health technology assessment world-wide. Clinical Practice Guidelines (CPG) can enable economists to include economic information on health care provision. Application of economic evidence in CPGs, and its integration into clinical practice and national decision making is hampered by objections from professions, paucity of economic evidence or lack of policy commitment. The use of state-of-art economic methodologies will improve this. Economic evidence can be graded by 'checklists' to establish the best evidence for decision making given methodological rigor. New economic evaluation checklists, Multi-Criteria Decision Analyses (MCDA) and other decision criteria enable health economists to impact on decision making world-wide. We analyse the methodologies for integrating economic evidence into CPG agencies globally, including the Agency of Health Research and Quality (AHRQ) in the USA, National Health and Medical Research Council (NHMRC) and Australian political reforms. The Guidelines and Economists Network International (GENI) Board members from Australia, UK, Canada and Denmark presented the findings at the conference of the International Health Economists Association (IHEA) and we report conclusions and developments since. The Consolidated Guidelines for the Reporting of Economic Evaluations (CHEERS) 24 item check list can be used by AHRQ, NHMRC, other CPG and health organisations, in conjunction with the Drummond ten-point check list and a questionnaire that scores that checklist for grading studies, when assessing economic evidence. Cost-effectiveness Analysis (CEA) thresholds, opportunity cost and willingness-to-pay (WTP) are crucial issues for decision rules in CEA generally, including end-of-life therapies. Limitations of inter-rater reliability in checklists can be addressed by including more than one assessor to reach a consensus, especially when impacting on treatment decisions. We identify priority areas to generate economic evidence for CPGs by NHMRC, AHRQ, and other agencies. The evidence may cover demand for care issues such as involved time, logistics, innovation price, price sensitivity, substitutes and complements, WTP, absenteeism and presentism. Supply issues may include economies of scale, efficiency changes, and return on investment. Involved equity and efficiency measures may include cost-of-illness, disease burden, quality-of-life, budget impact, cost-effective ratios, net benefits and disparities in access and outcomes. Priority setting remains essential and trade-off decisions between policy criteria can be based on MCDA, both in evidence based clinical medicine and in health planning.

Rules, Schema, and Decision Making.

DTIC Science & Technology

1987-09-01

discussion ............................................................ 47 6. GENERAL DISCUSSION...65 6.3. Generality of results................................................................ 68 6.4. Implications for...3 2-1 General model of decision making

The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral Evidence

PubMed Central

Dixon, Matthew L.; Christoff, Kalina

2012-01-01

Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel ‘free-choice’ versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives. PMID:23284730

The future of decision-making in critical care after Cuthbertson v. Rasouli.

PubMed

Hawryluck, Laura; Baker, Andrew J; Faith, Andrew; Singh, Jeffrey M

2014-10-01

The Supreme Court of Canada (SCC) ruling on Cuthbertson v. Rasouli has implications for all acute healthcare providers. This well-publicized case involved a disagreement between healthcare providers and a patient's family regarding the principles surrounding withdrawal of life support, which the physicians involved considered no longer of medical benefit and outside the standard of care, and whether consent was required for such withdrawals. Our objective in writing this article is to clarify the implications of this ruling on the care of critically ill patients. SCC ruling Cuthbertson v. Rasouli. The SCC ruled that consent must be obtained for all treatments that serve a "health-related purpose", including withdrawal of such treatments. The SCC did not fully consider what the standard of care should be. Health-related purpose is not sufficient in and of itself to mandate treatment, and clinicians must still ensure that their patients or decision-makers are aware of the possible medical benefits, risks, and expected outcomes of treatments. The provision of treatments that have no potential to provide medical benefit and carry only risks would still fall outside the standard of care. Nevertheless, due to their health-related purpose, physicians must seek consent for the discontinuation of these treatments. The SCC ruled that due to the legal definition of "health-related purpose", which is distinct from medical benefit, consent is required to withdraw life-support and outlined the steps to be taken should conflict arise. The SCC decision did not directly address the role of medical standard of care in these situations. In order to ensure optimal decision-making and communication with patients and their families, it is critical for healthcare providers to have a clear understanding of the implications of this legal ruling on medical practice.

The impact of loss sensitivity on a mobile phone supply chain system stability based on the chaos theory

NASA Astrophysics Data System (ADS)

Ma, Junhai; Xie, Lei

2018-02-01

This paper, based on the China's communications and the current situation of the mobile phone industry, focuses on the stability of a supply chain system that consists of one supplier and one bounded rational retailer. We explore the influence of the decision makers' loss sensitivity and decision adjustment speed on the stability of the supply chain. It is found that when the retailer is not sensitive to the loss or adjusts decisions cautiously, the system can be stable. The single-retailer model is extended to a multi-retailer one to study the influence of competition on the system stability. The results show that the market share of each retailer does not affect the system stability when it is fixed. The decision of each retailer does not affect that of any other retailer and the system stability. We present two decision adjustment rules (;bounded rationality expectation (BRE); and "adaptive exponential smoothing (AES)") and compare their performances on the system stability, and find that the AES rule does not affect the system stability, while the BRE rule will make the system stability be sensitive to the retailers' loss sensitivity and the decision adjustment speed. We also reveal the unstable system's negative impact on the retailers' decisions and profits, to emphasize the importance to maintain the system stability.

