Date of Degree
PhD (Doctor of Philosophy)
John M. Brooks
Observational data and alternative estimators with correct interpretations have been used to assess the "right" treatment rates in previous studies. However, no systematic analytical approach has been proposed to examine whether the existing diagnosis rates were right in practice. This study used patients with acute myocardial infarction (AMI) as an example to demonstrate use of observational data to explore the clinical and economic effects of depression diagnosis and the "right" depression diagnosis rates in real-world settings. The objectives of this study were to (1) examine the effects of depression diagnosing on survival, healthcare costs and utilization among elderly patients with AMI; and (2) ascertain bounds on the estimates of the effects of depression diagnosing on survival, healthcare costs and utilization based on chart abstracted data for a subset of patients.
Using Medicare claims data, we included a retrospective cohort of all Medicare fee-for-service patients with their first AMI without a depression diagnosis in the previous year during 2007-2008. Depression diagnosis was identified if a patient had a depression diagnosis within 30 days after AMI admission. We also assessed the effects of depression diagnosis within 60 and 90 days after AMI admission. Outcomes were survival, healthcare costs (total costs, Part A, Part B (outpatient, physician fee schedule, and other), and Part D costs), and utilization (hospitalizations, emergency department (ED) visits, outpatient visits, physician visits, and prescription claims) within 1 year after AMI admission. Risk adjustment (RA) and instrumental variables (IV) models were used to estimate the effects of depression diagnosis on AMI patient outcomes. Instruments of local area depression diagnosis styles were created based on area diagnosis ratio (ADR). Using chart abstracted data for a convenience sample, we measured patient physical functional status by difficulties with activities of daily living (ADL) and overall health by adult comorbidity evaluation-27 (ACE-27), AMI severity, and mental illnesses during the index hospitalization.
Among 155841 AMI patients in our study sample, 5.9% had a depression diagnosis within 30 days after AMI admission. Our RA estimates showed that depression diagnosis was associated with decreased survival, increased total healthcare costs, Part A costs, Part B outpatient costs, hospitalizations, ED visits, physician visits, and prescription claims in 1 year after AMI admission for patients diagnosed with depression. The ADR-based instruments were strongly related to depression diagnosis (Chow-F values > 10). Our IV estimates showed that higher depression diagnosis rates were associated with increased total healthcare costs, Part A costs, Part B physician fee schedule costs, Part B other costs, Part D costs, and physician visits, but decreased ED visits and prescription claims in 1 year after AMI admission for patients whose depression diagnosis was affected by ADR-based instruments.
Since patients diagnosed with depression were more likely to be sicker based on measures in the charts, the RA estimates might be biased toward worse health outcomes and higher healthcare costs and utilization. Across patients grouped by local depression diagnosis styles, the measures in the charts were more evenly distributed across diagnosis groups. However, patients living in areas with stronger preferences of depression diagnosis tended to use more wheelchairs, indicating worse physical function than those living in areas with less stronger preferences. Furthermore, our instruments based on local physician depression diagnosis styles might be correlated with local area practice styles in general (preference to healthcare utilization overall) and local physician supply, and thereby affect healthcare utilization and costs. Therefore, the instruments might not be valid and we could not conclude whether the existing depression diagnosis rates need to be changed.
Acute myocardial infarction, Depression, Diagnosis, Econometrics, Instrumental variables, Mental health
xiii, 265 pages
Includes bibliographical references (pages 248-265).
Copyright 2014 Yuexin Tang