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, 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 1: The Content, Quality, and Accessibility of Care. Ann Intern Med. 2003;138:273-287. doi: 10.7326/0003-4819-138-4-200302180-00006
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Published: Ann Intern Med. 2003;138(4):273-287.
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.
Per capita Medicare spending varies considerably from region to region. The effect of greater Medicare spending on quality of care and access 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 better quality or outcomes of care.
Medicare beneficiaries who live in higher Medicare spending regions do not necessarily get better-quality care than those in lower-spending regions.
Overview of study design.
Average per capita Medicare spending, health care resource levels, and other key attributes of U.S. hospital referral regions according to quintiles of spending.
Table 1. Characteristics of the Hip Fracture Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Table 2. Characteristics of the Colorectal Cancer Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Table 3. Characteristics of the Acute Myocardial Infarction Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Table 4. Characteristics of the Medicare Current Beneficiary Survey Cohort according to Level of Medicare Spending in Hospital Referral Region of Residence
Per capita utilization of hospital and physician services during follow-up by study cohorts.
Utilization of physician services across quintiles of spending for the Medicare Current Beneficiary Survey cohort, 19921996.
Relative rate and 95% CIs of specific services provided to cohort members residing in the highest quintile of Medicare spending compared with those residing in the lowest quintile for the three chronic disease cohorts combined.
Table 5. Quality of Care according to Level of Medicare Spending in Hospital Referral Region of Residence
Percentage of patients in the acute myocardial infarction cohort who received the specified therapy (among ideal candidates), according to type of hospital and quintile of Medicare spending.PP
Table 6. Access to Care according to Level of Medicare Spending in Hospital Referral Region of Residence
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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