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The American Journal of Managed Care August 2015
Differential Impact of Mental Health Multimorbidity on Healthcare Costs in Diabetes
Leonard E. Egede, MD, MS; Mulugeta Gebregziabher, PhD; Yumin Zhao, PhD; Clara E. Dismuke, PhD; Rebekah J. Walker, PhD; Kelly J. Hunt, PhD, MSPH; and R. Neal Axon, MD, MSCR
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Lonny Reisman, MD, Chief Executive Officer, HealthReveal
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Kristin N. Ray, MD, MS; Amalavoyal V. Chari, PhD; John Engberg, PhD; Marnie Bertolet, PhD; and Ateev Mehrotra, MD, MPH
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A Comparison of Relative Resource Use and Quality in Medicare Advantage Health Plans Versus Traditional Medicare
Bruce E. Landon, MD, MBA, MSc; Alan M. Zaslavsky, PhD; Robert Saunders, PhD; L. Gregory Pawlson, MD, MPH; Joseph P. Newhouse, PhD; and John Z. Ayanian, MD, MPP
Global Payment Contract Attitudes and Comprehension Among Internal Medicine Physicians
Joshua Allen-Dicker, MD, MPH; Shoshana J. Herzig, MD, MPH; and Russell Kerbel, MD, MBA
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Lena M. Chen, MD, MS; Joseph W. Sakshaug, PhD; David C. Miller, MD, MPH; Ann-Marie Rosland, MD, MS; and John Hollingsworth, MD, MS
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Jessica S. Ancker, MPH, PhD; Samantha Brenner, MD; Joshua E. Richardson, PhD, MLIS, MS; Michael Silver, MS; and Rainu Kaushal, MD, MPH
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James D. Slover, MD, MS; Raj J. Karia, MPH; Chelsie Hauer, MPH; Zachary Gelber, DDS; Philip A. Band, PhD; and Jove Graham, PhD
A Randomized Controlled Trial of Co-Payment Elimination: The CHORD Trial
Kevin G. Volpp, MD, PhD; Andrea B. Troxel, ScD; Judith A. Long, MD; Said A. Ibrahim, MD, MPH; Dina Appleby, MS; J. Otis Smith, EdD; Jane Jaskowiak, BSN, RN; Marie Helweg-Larsen, PhD; Jalpa A. Doshi, PhD; and Stephen E. Kimmel, MD, MSCE
A Randomized Controlled Trial of Negative Co-Payments: The CHORD Trial
Kevin G. Volpp, MD, PhD; Andrea B. Troxel, ScD; Judith A. Long, MD; Said A. Ibrahim, MD, MPH; Dina Appleby, MS; J. Otis Smith, EdD; Jalpa A. Doshi, PhD; Jane Jaskowiak, BSN, RN; Marie Helweg-Larsen, PhD; and Stephen E. Kimmel, MD, MSCE

A Comparison of Relative Resource Use and Quality in Medicare Advantage Health Plans Versus Traditional Medicare

Bruce E. Landon, MD, MBA, MSc; Alan M. Zaslavsky, PhD; Robert Saunders, PhD; L. Gregory Pawlson, MD, MPH; Joseph P. Newhouse, PhD; and John Z. Ayanian, MD, MPP
Compared with traditional Medicare, relative resource use for those with diabetes or cardiovascular disease is lower in Medicare Advantage, while quality of care is higher.

Objectives: Prior analyses of Medicare health plans have exam-ined either utilization of services or quality of care, but not both jointly. Our objective was to compare utilization and quality for Medicare Advantage (MA) enrollees with diabetes or cardiovascular disease to that for similarly defined traditional Medicare (TM) beneficiaries.

Study Design: Cross-sectional matched observational study using data for 2007.

Methods: We obtained individual-level Healthcare Effectiveness Data and Information Set (HEDIS) relative resource use (RRU) and quality data for patients enrolled in MA, and then developed comparable claims-based measures for matched samples of TM beneficiaries. Main outcome measures: utilization levels for inpatient care, evaluation and management services, and surgery; number of emergency department (ED) and inpatient visits; and quality of ambulatory care measures.

Results: We studied approximately 680,000 MA health maintenance organization (HMO) enrollees with diabetes and 270,000 HMO enrollees with cardiovascular conditions. For both conditions and almost all major strata, the RRU was lower for those enrolled in MA than for those in TM. Spending for those with diabetes was $5223 for MA HMO enrollees compared with $6413 for those in TM (cost ratio, 0.81; P <.001). ED utilization rates were consistently lower in MA than TM (567 vs 719 visits/1000 enrollees; rate ratio, 0.79; P <.001). Health plans that are more established, nonprofit, and/or larger generally had lower resource use and better relative quality than did smaller, newer, for-profit HMOs or preferred provider organizations.

