期刊
MEDICAL CARE
卷 48, 期 6, 页码 S114-S120出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MLR.0b013e3181dbebe3
关键词
confounding; unmeasured confounding; propensity scores; variable selection; pharmacoepidemiology
类别
资金
- NIA NIH HHS [K25-AG027400, R01 AG018833, K25 AG027400, R01 AG023178, R01-AG023178, R01-AG18833] Funding Source: Medline
- NLM NIH HHS [R01-LM010213, R01 LM010213] Funding Source: Medline
Epidemiologic studies are increasingly used to investigate the safety and effectiveness of medical products and interventions. Appropriate adjustment for confounding in such studies is challenging because exposure is determined by a complex interaction of patient, physician, and healthcare system factors. The challenges of confounding control are particularly acute in studies using healthcare utilization databases where information on many potential confounding factors is lacking and the meaning of variables is often unclear. We discuss advantages and disadvantages of different approaches to confounder control in healthcare databases. In settings where considerable uncertainty surrounds the data or the causal mechanisms underlying the treatment assignment and outcome process, we suggest that researchers report a panel of results under various specifications of statistical models. Such reporting allows the reader to assess the sensitivity of the results to model assumptions that are often not supported by strong subject-matter knowledge.
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