Improving clinical models based on knowledge extracted from current datasets: a new approach.

PubMed

Mendes, D; Paredes, S; Rocha, T; Carvalho, P; Henriques, J; Morais, J

2016-08-01

The Cardiovascular Diseases (CVD) are the leading cause of death in the world, being prevention recognized to be a key intervention able to contradict this reality. In this context, although there are several models and scores currently used in clinical practice to assess the risk of a new cardiovascular event, they present some limitations. The goal of this paper is to improve the CVD risk prediction taking into account the current models as well as information extracted from real and recent datasets. This approach is based on a decision tree scheme in order to assure the clinical interpretability of the model. An innovative optimization strategy is developed in order to adjust the decision tree thresholds (rule structure is fixed) based on recent clinical datasets. A real dataset collected in the ambit of the National Registry on Acute Coronary Syndromes, Portuguese Society of Cardiology is applied to validate this work. In order to assess the performance of the new approach, the metrics sensitivity, specificity and accuracy are used. This new approach achieves sensitivity, a specificity and an accuracy values of, 80.52%, 74.19% and 77.27% respectively, which represents an improvement of about 26% in relation to the accuracy of the original score.

20 CFR 418.1355 - What are the rules for reopening a decision by an administrative law judge of the Office of...

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false What are the rules for reopening a decision by an administrative law judge of the Office of Medicare Hearings and Appeals (OMHA) or by the Medicare Appeals Council (MAC)? 418.1355 Section 418.1355 Employees' Benefits SOCIAL SECURITY ADMINISTRATION MEDICARE SUBSIDIES Medicare Part B...

40 CFR 164.90 - Initial decision.

Code of Federal Regulations, 2010 CFR

2010-07-01

....90 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS RULES OF... REFUSALS TO REGISTER, CANCELLATIONS OF REGISTRATIONS, CHANGES OF CLASSIFICATIONS, SUSPENSIONS OF... Environmental Appeals Board. The initial decision shall become the decision of the Environmental Appeals Board...

40 CFR 164.90 - Initial decision.

Code of Federal Regulations, 2011 CFR

2011-07-01

....90 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS RULES OF... REFUSALS TO REGISTER, CANCELLATIONS OF REGISTRATIONS, CHANGES OF CLASSIFICATIONS, SUSPENSIONS OF... Environmental Appeals Board. The initial decision shall become the decision of the Environmental Appeals Board...

Separating Decision and Encoding Noise in Signal Detection Tasks

PubMed Central

Cabrera, Carlos Alexander; Lu, Zhong-Lin; Dosher, Barbara Anne

2015-01-01

In this paper we develop an extension to the Signal Detection Theory (SDT) framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains SDT models with decision noise by combining a multi-pass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with three and five response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009, Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks. PMID:26120907

Age differences in decision making: a process methodology for examining strategic information processing.

PubMed

Johnson, M M

1990-03-01

This study explored the use of process tracing techniques in examining the decision-making processes of older and younger adults. Thirty-six college-age and thirty-six retirement-age participants decided which one of six cars they would purchase on the basis of computer-accessed data. They provided information search protocols. Results indicate that total time to reach a decision did not differ according to age. However, retirement-age participants used less information, spent more time viewing, and re-viewed fewer bits of information than college-age participants. Information search patterns differed markedly between age groups. Patterns of retirement-age adults indicated their use of noncompensatory decision rules which, according to decision-making literature (Payne, 1976), reduce cognitive processing demands. The patterns of the college-age adults indicated their use of compensatory decision rules, which have higher processing demands.

16 CFR 5.65 - Review of initial decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Review of initial decision. 5.65 Section 5.65 Commercial Practices FEDERAL TRADE COMMISSION ORGANIZATION, PROCEDURES AND RULES OF PRACTICE... initial decision. Appeals from the initial decision of the Administrative Law Judge or review by the...

22 CFR 35.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., permit, favorable decision, ruling, status, or loan gurarantee. (e) Claim means any request, demand, or.... (k) Initial decision means the written decision of the ALJ required by § 35.10 or § 35.37, and includes a revised initial decision issued following a remand or a motion for reconsideration. (l...

75 FR 62538 - Agency Information Collection Activities; Proposed Collection; Comment Request; Extension

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-12

... information collection requirements contained in its Used Motor Vehicle Trade Regulation Rule (``Used Car Rule...-5634. SUPPLEMENTARY INFORMATION: The Used Car Rule facilitates informed purchasing decisions by requiring used car dealers to disclose information about warranty coverage, if any, and the mechanical...

77 FR 52676 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-30

... #0; #0;Notices #0; Federal Register #0; #0; #0;This section of the FEDERAL REGISTER contains documents other than rules #0;or proposed rules that are applicable to the public. Notices of hearings #0;and investigations, committee meetings, agency decisions and rulings, #0;delegations of authority...