Year: 2014
Type: article
Abstract: BACKGROUND: Systematic coding systems are used to define clinically meaningful outcomes when leveraging administrative claims data for research. How and when these codes are applied within a research study can have implications for the study validity and their specificity can vary significantly depending on treatment received. SUBJECTS: Data are from the Surveillance, Epidemiology, and End Results-Medicare linked dataset. STUDY DESIGN: We use propensity score methods in a retrospective cohort of prostate cancer patients first examined in a recently published radiation oncology comparative effectiveness study. RESULTS: With the narrowly defined outcome definition, the toxicity event outcome rate ratio was 0.88 per 100 person-years (95% confidence interval, 0.71-1.08). With the broadly defined outcome, the rate ratio was comparable, with 0.89 per 100 person-years (95% confidence interval, 0.76-1.04), although individual event rates were doubled. Some evidence of surveillance bias was suggested by a higher rate of endoscopic procedures the first year of follow-up in patients who received proton therapy compared with those receiving intensity-modulated radiation treatment (11.15 vs. 8.90, respectively). CONCLUSIONS: This study demonstrates the risk of introducing bias through subjective application of procedure codes. Careful consideration is required when using procedure codes to define outcomes in administrative data.
Source: Medical Care
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
Funders: U.S. Department of Health and Human Services, GlaxoSmithKline, Sanofi, California Department of Public Health, North Carolina GlaxoSmithKline Foundation, National Institutes of Health, Agency for Healthcare Research and Quality, University of North Carolina at Chapel Hill, National Institute on Aging, National Cancer Institute, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill
OpenAlex ID: W2323677748