Journal
JOURNAL OF CLINICAL EPIDEMIOLOGY
Volume 64, Issue 10, Pages 1054-1059Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jclinepi.2011.01.001
Keywords
Administrative database research; Codes; Bias; Bayesian calculations; Misclassification; Systematic review
Funding
- Department of Medicine, University of Ottawa
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Objective: Administrative database research (ADR) frequently uses codes to identify diagnoses or procedures. The association of these codes with the condition it represents must be measured to gauge misclassification in the study. Measure the proportion of ADR studies using diagnostic or procedural codes that measured or referenced code accuracy. Study Design and Setting: Random sample of 150 MEDLINE-cited ADR studies stratified by year of publication. The proportion of ADR studies using codes to define patient cohorts, exposures, or outcomes that measured or referenced code accuracy and Bayesian estimates for probability of disease given code operating characteristics were measured. Results: One hundred fifteen ADR studies (76.7% [95% confidence interval (CI), 69.3-82.8]) used codes. Of these studies, only 14 (12.1% [7.3-19.5]) measured or referenced the association of the code with the entity it supposedly represented. This proportion did not vary by year of publication but was significantly higher in journals with greater impact factors. Of five studies reporting code sensitivity and specificity, the estimated probability of code-related condition in code-positive patients was less than 50% in two. Conclusion: In ADR, diagnostic and procedural codes are commonly used but infrequently validated. People with a code frequently do not have the condition it represents. (C) 2011 Elsevier Inc. All rights reserved.
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