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Regional Variation in Medication Adherence


  • Gibson Teresa B

    () (Thomson Reuters)

  • Landrum Mary Beth

    () (Harvard Medical School)

  • Batata Amber

    () (Pfizer Inc.)

  • Fendrick A. Mark

    () (University of Michigan)

  • Wang Sara

    () (Formerly of Thomson Reuters)

  • Chernew Michael E.

    () (Harvard Medical School)


An extensive literature has demonstrated geographic variation in medical services and this variation has been largely attributed to the health care system and not to regional differences in patient behavior. We use empirical Bayes shrinkage models, conditional on patient, firm, and market covariates, to investigate geographic variation in adherence to prescription medications across hospital referral regions (HRRs). Models are estimated for commercially insured patients in 11 combinations of chronic diseases and drug classes. We use factor analysis to create a market-level composite measure of adherence that we relate to adjusted market-level spending on non-drug services. We find that there is a very small amount of variation in adherence to prescription drugs across HRRs supporting the widely held assumption that geographic variation is attributable to the health system. Markets with high adherence have systematically lower medical spending, and this inverse correlation is more likely due to unobserved market traits.

Suggested Citation

  • Gibson Teresa B & Landrum Mary Beth & Batata Amber & Fendrick A. Mark & Wang Sara & Chernew Michael E., 2011. "Regional Variation in Medication Adherence," Forum for Health Economics & Policy, De Gruyter, vol. 14(2), pages 1-22, July.
  • Handle: RePEc:bpj:fhecpo:v:14:y:2011:i:2:n:8

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    References listed on IDEAS

    1. Amitabh Chandra & Douglas O. Staiger, 2007. "Productivity Spillovers in Health Care: Evidence from the Treatment of Heart Attacks," Journal of Political Economy, University of Chicago Press, vol. 115, pages 103-140.
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    5. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
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