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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
Clinical Efficacy: A Cost Containment Weapon for the 21st Century
Lonny Reisman, MD, Chief Executive Officer, HealthReveal
Opportunity Costs of Ambulatory Medical Care in the United States
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
Addressing the Primary Care Workforce Crisis
Zirui Song, MD, PhD; Vineet Chopra, MD, MSc; and Laurence F. McMahon, Jr, MD, MPH
The Association Among Medical Home Readiness, Quality, and Care of Vulnerable Patients
Lena M. Chen, MD, MS; Joseph W. Sakshaug, PhD; David C. Miller, MD, MPH; Ann-Marie Rosland, MD, MS; and John Hollingsworth, MD, MS
Trends in Public Perceptions of Electronic Health Records During Early Years of Meaningful Use
Jessica S. Ancker, MPH, PhD; Samantha Brenner, MD; Joshua E. Richardson, PhD, MLIS, MS; Michael Silver, MS; and Rainu Kaushal, MD, MPH
Feasibility of Integrating Standardized Patient-Reported Outcomes in Orthopedic Care
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.
With 1 exception, total standardized spending, as well as each of the 3 categories of spending, was markedly lower for MA HMO enrollees than for matched TM enrollees (Table 2). For instance, total spending was 19% less for diabetics enrolled in MA than for those enrolled in TM ($5223 vs $6413; P <.001). The single exception was for diabetics without comorbidity (eg, inpatient spending of $1309 for MA vs $925 for TM; P <.001). Visits to the ED were consistently lower in MA, as were rates of hospital inpatient discharges. Similar results were observed for those enrolled in PPOs (eAppendix Table 2).

Spending and Utilization by Type of Health Plan

Patterns of comparative price-standardized utilization by type of plan are presented in Figures 1 and 2 respectively (eAppendix Table 3 shows the detailed results). For large, established, nonprofit HMOs, all 3 categories of spending were lower than for the matched TM sample, with differences ranging from 16% (evaluation and man-agement services for diabetics) to 70% (surgery rates for those with cardiovascular disease). In contrast, results were mixed for new, for-profit, small HMOs, where aggregate spending was higher in some categories in MA (eg, inpatient spending for cardiovascular disease, 16% higher), and lower for others (eg, surgery and procedures 43% lower for diabetics in MA). Results for PPO health plans were similar to those for new, for-profit, small HMOs.

Spending and Quality of Care by Health Plan Characteristics

The mean plan-weighted rates of A1C testing, LDL cholesterol testing, and diabetic retinal exams were 89.7%, 87.6%, and 65.2%, respectively. Figure 3 presents scatter plots of HMO health plan spending and the composite measure of quality for the diabetes cohort by health plan age (established prior to 2006 or not), size (>25,000 members), and tax status. Several findings are apparent: first, while members of most health plans experienced higher quality than the matched TM population in their area and therefore are plotted above the solid horizontal axis, the MA-TM difference varied substantially and for some plans was negative (MA worse than TM). Similarly, MA spending was lower than that in TM for most health plans, but the magnitude of the difference varied and was sometimes reversed (plotted to right of solid vertical axis). Second, there was little association between the spending and quality effects (Pearson correlation coefficient, 0.16), as manifested by the nearly equal distribution of plans across the 4 quadrants formed by median splits (dashed lines) on the 2 variables. Finally, although HMO health plans of each type are present in all 4 quadrants of each plot, the upper left hand quadrant (higher quality/lower spending) contains the most established, large, nonprofit HMO plans and the lower right hand quadrant (lower quality/higher spending) contains a higher proportion of new, small, for-profit HMO plans. A similar pattern was seen for the cardiovascular measures (eAppendix Figure).


This study provides the first compre-hensive comparison between MA and TM of price-standardized utilization and quality of care for those with diabetes and cardiovascular disease, 2 prevalent and costly chronic medical conditions. We found several notable results: first, for both cohorts, RRU—which is a measure of total utilization using a standardized set of prices—was lower in MA health plans than in TM in each of the main categories of spending examined. Moreover, MA plans achieved higher performance on measures of ambulatory quality.19 Second, marked heterogeneity was evident among MA plans. Most older, larger, nonprofit health plans were able to achieve substantial reductions in service utilization while delivering care of high quality, whereas many newer, smaller, for-profit plans had similar or greater utilization when compared with TM. Finally, utilization among PPOs—an alternative arrangement to HMOs that is generally less managed and coordinated—showed patterns that were similar to new, smaller HMOs and to TM.

