The Impact of Medicare Part D on Out‐of‐Pocket Costs for Prescription Drugs, Medication Utilization, Health Resource Utilization, and Preference‐Based Health Utility

Global Health Economics, Baxter Healthcare Corporation, One Baxter Parkway, Deerfield, IL 60015, USA.
Health Services Research (Impact Factor: 2.78). 05/2011; 46(4):1104-23. DOI: 10.1111/j.1475-6773.2011.01273.x
Source: PubMed


To quantify the impact of Medicare Part D eligibility on medication utilization, emergency department use, hospitalization, and preference-based health utility among civilian noninstitutionalized Medicare beneficiaries.
Difference-in-differences analyses were used to estimate the effects of Part D eligibility on health outcomes by comparing a 12-month period before and after Part D implementation using the Medical Expenditure Panel Survey. Models adjusted for sociodemographic characteristics and health status and compared Medicare beneficiaries aged 65 and older with near elderly aged 55-63 years old.
Five hundred and fifty-six elderly and 549 near elderly were included. After adjustment, Part D was associated with a U.S.$179.86 (p=.034) reduction in out-of-pocket costs and an increase of 2.05 prescriptions (p=.081) per patient year. The associations between Part D and emergency department use, hospitalizations, and preference-based health utility did not suggest cost offsets and were not statistically significant.
Although there was a substantial reduction in out-of-pocket costs and a moderate increase in medication utilization among Medicare beneficiaries during the first year after Part D, there was no evidence of improvement in emergency department use, hospitalizations, or preference-based health utility for those eligible for Part D during its first year of implementation.

13 Reads
  • Source
    • "Having a comparison group partly relieves this concern because we would expect these other time-varying factors to affect both seniors and adults ages 55 to 63. In line with previous Part D evaluations (Engelhardt & Gruber, 2011; Lichtenberg & Sun, 2007; Liu et al., 2011; Mahmoudi & Jensen, 2014), our near-elderly comparison group accounts for factors that could have also affected hospitalization utilization. Excluding this comparison group could lead to incorrect inferences about the effects of Part D if changes in hospital use were also partly driven by broader changes that occurred in the hospital and pharmaceutical industries, or in the economy more generally, such as the onset of the housing crisis and the Great Recession (Wooldridge, 2007). "
    [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study is to evaluate whether Medicare Part D reduced racial/ethnic disparities in hospital utilization among Medicare seniors, based on the Institute of Medicine's definition of a disparity. Using data on 43,098 adult respondents to the 2002-2009 Medical Expenditure Panel Survey, we derive a difference-in-difference-in-differences estimator using a multivariate regression framework, and measure Part D's effects on disparities in any hospitalization, the number of nights hospitalized, and inpatient expenses. Part D narrowed racial/ethnic disparities in hospital utilization. For African Americans, it reduced the disparity in any hospitalization by 2.94% (p < .001) but had no effect on disparities in nights hospitalized or inpatient expenses. For Hispanics, Part D reduced disparities in nights hospitalized by 1.58 nights (p = .009) and in inpatient expenses by US$3,453 (p < .001). Following Medicare Part D, disparities in hospital utilization narrowed significantly for both African American and Hispanic seniors, but in different ways for each population. © The Author(s) 2015.
    Journal of Aging and Health 02/2015; 27(5). DOI:10.1177/0898264315569450 · 1.56 Impact Factor
  • Source
    • "remain unanswered and an important issue for research . This analysis is not without limitations . First , the most suitable com - parison group would have been a group of Medicare beneficiaries aged 65 and older who were not eligible for Part D . Unfortunately , no such group exists , so like most prior studies ( Basu , Yin , and Alexander 2010 ; Liu et al . 2011 ) , we chose adults aged 55 – 63 without Medicare as our comparison group . Second , our DDD research design is unable to fully disentangle the effects of Part D from the effects of changes in Medicare ' s MA program that were also occurring post - 2003 ( McGuire , Newhouse , and Sinaiko 2011 ) . Thus , the changes in disparities uncove"
    [Show abstract] [Hide abstract]
    ABSTRACT: To evaluate whether Medicare Part D has reduced racial/ethnic disparities in prescription drug utilization and spending. Nationally representative data on white, African American, and Hispanic Medicare seniors from the 2002-2009 Medical Expenditure Panel Survey are analyzed. Five measures are examined: filling any prescriptions during the year, the number of prescriptions filled, total annual prescription spending, annual out-of-pocket prescription spending, and average copay level. We apply the Institute of Medicine's definition of a racial/ethnic disparity and adopt a difference-in-difference-in-differences (DDD) estimator using a multivariate regression framework. The treatment group consists of Medicare seniors, the comparison group, adults without Medicare aged 55-63 years. Difference-in-difference-in-differences estimates suggest that for African Americans Part D increased the disparity in annual spending on prescription drugs by $258 (p = .011), yet had no effect on other measures of prescription drug disparities. For Hispanics, DDD estimates suggest that the program reduced the disparities in annual number of prescriptions filled, annual total and out-of-pocket spending on prescription drugs by 2.9 (p = .077), $282 (p = .019) and $143 (p < .001), respectively. Medicare Part D had mixed effects. Although it reduced Hispanic/white disparities related to prescription drugs among seniors, it increased the African American/white disparity in total annual spending on prescription drugs.
    Health Services Research 09/2013; 49(2). DOI:10.1111/1475-6773.12099 · 2.78 Impact Factor
  • Source
    02/2012; 10(1):2-13. DOI:10.1016/j.amjopharm.2012.01.004
Show more