Literature DB >> 325407

The evaluation of clinical predictions. A method and initial application.

A R Shapiro.   

Abstract

Clinical predictions are never certain but are inherently probablisitc. The accuracy coefficient, a measure of probabilistic accuracy based on probability assigned to outcomes that occur, was used to assess the skill of clinical rheumatologists in predicting patient outcomes. Physicians' scores correlated well with degree of clinical experience. An approach to evaluation based on the measure provides a sensitive assessment of marginal benefit of technologies such as laboratory tests, diagnostic procedures or computer consultations. Most currently used methods of computer prediction were not as accurate as the best physicians tested. By allowing measurement of ability to individualize predictions to each patient's unique characteristics, the accuracy-coefficient approach has potential use in physician assessment.

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Year:  1977        PMID: 325407     DOI: 10.1056/NEJM197706302962607

Source DB:  PubMed          Journal:  N Engl J Med        ISSN: 0028-4793            Impact factor:   91.245


  13 in total

1.  Evaluating the predictiveness of a continuous marker.

Authors:  Ying Huang; Margaret Sullivan Pepe; Ziding Feng
Journal:  Biometrics       Date:  2007-05-08       Impact factor: 2.571

Review 2.  Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

Authors:  R A Miller
Journal:  J Am Med Inform Assoc       Date:  1994 Jan-Feb       Impact factor: 4.497

Review 3.  Computer-assisted medical decision making: a critical review.

Authors:  J A Reggia
Journal:  Ann Biomed Eng       Date:  1981       Impact factor: 3.934

4.  Clinical disagreement: II. How to avoid it and how to learn from one's mistakes. Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario.

Authors: 
Journal:  Can Med Assoc J       Date:  1980-10-07       Impact factor: 8.262

5.  The ailing health care system.

Authors: 
Journal:  West J Med       Date:  1978-06

6.  Development and validation of a computer program using Bayes's theorem to support diagnosis of rheumatic disorders.

Authors:  H J Moens; J K van der Korst
Journal:  Ann Rheum Dis       Date:  1992-02       Impact factor: 19.103

7.  A multi-locus predictiveness curve and its summary assessment for genetic risk prediction.

Authors:  Changshuai Wei; Ming Li; Yalu Wen; Chengyin Ye; Qing Lu
Journal:  Stat Methods Med Res       Date:  2019-01-07       Impact factor: 3.021

8.  External validation of the Intensive Care National Audit & Research Centre (ICNARC) risk prediction model in critical care units in Scotland.

Authors:  David A Harrison; Nazir I Lone; Catriona Haddow; Moranne MacGillivray; Angela Khan; Brian Cook; Kathryn M Rowan
Journal:  BMC Anesthesiol       Date:  2014-12-15       Impact factor: 2.217

9.  Case mix, outcome and activity for patients with severe acute kidney injury during the first 24 hours after admission to an adult, general critical care unit: application of predictive models from a secondary analysis of the ICNARC Case Mix Programme database.

Authors:  Nitin V Kolhe; Paul E Stevens; Alex V Crowe; Graham W Lipkin; David A Harrison
Journal:  Crit Care       Date:  2008-10-13       Impact factor: 9.097

10.  Case mix, outcome and activity for patients admitted to intensive care units requiring chronic renal dialysis: a secondary analysis of the ICNARC Case Mix Programme Database.

Authors:  Colin A Hutchison; Alex V Crowe; Paul E Stevens; David A Harrison; Graham W Lipkin
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

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