Policy Implications

Our findings have important implications for policy. With the 2010 passage of the Affordable Care Act (ACA), the attention of policy makers has now shifted to controlling the seemingly inexorable growth in healthcare costs.20 Delivering high-value care requires decreasing utilization of services of low value while simultaneously maintaining or increasing the delivery of services of high value. We show that substantial numbers of larger, nonprofit HMO MA plans appear to be delivering care of high quality, while doing so with substantially fewer resources. Whether this is more due to their actions, as payers perhaps linked to their size and ability to influence provider behavior, or to use of more limited and selected networks of providers, or both, is unknown. Although there has been much focus on payment reform in TM—such as the launching of accountable care organizations (ACOs)—30% of Medicare enrollees are in MA health plans, a far larger proportion than are currently in ACOs.21

MA plans are currently paid more than TM on average.22 Because of Medicare regulations and competitionamong plans, many of the savings from these extra payments and the reduced utilization we documented in this study are passed through to beneficiaries in the form of lower premiums, less cost sharing, and benefits for noncovered services.23 However, providers may also profit from these excess payments, as they may be able to negotiate higher prices from MA plans. To finance its expansion of health insurance, the ACA reduced reimbursement for MA plans; how these reductions will impact plan and beneficiary participation and the future growth of the MA program remains an open question.

Although MA plans as a whole were able to achieve substantially lower utilization rates, we found considerable heteroge-neity among health plan types, consistent with earlier analyses.5,24 In particular, larger, more established (mostly nonprofit) health plans were able to deliver care of high quality at substantially lower cost. Health plans may use a variety of approaches to influence the costs and quality of care,25 ranging from contractually based incentives and pay-for-performance to care management programs directed to either patients or physicians, and utilization management programs such as prior authorization requirements. Future research will be needed to elucidate more fully how health plans have achieved these savings and what the most effective approaches might be.


An important limitation of our research is that our quality measures were limited to basic ambulatory services, and we lacked measures of more complex services (eg, appropriate use of coronary revascularization procedures, such as coronary artery bypass graft surgery, for which rates are higher in MA health plans10) and outcomes of care. Ultimately, healthcare organizations must be evaluated on their success at controlling spending while improving both intermediate clinical outcomes (eg, control of blood pressure) and ultimate outcomes such as risk-adjusted mortality. Larger, more establishedHMOs may have greater ability to achieve these goals.25,26 Future extensions of this re-search should evaluate the extent to which health plans achieve savings while improving outcomes of care that are important to patients and delivery systems as a whole.

Our study is subject to several additional limitations. One possible explanation for our findings is favorable selection into MA, as suggested by research using data prior to the time of our study.27 To minimize the impact of such selection effects in our analysis, we matched MA and TM enrollees by age, sex, race/ethnicity, and geographic area, usually at the zip code level, which in the aggregate created cohorts with similar sociodemographic characteristics. Indeed, the health services research literature commonly uses US Census data at this level to impute these characteristics.28-31 We then compared care for patient populations with specific diagnoses, further controlling for clinical characteristics that might be associated with higher spending. Furthermore, favorable selection into MA appears to have fallen considerably in recent years.32-34 Also, our data are now several years old. These data, however, are from the most recent year of RRU data for which CMS required reporting by health plans. Nonetheless, the RRU data made possible analyses that would not otherwise be possible given the unavailability of health plan claims data, despite only covering a limited set of conditions. Finally, the RRU data that health plans submitted to CMS were not fully audited and may have been incompletely reported since they did not affect payment.


Proponents of managed care have long argued that integrated health plans can deliver care more efficiently than traditional fee-for-service care by using their ability to tailor their provider networks to the needs of their population and to implement disease and case management programs to improve chronic disease management.19 In this large national study of enrollees with diabetes or cardiovascular disease, our findings suggest that many Medicare HMO health plans are able to deliver care of equal or better quality with lower RRU than TM.

Author Affiliations: Department of Health Care Policy, Harvard Medical School (BEL, AMZ, JPN, JZA), Boston, MA; Division of Primary Care and General Internal Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (BEL), Boston, MA; National Committee for Quality Assurance (RS), Washington, DC; Stevens and Lee (LGP), Lancaster, PA; Department of Health Policy and Management, Harvard School of Public Health (JPN), Boston, MA; John F. Kennedy School of Government, Harvard University (JPN), Boston, MA; National Bureau of Economic Research (JPN), Cambridge, MA; Institute for Healthcare Policy and Innovation, Gerald R. Ford School of Public Policy, University of Michigan (JZA), Ann Arbor, MI; Division of General Medicine, Medical School, University of Michigan (JZA), Ann Arbor, MI; Department of Health Management and Policy, School of Public Health, University of Michigan (JZA), Ann Arbor, MI.

Source of Funding: This study was supported by a grant from the National Institute on Aging (P01 AG032952). The funding source did not play a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, and approval of the manuscript.

Author Disclosures: Dr Newhouse is a director of and holds equity in Aetna, which sells Medicare Advantage products. Drs Saunders (current) and Pawlson (past) are current or former employees of NCQA, which holds the copyright for HEDIS measures. Dr Ayanian is a consultant to RTI on risk adjustment models for Medicare Advantage health. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (BEL, JZA, AMZ, JPN); acquisition of data (LGP, JPN, RS); analysis and interpretation of data (BEL, JZA, AMZ, JPN, RS); drafting of the manuscript (BEL, LGP); critical revision of the manuscript for important intellectual content (JZA, LGP, AMZ, JPN, RS); statistical analysis (BEL, AMZ, JPN); obtaining funding (BEL, JPN).

Address correspondence to: Bruce E. Landon, MD, MBA, MSc, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02215. E-mail:

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