Conclusions: RRU for those with diabetes or cardiovascular disease is lower in MA, while quality of care is higher. Better MA plans may add value to the care of these major chronic medical conditions.

Am J Manag Care. 2015;21(8):559-566
Take-Away Points

We compared price-standardized utilization and quality of care for Medicare Advan-tage (MA) enrollees with diabetes or cardiovascular disease with matched beneficiaries from traditional Medicare in geographic areas. We found that:
  • For both conditions, relative resource use was lower for those enrolled in MA than for those in traditional Medicare.
  • Quality of care for diabetes and cardiovascular disease measures was higher in MA for the 4 measures examined, although plans varied greatly in their performance.
  • Health plans that are more established, nonprofit, and/or larger generally had lower relative resource use and better relative quality than did HMOs or PPOs that were smaller, newer, and/or for-profit.
Under managed competition, health plans are expected to compete to provide health services of high quality while also controlling the overall costs of care. A key element of a health plan’s ability to contain cost is its ability to control utilization. Although some transparency initiatives are now publicizing the costs that health plans pay for specific services,1 such approaches have not assessed differences in the full range of medical services used by patients with particular health conditions. Moreover, many have concerns that health plans that are more successful at controlling utilization might also deliver care of lower quality, though existing data from commercial health plans show no clear relationship between spending and quality.2,3

Medicare’s managed care program, Medicare Advantage (MA), currently provides care to 15.7 million Americans, representing 30% of beneficiaries.4 Relative to traditional Medicare (TM), MA plans may be able to treat patients with particular diagnoses with greater efficiency while attaining equal or superior quality through their flexibility in enrollee benefits, network contracting, and coordination of care, but whether they do so is not known.5 Since 1997, health plans participating in Medicare have been required to report annually on measures of the quality of preventive care and of the management of chronic diseases such as diabetes.6-8 In 2006 and 2007, CMS also required MA plans to report a set of relative resource use (RRU) measures focused on the care of patients with diabetes (2006 and 2007) and cardiovascular disease (2007 only).9 Such measures of price-adjusted utilization allow for direct comparisons of utilization among health plans as well as between MA and TM.

In this study, we evaluated both the utilization of services and the quality of ambulatory care provided by MA health plans by comparing annual standardized spending and quality of care for 2 specific medical conditions for MA health plan enrollees with corresponding measures among TM beneficiaries.



From CMS and the National Committee for Quality As-surance (NCQA), we obtained health-plan-level Healthcare Effectiveness Data and Information Set (HEDIS) measures of RRU and individual-level HEDIS data on quality of ambulatory care for patients with diabetes and cardiovascular disease enrolled in MA health plans. We focused on care delivered in 2007, the most recent year in which MA plans were required to report these measures before reporting became voluntary and much less consistent.2,3 We constructed similar measures within TM from Medicare claims data for a random 20% sample of beneficiaries. Given the well-known geographic variation in Medicare services, we created matched samples for each health plan based on its geographic region and enrollee demographic characteristics.7,10

Data Sources and Measures

Medicare Advantage. The RRU measures use standardized pricing applied uniformly to services delivered within MA and TM, thereby accounting for variation in prices due to geography and negotiated prices in MA.9 Spending on all services for all patients with qualifying diagnoses is calculated over the entire year. The RRUs are risk-stratified by age (categorized into 5-year intervals for patients aged 65-85 years), sex, type of diabetes (type 1 or type 2) or cardiovascular disease (acute myocardial infarction, congestive heart failure, angina, or coronary artery disease) and the presence or absence of 1 or more major comorbidities (ie, cardiovascular conditions, chronic obstructive pulmonary disease [COPD], depression, hypertension, or chronic kidney disease for diabetes, and asthma, COPD, diabetes, and hypertension for cardiovascular disease). We then aggregated these strata using nationally determined weights to create a standardized measure of overall resource use. Spending categories include inpatient care, surgery and other procedures, and evaluation and management services, and we also sum spending across these categories. Rates of emergency department (ED) visits and inpatient admissions are also reported. Beneficiaries with concomitant specified dominant medical conditions including active cancer, end-stage renal disease, human immunodeficiency virus/AIDS, and organ transplants are excluded.

HEDIS quality data are collected from administrative billing or encounter records, or by using a hybrid approach in which medical records are also reviewed for services that may not be recorded in administrative data.7,11 CMS has audited HEDIS quality measures reported by Medicare health maintenance organizations (HMOs) and found them to be highly accurate.12 In order to compare MA and TM, we focused on measures that can be constructed from Medicare claims for TM enrollees, including low-density lipoprotein (LDL) cholesterol testing in the current year for enrollees aged 65 to 75 years with cardiovascular disease, and 3 services for enrollees aged 65 to 75 years with diabetes: glycated hemoglobin (A1C) testing in the current year; LDL cholesterol testing in the current year; and a diabetic retinal exam in the current or prior year.

