Medical decision making : an international journal of the Society for Medical Decision Making
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Estimates of sensitivity and specificity can be biased by the preferential referral of patients with positive test responses or ancillary clinical abnormalities (the "concomitant information vector") for diagnostic verification. When these biased estimates are analyzed by Bayes' theorem, the resultant posterior disease probabilities (positive and negative predictive accuracies) are similarly biased. Accordingly, a series of computer simulations was performed to quantify the effects of various degrees of verification bias on the calculation of predictive accuracy using Bayes' theorem. ⋯ These errors produced absolute underestimations as high as 22% in positive predictive accuracy, and as high as 14% in negative predictive accuracy, when analyzed by Bayes' theorem at a base rate of 50%. Mathematical correction for biased verification based on the test response using a previously published algorithm significantly reduced these errors by as much as 20%. These data indicate 1) that selection bias significantly distorts the determination of predictive accuracies calculated by Bayes' theorem, and 2) that these distortions can be significantly offset by a correction algorithm.
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SAPHIRE is a concept-based approach to information retrieval in the biomedical domain. Indexing and retrieval are based on a concept-matching algorithm that processes free text to identify concepts and map them to their canonical form. This process requires a large vocabulary containing a breadth of medical concepts and a diversity of synonym forms, which is provided by the Meta-1 vocabulary from the Unified Medical Language System Project of the National Library of Medicine. This paper describes the use of Meta-1 in SAPHIRE and an evaluation of both entities in the context of an information retrieval study.
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Medical authorities have asserted the importance of observing a patient's clinical course over time. Distinguished committees have suggested that changes over time in physicians' prognostic estimates should influence decisions to transfer patients out of intensive care units (ICUs). This study evaluated how the opportunity to observe patients over time affected physicians' prognostic estimates for a cohort of 269 critically ill patients sequentially admitted to a medical-surgical ICU in a teaching hospital. ⋯ No group of physicians substantially improved the reliability or the discriminating power of its later estimates. The physicians in the study could not take advantage of sequential clinical information over time. These results point out the need to teach physicians how to better integrate and process sequential clinical data.
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In contingency judgment a primacy effect exists when a conclusion about the relationship between clinical variables is inordinately influenced by cases seen earlier rather than later in a presentation sequence. In this study, medical and nursing trainees evidenced this behavior in a hypothetical clinical judgment situation. ⋯ A related, but less explicit, intervention was also tried. This intervention did not significantly reduce primacy effects among nursing students, but was somewhat effective among general undergraduate students performing a non-clinical contingency judgment task.