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
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 author 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 Institutes of Health (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, email@example.com.
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.
Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder ÉL. The Implications of Regional Variations in Medicare Spending. Part 2: Health Outcomes and Satisfaction with Care. Ann Intern Med. 2003;138:288-298. doi: 10.7326/0003-4819-138-4-200302180-00007
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Published: Ann Intern Med. 2003;138(4):288-298.
The health implications of regional differences in Medicare spending are unknown.
To determine whether regions with higher Medicare spending achieve better survival, functional status, or satisfaction with 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 (MCBS) (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).
5-year mortality rate (all four cohorts), change in functional status (MCBS cohort), and satisfaction (MCBS cohort).
Cohort members were similar in baseline health status, but those in regions with higher end-of-life spending received 60% more care. Each 10% increase in regional end-of-life spending was associated with the following relative risks for death: hip fracture cohort, 1.003 (95% CI, 0.999 to 1.006); colorectal cancer cohort, 1.012 (CI, 1.004 to 1.019); acute myocardial infarction cohort, 1.007 (CI, 1.001 to 1.014); and MCBS cohort, 1.01 (CI, 0.99 to 1.03). There were no differences in the rate of decline in functional status across spending levels and no consistent differences in satisfaction.
Medicare enrollees in higher-spending regions receive more care than those in lower-spending regions but do not have better health outcomes or satisfaction with care. Efforts to reduce spending should proceed with caution, but policies to better manage further spending growth are warranted.
Per capita Medicare spending varies considerably from region to region. The effect of greater Medicare spending on mortality, functional status, and satisfaction is not known.
Using end-of-life care spending as an indicator of Medicare spending, the researchers categorized geographic regions into five quintiles of spending and examined costs and outcomes of care for hip fracture, colorectal cancer, and acute myocardial infarction. Residents of high-spending regions received 60% more care but did not have lower mortality rates, better functional status, or higher satisfaction.
Medicare beneficiaries who live in higher Medicare spending regions do not necessarily have better health outcomes or satisfaction with health care than those in lower-spending regions.
Table 1. Crude and Predicted Mortality Rates in Study Cohorts according to Level of Medicare Spending in Hospital Referral Region of Residence
Table 2. Adjusted Relative Risk for Death across Quintiles of Medicare Spending and Relative Risk Associated with a 10% Increase in Medicare Spending, as Estimated by Using the Acute Care Expenditure Index (Sensitivity Analysis)
Table 3. Average Change per Year in Functional Status on Health Activities and Limitation Index among Participants in the Medicare Current Beneficiary Survey according to Medicare Spending in the Hospital Referral Region of Residence
Adjusted relative risk for death during follow-up across quintiles of Medicare spending.
Adjusted relative risk for death associated with a 10% increase in Medicare spending overall and among specified subgroups of the hip fracture cohort.
Adjusted relative risk for death associated with a 10% increase in Medicare spending overall and among specified subgroups of the colorectal cancer cohort.
Adjusted relative risk for death associated with a 10% increase in Medicare spending overall and among specified subgroups of the acute myocardial infarction ( MI
Satisfaction with care.
Appendix Table 1. Characteristics of the Hip Fracture Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Appendix Table 2. Characteristics of the Colorectal Cancer Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Appendix Table 3. Characteristics of the Acute Myocardial Infarction Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Appendix Table 4. Characteristics of the Medicare Current Beneficiary Survey Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Appendix Table 5. Summary of Variables Used in Cohort Analyses
Appendix Table 6. Survival Model for the Hip Fracture Cohort
Appendix Table 7. Survival Model for the Colorectal Cancer Cohort
Appendix Table 8. Survival Model for the Acute Myocardial Infarction Cohort
Appendix Table 9. Survival Model for the Medicare Beneficiary Survey Cohort
Appendix Table 10. Models Testing the Association between the End-of-Life Expenditure Index and Change in Scores on the Health Activities and Limitations Index
Appendix Table 11. Specific Services Provided to Chronic Disease Cohorts during First Year of Follow-up
Appendix Table 12. Unadjusted Utilization Rates of Hospital and Physician Services, by Specified Subgroups of the Hip Fracture Cohort
Appendix Table 13. Unadjusted Utilization Rates of Hospital and Physician Services, by Specified Subgroups of the Colorectal Cancer Cohort
Appendix Table 14. Unadjusted Utilization Rates of Hospital and Physician Services, by Specified Subgroups of the Acute Myocardial Infarction Cohort
Appendix Table 15. Impact of Chronic Conditions on Functional Status Scores
Appendix Table 16. Reference Populations Used To Calculate the Acute Care Expenditure Index for Each Cohort
Appendix Table 17. Average Predicted Mortality Rate across Quintiles of the Acute Care Expenditure Index
Appendix Table 18. Ratio of Risk-Adjusted Utilization Rates for Each Cohort in the Specified Quintile of Medicare Spending to Spending in the Lowest-Cost Regions
Appendix Table 19. Association between Acute Care Expenditure Index in Hospital Referral Region of Residence and Cohort-Specific Risk-Adjusted Long-Term Mortality Rates (Sensitivity Analysis)
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