Elliott S. Fisher, MD, MPH; David E. Wennberg, MD, MPH; Thrse A. Stukel, PhD; Daniel J. Gottlieb, MS; F. L. Lucas, PhD; Étoile L. Pinder, MS
Acknowledgments: The authors thank the staff of the Northeast Health Care Quality Foundation for assistance in preparing the Cooperative Cardiovascular Project data.
Disclaimer: The analyses of the Cardiovascular Cooperative Project data were performed under contract number 500-99-NH01, titled Utilization and Quality Control Peer Review Organization for the State of New Hampshire, sponsored by the Centers for Medicare & Medicare Services (formerly the Health Care Financing Administration), Department of Health and Human Services. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government.
The authors assume full responsibility for the accuracy and completeness of the analyses presented. This article is a direct result of the Health Care Quality Improvement Program initiated by the Centers for Medicare & Medicare Services, which has encouraged identification of quality improvement projects derived from analysis of patterns of care, and therefore required no special funding on the part of this contractor. Ideas and contributions to the authors concerning experience with issues presented are welcomed.
The opinions expressed herein are those of the authors alone and do not necessarily reflect those of the Centers for Medicare & Medicare Services, the Robert Wood Johnson Foundation, or the Department of Veterans Affairs.
Grant Support: By the Robert Wood Johnson Foundation, the National Cancer Institute (CA52192), and the National Institute of Aging (1PO1 AG19783-01).
Potential Financial Conflicts of Interest: None disclosed.
Requests for Single Reprints: Elliott S. Fisher, MD, MPH, Strasenburgh Hall, HB 7251, Dartmouth Medical School, Hanover, NH 03755; VA Outcomes Group, White River Junction Veterans Affairs Medical Center, White River Junction, VT 05001; e-mail, firstname.lastname@example.org.
Current Author Addresses: Dr. Fisher, Mr. Gottlieb, and Ms. Pinder: Strasenburgh Hall, HB 7251, Dartmouth Medical School, Hanover, NH 03755.
Drs. Wennberg and Lucas: Maine Medical Center, 22 Bramhall Street, Portland, ME 04102.
Dr. Stukel: Institute for Clinical Evaluative Sciences, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada.
Author Contributions: Conception and design: E.S. Fisher, D.E. Wennberg, T.A. Stukel, .L. Pinder.
Analysis and interpretation of the data: E.S. Fisher, D.E. Wennberg, T.A. Stukel, D.J. Gottlieb, F.L. Lucas, .L. Pinder.
Drafting of the article: E.S. Fisher, D.E. Wennberg, T.A. Stukel, D.J. Gottlieb, .L. Pinder.
Critical revision of the article for important intellectual content: E.S. Fisher, D.E. Wennberg, D.J. Gottlieb, F.L. Lucas.
Final approval of the article: E.S. Fisher, D.E. Wennberg, T.A. Stukel, D.J. Gottlieb, F.L. Lucas, .L. Pinder.
Statistical expertise: T.A. Stukel, D.J. Gottlieb.
Obtaining of funding: E.S. Fisher.
Administrative, technical, or logistic support: .L. Pinder.
Collection and assembly of data: E.S. Fisher, D.J. Gottlieb, .L. Pinder.
The health implications of regional differences in Medicare spending are unknown.
To determine whether regions with higher Medicare spending provide better care.
National study of Medicare beneficiaries.
Patients hospitalized between 1993 and 1995 for hip fracture (n = 614 503), colorectal cancer (n = 195 429), or acute myocardial infarction (n = 159 393) and a representative sample (n = 18 190) drawn from the Medicare Current Beneficiary Survey (19921995).
End-of-life spending reflects the component of regional variation in Medicare spending that is unrelated to regional differences in illness. Each cohort member's exposure to different levels of spending was therefore defined by the level of end-of-life spending in his or her hospital referral region of residence (n = 306).
Content of care (for example, frequency and type of services received), quality of care (for example, use of aspirin after acute myocardial infarction, influenza immunization), and access to care (for example, having a usual source of care).
Average baseline health status of cohort members was similar across regions of differing spending levels, but patients in higher-spending regions received approximately 60% more care. The increased utilization was explained by more frequent physician visits, especially in the inpatient setting (rate ratios in the highest vs. the lowest quintile of hospital referral regions were 2.13 [95% CI, 2.12 to 2.14] for inpatient visits and 2.36 [CI, 2.33 to 2.39] for new inpatient consultations), more frequent tests and minor (but not major) procedures, and increased use of specialists and hospitals (rate ratio in the highest vs. the lowest quintile was 1.52 [CI, 1.50 to 1.54] for inpatient days and 1.55 [CI, 1.50 to 1.60] for intensive care unit days). Quality of care in higher-spending regions was no better on most measures and was worse for several preventive care measures. Access to care in higher-spending regions was also no better or worse.
Regional differences in Medicare spending are largely explained by the more inpatient-based and specialist-oriented pattern of practice observed in high-spending regions. Neither quality of care nor access to care appear to be better for Medicare enrollees in higher-spending regions.
Fisher ES, Wennberg DE, Stukel TA, et al. The Implications of Regional Variations in Medicare Spending. Part 1: The Content, Quality, and Accessibility of Care. Ann Intern Med. 2003;138:273–287. doi: https://doi.org/10.7326/0003-4819-138-4-200302180-00006
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Published: Ann Intern Med. 2003;138(4):273-287.
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