title: How does drug treatment for diabetes compare between Medicare Advantage prescription drug plans (MAPDs) and stand-alone prescription drug plans (PDPs)?
abstract: OBJECTIVE
  To compare the use of guideline-recommended prescription medications for diabetes among Medicare beneficiaries enrolled in stand-alone prescription drug plans (PDPs) with Medicare Advantage prescription drug plans (MAPDs) in the presence of potential selection bias.
  
  
  METHODS
  Centers for Medicare and Medicaid Services' Chronic Condition Data Warehouse (2006, 2007).
  
  
  METHODS
  Retrospective cross-sectional comparison of drug use and proportion of days covered (PDC) for oral-antidiabetics, ACE-inhibitors/ARBs, and antihyperlipidemics among PDP and MAPD enrollees with diabetes. We estimated "naïve" regression models assuming exogenous plan choice and two-stage residual inclusion (2SRI) models to study endogeneity in choice of Part D plan type.
  
  
  METHODS
  We identified 111,290 diabetics based on ICD-9 codes in Medicare claims from a random 5 percent sample of Medicare beneficiaries in 2005 excluding dual eligibles.
  
  
  RESULTS
  The naïve regression models indicated lower probability of drug use for oral-antidiabetics (-4 percent; p < .001) and ACE-inhibitors/ARBS (-2 percent; p = .004) among PDP enrollees, but their PDC was higher (3-5 percent) for all drug classes (p < .001). 2SRI models produced no significant differences in any-use equations, but significantly higher PDC values for PDP enrollees for oral-antidiabetics and ACE-inhibitors/ARBs.
  
  
  CONCLUSIONS
  We found similar overall use of recommended drugs in diabetes treatment and no consistent evidence of favorable or adverse selection into PDPs and MAPDs.
authors.affiliation: Pharmaceutical Health Services Department, University of Maryland School of Pharmacy, Peter Lamy Center on Drug Therapy and Aging, Baltimore, MD, USA.
authors.forename: Mujde Z
authors.initials: MZ
authors.lastname: Erten
authors.forename: Bruce
authors.initials: B
authors.lastname: Stuart
authors.forename: Amy J
authors.initials: AJ
authors.lastname: Davidoff
authors.forename: J Samantha
authors.initials: JS
authors.lastname: Shoemaker
authors.forename: Lynda
authors.initials: L
authors.lastname: Bryant-Comstock
authors.forename: Rahul
authors.initials: R
authors.lastname: Shenolikar
mesh_terms: D000284:Administration, Oral; D000368:Aged; D000369:Aged, 80 and over; D000806:Angiotensin-Converting Enzyme Inhibitors / Q000627:therapeutic use; D015897:Comorbidity; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000188:drug therapy*; D004363:Drug Utilization / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D000960:Hypolipidemic Agents / Q000627:therapeutic use; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D008297:Male; D020398:Medicare Part C / Q000706:statistics & numerical data*; D054524:Medicare Part D / Q000706:statistics & numerical data*; D008875:Middle Aged; D012189:Retrospective Studies; D012959:Socioeconomic Factors; D014481:United States
chemical_list: D000806:Angiotensin-Converting Enzyme Inhibitors; D007004:Hypoglycemic Agents; D000960:Hypolipidemic Agents