We defined health plans as CMS contracts, meaning a health plan unit operating in a single state, or in a few cases, up to 3 adjoining states, and we included both HMOs and preferred provider organizations (PPOs). We focused on beneficiaries 65 years or older who were enrolled for the entire calendar year. We excluded beneficiaries in legacy health plans that were reimbursed on a cost basis rather than by capitation. In addition, we excluded beneficiaries in private fee-for-service plans because these plans are not required to report HEDIS data to CMS, as well as those enrolled in special needs plans because such plans serve nonrepresentative beneficiaries. Finally, we excluded HMOs with fewer than 500 enrollees (accounting for <0.2% of enrollees).7,10

Traditional Medicare. To create a comparison sample for each health plan for both the RRU and the diabetes quality analyses, we used the TM enrollment file and Part A and Part B claims files for a random 20% of beneficiaries to identify all persons who were continuously enrolled in Medicare Part A and Part B for the entire reporting year and were 65 years or older as of January 1, 2007.13,14 We excluded residents of long-stay nursing homes—identified using a validated algorithm—because these beneficiaries rarely enroll in MA; however, we had no similar method to exclude these beneficiaries from the MA data.15,16 We applied NCQA specifications to identify the eligible populations for the measures, assigned a standardized priceobtained from NCQA to each delivered service identified in the claims, and aggregated spending across groups using the exact specifications from NCQA.

Medicare Beneficiary Summary files provided demographic data (age, sex, race/ethnicity, zip code, county, and state of residence), vital status, and health plan and Medicare enrollment information for each beneficiary.

Health Plan Characteristics

We categorized health plans as large (>25,000 enrollees) versus small, and identified health plans new to MA since 2006. CMS provided the tax status.

Statistical Analyses

We compared RRUs and quality of care in each MA plan with a TM sample matched by geographic distribution (RRUs and quality measures) and demographic characteristics (quality measures only) and then aggregated these results to obtain national estimates. For the RRU measures, the control TM population was weighted to match the exact distribution of health plan enrollees across all zip codes in which it operated. Matching on geography controlled for variation in practice patterns within Medicare across regions.17,18 By matching at the zip code level where possible, we also controlled for unmeasured socioeconomic characteristics associated with residence at this level of geography.

To provide nationally representative estimates of over-all HMO and PPO performance relative to traditional Medicare, we averaged HEDIS RRUs and quality mea-sures, respectively, over MA plans and matched cohorts of traditional Medicare enrollees, weighted by MA enrollment. To assess variation in performance of health plans based on particular characteristics relative to matched traditional Medicare in local areas, we used hierarchical regression models with correlated bivariate random effects for each health plan and its matched traditional Medicare sample and fixed effects for the health plan characteristics noted above, including an indicator vari-able for PPOs, with separate coefficients for the MA and traditional Medicare samples. Because more than 80% of PPOs were small, new, and for-profit, the PPO measure pertains to just this category of PPOs (the few other PPOs were not included in these models).

Finally, for each HMO plan, we created a composite of the 3 diabetes quality measures by taking the mean across the measures, and similarly created an aggregate measure of spending by summing over the 3 spending categories: inpatient care, surgery and other procedures, and evaluation and management services. We constructed similar summary measures of quality and spending for the matched TM cohort for each health plan. We then plotted mean quality relative to the local TM comparison group against mean spending relative to the same comparison group to provide a visual representation of the marginal contribution versus TM for each health plan. We also created a similar plot for the cardiovascular cohort using the single quality measure available for this group.

Analyses were conducted with SAS version 9.2 (SAS Institute, Cary, North Carolina). Two-tailed P values are reported for statistical tests. Our study protocol was approved by the Human Studies Committee of Harvard Medical School and the CMS Privacy Board.


Characteristics of the Medicare HMOs and PPOs in our study appear in Table 1. We studied data from 190 HMOs and 67 PPOs that included 4,207,433, and 318,293 enrollees, respectively, in 2007. About two-thirds of enrollees were in for-profit health plans. Although 75% of the health plans were small (<25,000 members), these HMOs represented only about 25% of enrollment. Most HMOs had participated in Medicare prior to 2006, but only 11 PPOs had done so.

The MA HMOs in our study enrolled approximately 680,000 beneficiaries with diabetes (and the PPOs approximately 50,000) and approximately 268,000 enrollees with 1 of the 4 cardiovascular conditions (and approximately 12,000 PPO enrollees; sample sizes vary slightly by measure). For the diabetes cohort, just under half were male (48.8%) and more than 80% were white. The largest proportion was from the south and more than 85% had at least 1 comorbid condition (eAppendix Table 1, available at After weighting the TM sample to match the MA distribution, the 2 samples had identical demographic characteristics.

Utilization in MA and TM by Types of Diabetes and Cardiovascular Disease

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