A novel approach to the determination of clinical decision thresholds

Details

Serval ID
serval:BIB_11C90D0C2312
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A novel approach to the determination of clinical decision thresholds
Journal
Evidence-based Medicine
Author(s)
Ebell M.H., Locatelli I., Senn N.
ISSN
1473-6810 (Electronic)
ISSN-L
1356-5524
Publication state
Published
Issued date
2015
Peer-reviewed
Oui
Volume
20
Number
2
Pages
41-47
Language
english
Notes
Erratum in Correction. [Evid Based Med. 2015]
Abstract
Our objective was to determine the test and treatment thresholds for common acute primary care conditions. We presented 200 clinicians with a series of web-based clinical vignettes, describing patients with possible influenza, acute coronary syndrome (ACS), pneumonia, deep vein thrombosis (DVT) and urinary tract infection (UTI). We randomly varied the probability of disease and asked whether the clinician wanted to rule out disease, order tests or rule in disease. By randomly varying the probability, we obtained clinical decisions across a broad range of disease probabilities that we used to create threshold curves. For influenza, the test (4.5% vs 32%, p<0.001) and treatment (55% vs 68%, p=0.11) thresholds were lower for US compared with Swiss physicians. US physicians had somewhat higher test (3.8% vs 0.7%, p=0.107) and treatment (76% vs 58%, p=0.005) thresholds for ACS than Swiss physicians. For both groups, the range between test and treatment thresholds was greater for ACS than for influenza (which is sensible, given the consequences of incorrect diagnosis). For pneumonia, US physicians had a trend towards higher test thresholds and lower treatment thresholds (48% vs 64%, p=0.076) than Swiss physicians. The DVT and UTI scenarios did not provide easily interpretable data, perhaps due to poor wording of the vignettes. We have developed a novel approach for determining decision thresholds. We found important differences in thresholds for US and Swiss physicians that may be a function of differences in healthcare systems. Our results can also guide development of clinical decision rules and guidelines.
Keywords
Epdemiology, General Medicine (see Internal Medicine), Primary Care, Statistics & Research Methods
Pubmed
Create date
17/03/2015 10:46
Last modification date
20/08/2019 13:39
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