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Biomedical subjects

P Heckerling

Publications and source records attributed to P Heckerling.

6 recordsLinked to original sources
PubMed1999

Reducing unnecessary coagulation testing in hypertensive disorders of pregnancy.

OBJECTIVE: To estimate the magnitude of laboratory testing for hypertension in pregnancy and determine whether abnormalities in prothrombin time (PT), activated partial thromboplastin time (aPTT), and fibrinogen can be predicted by results of common, less expensive tests. MATERIALS AND METHODS: Laboratory records were searched and charts were reviewed to identify gravidas tested for hypertension and to exclude conditions producing coagulopathy. Contingency tables were constructed to assess the ability of the platelet count, lactate dehydrogenase, and transaminases to predict coagulation test results. RESULTS: Preliminary data on 73 gravidas found that a platelet count plus a lactate dehydrogenase test best predicted coagulation abnormalities. Results on another 732 gravidas indicated that coagulation tests were obtained in about 30%. No patient had a PT greater than 18 seconds, two had an aPTT greater than 40 seconds, and three had fibrinogen levels less than 200 mg/dL. The combination of a normal platelet count plus a normal lactate dehydrogenase had a negative predictive value of 100% for clinically significant abnormalities of PT and aPTT, and 99% for significant abnormalities of fibrinogen. CONCLUSIONS: Substantial coagulation testing was done on gravidas evaluated for a hypertensive disorder even though the prevalence of clinically significant abnormalities was low. Laboratory evaluation of patients suspected of having preeclampsia need not include a PT, aPTT, or fibrinogen test when there is no evidence of bleeding or of a condition that could produce coagulopathy and when the platelet count and lactate dehydrogenase level are both normal.

Blood Coagulation Tests↗
PubMed1998

Measuring the quality of diagnostic hypothesis sets for studies of decision support.

Within medical informatics there is widespread interest in computer-based decision support and the evaluation of its impact. It is widely recognized that the measurement of dependent variables, or outcomes, represents the most challenging aspect of this work. This paper describes and reports the reliability and validity of an outcome metric for studies of diagnostic decision support. The results of this study will guide the analytic methods used in our ongoing multi-site study of the effects of decision support on diagnostic reasoning. Our measurement approach conceptualizes the quality of a diagnostic hypothesis set as having two components summed to generate a composite index: a Plausibility Component derived from ratings of each hypothesis in the set, whether correct or incorrect; and a Location Component derived from the location of the correct diagnosis if it appears in the set. The reliability of this metric is determined by the extent of interrater agreement on the plausibility of diagnostic hypotheses. Validity is determined by the extent to which the index generates scores that make sense on inspection (face validity), as well as the extent to which the component scores are non-redundant and discriminate the performance of novices and experts (construct validity). Using data from the pilot and main phases of our ongoing study (n = 124 subjects working 1116 cases), the reliability of our diagnostic quality metric was found to be 0.85-0.88. The metric was found to generate, on inspection, no clearly counterintuitive scores. Using data from the pilot phase of our study (n = 12 subjects working 108 cases), the component scores were moderately correlated (r = 0.68). The composite index, computed by equally weighting both components, was found to discriminate the hypotheses of medical students and attending physicians by 0.97 standard deviation units. Based on these findings, we have adopted this metric for use in our further research exploring the impact of decision support systems on diagnostic reasoning and will make it available to the informatics research community.

Decision Support Systems, Clinical↗
PubMed1997

Changes in diagnostic decision-making after a computerized decision support consultation based on perceptions of need and helpfulness: a preliminary report.

We examined the degree to which attending physicians, residents, and medical students' stated desire for a consultation on difficult-to-diagnose patient cases is related to changes in their diagnostic judgments after a computer consultation, and whether, in fact, their perceptions of the usefulness of these consultations are related to these changes. The decision support system (DSS) used in this study was ILIAD (v4.2). Preliminary findings based on 16 subjects' (6 general internists, 4 second-year residents in internal medicine, and 6 fourth-year medical students) workup of 136 patient cases indicated no significant main effects for 1) level of experience, 2) whether or not subjects indicated they would seek a diagnostic consultation before using the DSS, or 3) whether or not they found the DSS consultation in fact to be helpful in arriving at a diagnosis (p > .49 in all instances). Nor were there any significant interactions. Findings were similar using subjects or cases as the unit of analysis. It is possible that what may appear to be counter-intuitive, and perhaps irrational, may not necessarily be so. We are currently examining potential explanatory hypotheses in our ongoing current, larger study.

Attitude to Computers↗
PubMedDate not supplied

Effects of a decision support system on the diagnostic accuracy of users: a preliminary report.

OBJECTIVES: To assess the effects of incomplete data upon the output of a computerized diagnostic decision support system (DSS), to assess the effects of using the system upon the diagnostic opinions of users, and to explore if these effects vary as a function of clinical experience. DESIGN: Experimental pilot study. Four clusters of nine cases each were constructed and equated for case difficulty. Definitive findings were omitted from the case abstracts. Subjects were randomly assigned to one of four clusters and were trained on the DSS prior to use. SUBJECTS: The study involved 16 physicians at three levels of clinical experience (six general internists, four residents in internal medicine, and six fourth-year medical students), from three academic medical centers. PROCEDURE: Each subject worked up nine cases, first without and then with ILIAD consultation. They were asked to offer up to six potential diagnoses and to list up to three steps that should be the next items in the diagnostic workup. Effects of DSS consultation were measured by changes in the position of the correct diagnosis in the lists of differential diagnoses, pre- and post-consultation. RESULTS: The DSS lists of diagnostic possibilities contained the correct diagnosis in 38% of cases, about midway between the levels of accuracy of residents and attending general internists. In over 70% of cases, the DSS output had no effect on the position of the correct diagnosis in the subjects' lists. The system's diagnostic accuracy was unaffected by the clinical experience of the users.

Decision Making↗