1. Geographic Variation in Health Care Presentation for: IOM Panel on Geographic Variation in Healthcare Spending and Promotion of High-Value Care Michael Chernew

2. Practice patterns vary widely for similar patients Source: Wennberg and Gittelsohn, 1973. Science 183(4117): 1102-1108. Surgical Procedure Lowest Two Areas Entire State Highest Two Areas Tonsillectomy13324385151 Appendectomy1015182732 Males Prostatectomy Prostatectomy1113202838 Females Cholecystectomy Cholecystectomy1719274657 Hysterectomy Hysterectomy2022303460 Mastectomy Mastectomy1214182833 Number of Procedures per 10,000 for 13 Vermont hospital service areas, 1969

3. Voluminous literature 4x variation in cesarean delivery (Baicker et al 2006) 1.6x variation in antibiotic fills PMPY, 5 th - 95 th percentile (Steinman 2009) 13.5x variation in odds ratio for type of vascular access for dialysis patients (Hirth et al 1996)

4. Variation in spending as well as in use Source: Fisher et al, 2009

5. Why is this important? Changes beliefs away from notion that physicians are always right –Weakens notion that practice of medicine is purely science Quantifies potential waste in the system –Not sure how to best get rid of ‘waste’ Translating the population based results to the bedside is hard Helps identify ‘efficient’ markets –Is Minneapolis more efficient than Miami?

6. Explaining variation Explanations that generate concern Explanations that we typically accept Explanations with uncertain implications Health Status Health behaviors Patient Preferences Input Prices Physician supply Infrastructure Insurance Output prices Beliefs Greed Culture Income Cost shifting

7. Empirical implications Spending im = X i *  1 + Z im *  2 + M m +  i M m denotes mean spending at the market level after adjusting for personal traits (X) and market traits (Z)  Adding X’s and Z’s will shrink variation in M’s if:  X or Z affects spending AND varies across markets

8. Health status Clearly important at individual level Varies across markets (implying important at market level) Hard to measure Conceptually circular –If more treatment improves health, areas with aggressive practice styles will seem healthier

9. Controversy in measuring health status More aggressive places code more illness, so populations appear ‘sicker’ –Are they really sicker or do they just code more? –If just coding, the health status adjustments ‘over’ adjust. People who move have ‘increases’ in measured illness –Moving to area with 1 quartile higher spending associated with a 5.9% increase in HCC score (Song et al, 2010)

10. Other approaches to health status adjustments Look at specific diseases Examine end of life

11. Variation in price adjusted spending by Medicare beneficiaries. Source, Sutherland et al. 2010, NEJM

12. SES matters 50% of variation in discharges explained by SES, crude health status measures, and physician supply measures –Robust by area definition (county vs health care market) –Robust to methods McLaughlin et al, 1989 Source: McLaughlin et al, 1989

13. Physician Composition and Spending Source: Chernew et al, 2009

14. What do we get for extra spending Source: Baicker and Chandra, Health Affairs (April 2004)

15. Limitations Tendency for Medicare focus –Cost shifting –Erroneous inference about areas –Salience of LTC services and maybe fraud Uncertain policy solutions –Area focus obscures within area provider heterogeneity

16. Commercial vs. Medicare Correlation Level(2006)Growth 1996 - 2006 Hospital and Physician Reimbursements (2006) -.17 (p<0.01) (p<0.01).20(p<.01) Per Capita Inpatient Days (2004) 0.59 (p<.01) (p<.01).13(P<.01) Source: Chernew et al, 2010

17. Concentration and spending Population Hospital Concentration Top third Commercial spending markets, 2006 600,1450.434 Bottom third commercial spending markets, 2006 1,081,2230.312 Top third Medicare spending markets, 2006 1,365,5590.240 Bottom third Medicare spending markets, 2006 603,5800.464 Source: Chernew et al, 2010

18. Provider variation more complex Selection issues more salient –Health status adjustments difficult Attribution issues are complex