Geography of Medicare

1. Geography of Medicare By David M. Cutler and Louise Sheiner American Economic Review Vol. 89 No. 2 1999 Cliff Gagnier

2. Research Questions • In 1997, regional Medicare payments averaged $5,182 with a stand deviation of $897 • What factors account for regional differences in Medicare spending? • Are there regional inefficiencies that can be corrected by policy?

3. Three Theories • 1: Spending variation is due to regional differences in illness • 2: Spending variation is due to differences in demand factors, ex. demographic factors, insurance coverage • 3: Spending variation is due to the structure of medical care markets, ex. generalists vs. specialists

4. Data Source • 1998 Dartmouth Atlas of Health Care • Contains information on Medicare spending for 212 hospital referral regions (HRR’s) • Authors use HHR’s for the data values of metropolitan statistical areas (MSA’s) • The authors state that HHR’s are closely aligned with MSA’s

5. Method • Correlation of Medicare spending across MSA’s • Authors compared spending within MSA’s overtime • 15 year and 25 year time periods

6. Results • After 15 years, correlation = 70% • After 25 years, correlation = 40% • Therefore Illness does not vary greatly by region over time

7. Method • Explaining Medicare spending across areas • Variables implied in the three theories were gradually introduced in order to measure their impact on the difference in regional Medicare spending • The reduction in standard deviation was used as a measure of the set of variables’ relative impact

8. Method • Variables (5 analysis categories) • Each category includes the variables from the previous category • 1. No adjustment (no variables) • 2. Illness • 3. Demographics • 4. Insurance Supply • 5. Medical care supply

9. Results • No variables • Standard deviation = $869 • Illness • Standard deviation = $510 • Demographics • Standard deviation = $472 • Insurance Supply • Standard deviation = $436 • Medical care supply • Standard deviation = $390 • Remaining deviation due to the number of patients or the relative expense of care provided for the same illness

10. Policy Implications • Total discharges correlate with spending (.77) greater than average cost per discharge (.46) • Expensive regions hospitalize more often for the same illness than inexpensive regions • 1/3 of Medicare spending comes in the last six months of life • For-profit hospitals and a large percentage of specialists increase costs • HMO’s reduce cost • How can we get a level of care that is necessary but not more; or in other words maximize net social benefit?