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How Will Provider-Focused Payment Reform Impact Geographic Variation in Medicare Spending?

David Auerbach, PhD, MS; Ateev Mehrotra, MD, MPH; Peter Hussey, PhD; Peter J. Huckfeldt, PhD; Abby Alpert, PhD; Christopher Lau, PhD; and Victoria Shier, MA
Unlike ACOs or P4P, implementation of bundled payment for inpatient and post acute care in Medicare would modestly reduce geographic variation in spending.
To the extent that reduction in geographic variation in Medicare spending remains a national priority, our results provide insight on how the policies we investigated could be adjusted to achieve that goal. Instead of the set of measures we employed, a set of P4P quality measures could be identified in which high-cost areas of the United States have particularly low quality (eg, readmission rates); that would ensure a transfer of funds from high-cost regions with poor quality scores to low-cost regions with high scores. Also, policy makers could identify barriers to ACO formation in high-cost areas and consider ways to encourage such ACOs to develop. The reach of bundled payment could be extended by broadening the definition of spending included within the bundle (for example, increasing time period to 90 days) or by applying the policy to additional conditions. Applying bundled payment only to hospitals exceeding a minimum volume of bundles could reduce financial risk, but may reduce the impact on geographic variation as well.

We also acknowledge that other interventions could be employed (or are underway) that could also result in a reduction in geographic variation in Medicare spending. For example, adjustments to the Medicare Physician Fee Schedule that favor primary care relative to specialty care could reduce variation if high-cost areas tend to use more specialty care.11 If high-cost regions have more inefficient or low-value care, then policies that directly target inefficient care such as potentially avoidable hospitalizations may be another mechanism to reduce geographic variation. Whether high-cost regions have much higher prevalence of low-value care is unclear.12


Our estimates have some important limitations. First, the scenarios were designed to represent realistic versions of policies that could be implemented in the near future. We therefore relied upon scenarios that closely resembled current Medicare pilots or programs. However, different implementations of these policies could result in a different impact on spending. We explored some of these alternatives in our sensitivity analyses. Second, our results are limited by the available data. For example, in our ACO analyses we allocated beneficiaries to HRRs based on the location of primary care physicians, which only approximates true beneficiary locations. Also, a new set of ACOs was announced in January 2013, too late for inclusion in our analysis. It is possible that inclusion of these newest ACOs would alter our results.

Third, we focused on geographic variation in spending across HRRs. While HRRs are commonly used to examine geographic variation, we recognize that there is notable heterogeneity in spending within HRRs.6,13 Finally, we made only limited assumptions about provider behavior in response to these policies that we felt had a plausible basis in the literature. For example, in the case of bundled payment, we assumed that providers would react to the payment change by either reducing utilization within bundles of services or accepting reduced margins, but that they would not change the number of bundles provided or utilization of services outside of the bundle. However, we acknowledge that if actual behaviors differ systematically from our assumptions—and in particular, if providers in high-cost regions reacted differently from those in low-cost regions—the impact of these policies on geographic variation in spending could differ. As these policies begin to be implemented in pilot form, there may be evidence forthcoming on behavioral responses that would improve future policy design.


In summary, our results are useful to policy makers seeking solutions to the problem of unwarranted geographic variation in spending. Under a set of reasonable choices for implementing the policies we analyzed, we find that while they would reallocate a substantial portion of Medicare payments, P4P and ACOs are unlikely to reduce geographic variation in spending, and bundled payment would only modestly do so. The policies could be reengineered somewhat to have greater impact on this metric, but it is unclear if reduction in geographic variation in Medicare should be a goal, in and of itself, rather than more efficient delivery of care. 

Author Affiliations: RAND Corporation (DA), Boston, MA; Department of Health Care Policy, Harvard Medical School (AM), Boston, MA; RAND Corporation, Arlington, VA (PH), Santa Monica, CA (PJH, CL, VS); Paul Merage School of Business at University of California, Irvine (AA), Irvine, CA.

Source of Funding: The project was funded by the Institute of Medicine (IOM; a part of the umbrella organization, the National Academy of Sciences). Funding for the study ultimately derived from CMS via the Affordable Care Act, which contracted with the IOM.

Author Disclosures: The 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 (DA, MA, AA, PJH, PH); acquisition of data (DA, MA, AA, PJH, PH); analysis and interpretation of data (DA, CL, MA, AA, PJH, PH, VS); drafting of the manuscript (DA, CL, PJH, VS); critical revision of the manuscript for important intellectual content (DA, CL, MA, PH); statistical analysis (DA, PJH); provision of patients or study materials (DA); obtaining funding (DA, MA, PH); administrative, technical, or logistic support (DA, VS); and supervision (DA).

Address correspondence to: David Auerbach, PhD, MS, RAND Corporation, 20 Park Plz, Ste 920, Boston, MA 02116. E-mail: 


1. Zuckerman S, Waidmann T, Berenson R, Hadley J. Clarifying sources of geographic differences in Medicare spending. N Engl J Med. 2010;363(1):54-62.
2. Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. The implications of regional variations in Medicare spending. part 1: the content, quality, and accessibility of care. Ann Intern Med. 2003;138(4):273-287.
3. Sirovich BE, Gottlieb DJ, Welch HG, Fisher ES. Variation in the tendency of primary care physicians to intervene. Arch Int Med. 2005;165(19):2252-2256.
4. Landrum MB, Meara ER, Chandra A, Guadagnoli E, Keating NL. Is spending more always wasteful? the appropriateness of care and outcomes among colorectal cancer patients. Health Aff (Millwood). 2008;27(1):159-168.
5. Congressional Budget Office. Budget Options Volume 1: Health Care. Washington, DC; 2008. Accessed May 2015.
6. Institute of Medicine. Geographic Variation in Health Care Spending and Promotion of High-Value Care—Interim Report. Washington, DC; National Academies Press; 2013.
7. HRR level demographic, cost, utilization, and quality data. CMS website. Accessed February 13, 2013.
8. Steinbrook R. The role of the emergency department. N Engl J Med. 1996;334(10):657-658.
9. CMS. Proposed rule versus final rule for accountable care organizations (ACOs) in the Medicare Shared Savings Program. Accessed May 2015.
10. Song Z, Safran DG, Landon BE, et al. The ‘Alternative Quality Contract,’ based on a global budget, lowered medical spending and improved quality [published online July 2012]. Health Aff (Millwood). 2012;31(8):1885-1894.
11. Baicker K, Chandra A. Medicare spending, the physician workforce, and beneficiaries’ quality of care. Health Aff (Millwood). 2004;23(3):w184-w197.
12. Schwartz AL, Landon BE, Elshaug AG, Chernew ME, McWilliams JM. Measuring low-value care in Medicare. JAMA Intern Med. 2014;174(7):1067-1076.
13. Congressional Budget Office. Geographic Variation in Health Care Spending. Washington, DC: Congressional Budget Office; 2008. Accessed May 2015.
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