The Design of Pay-For-Performance Programs for Reducing Disparities: What do the Data Tell Us?

1. The Design of Pay-For-Performance Programs for Reducing Disparities: What do the Data Tell Us? AcademyHealth Washington, DC June 9, 2008 Joel S. Weissman, Ph.D. MGH/Harvard Health Policy Institute This work was supported by grants from The Commonwealth Fund and RWJF/HCFO

2. Co-Authors/Acknowledgements • Romana Hasnain-Wynia • Lisa Iezzoni • Ray Kang • Mary Beth Landrum • Christine Vogeli • Robin Weinick The authors acknowledge the assistance of the IFQHC and the Centers for Medicare and Medicaid Services (CMS) in providing data which made this research possible. The conclusions prescribed are solely those of the author(s) and do not represent those of  IFQHC or CMS Weissman2008AcadHlth_P4P_disparities.ppt

3. Background • Emergence of Pay-for-performance (P4P) • May improve quality • May decrease costs • Equity is one of the IOM’s six quality goals • Implications for disparities • Only one empirical article out 536 in P4P literature examined both performance incentives and racial disparities (Chien, et al 2007) Weissman2008AcadHlth_P4P_disparities.ppt

4. Methodological Concerns and Potential Unintended Consequences • Minimum case requirements may eliminate many or most hospitals from eligibility for disparities-based measurement and therefore participation in P4P • Penalizing under-resourced hospitals may further disadvantage minorities • Design issues around hospital ranking methods are still in development • “Rising tide lifts all boats” vs “Disparities reduction” Weissman2008AcadHlth_P4P_disparities.ppt

5. Study Questions Q1. How would minimum case restrictions affect the number of hospitals eligible for a p4p program focused on disparities? Q2. Are minority patients disproportionately represented in low performing hospitals? Q2a. What proportion of hospitals provide better quality of care to minority patients than to whites? Q3. Which type of hospital ranking method might have the greatest impact on aggregate national disparities? Weissman2008AcadHlth_P4P_disparities.ppt

6. Methods • Set a 30&30 (minority&white) case threshold for hospital P4P eligibility • Calculate scores for each condition, each race-ethnicity group • Quality Scores (Overall “all-or-none” Composites) • Disparity Scores (White composite – Minority composite) • Calculate • Within-hospital scores (for ranking) • National scores (aggregated individual scores, all hospitals, i.e., without 30/30 threshold restriction) Weissman2008AcadHlth_P4P_disparities.ppt

7. Methods - 2 • Hospital ranked using 2 methods (P4P Design) • “Quality Score” method • “Disparity Score” method • Race-ethnicity distributions determined in high and low performers (+/- 50th percentile) • “Successful” P4P programs were simulated • Make the bottom half look like the top • Re-calculate national disparities scores Weissman2008AcadHlth_P4P_disparities.ppt

8. RESULTS Weissman2008AcadHlth_P4P_disparities.ppt

9. Many Hospitals Do Not Minimum # of Cases for Disparity P4P * -- at least 30 white and 30 minority cases Weissman2008AcadHlth_P4P_disparities.ppt

10. But… Hospitals that Met the 30/30 Threshold Treated Most of the Minority Patients Weissman2008AcadHlth_P4P_disparities.ppt

11. % of Patients Treated in Low Performing* Hospitals – “Quality Score” Ranking Method * Below 50th Percentile Weissman2008AcadHlth_P4P_disparities.ppt

12. % of Patients Treated in Low Performing* Hospitals – “Disparity Score” Ranking Method * Below 50th Percentile Weissman2008AcadHlth_P4P_disparities.ppt

13. Half of hospitals actually provided similar or better quality of care to minority patients Weissman2008AcadHlth_P4P_disparities.ppt

14. National Aggregate Disparity Scores, HQA, 2005 * Includes Ha/PI, AI/AN, Other Weissman2008AcadHlth_P4P_disparities.ppt

15. Reductions in National Disparity Scores Following Performance Improvement in Low Ranking Hospitals: Simulated Effects AMI Patients, 2005 Orig. Disparities 4.4% 3.8% 1.8% 3.9% Hospital Ranking Method: Weissman2008AcadHlth_P4P_disparities.ppt

16. Limitations • Simulations are “optimistic”, and, • Do not address potential for cherry-picking • Other composites may provide different results • Some P4P programs focus on structural characteristics, not quality Weissman2008AcadHlth_P4P_disparities.ppt

17. Conclusions • The number of hospitals that would be excluded for lack of sufficient minority cases is large, yet the number of minority patients excluded would be relatively modest. • P4P can have the unintended consequence of penalizing hospitals that serve a disproportionate share of minorities. However, the effect depends on the method used to rank hospitals. Weissman2008AcadHlth_P4P_disparities.ppt

18. Conclusions - 2 • About half of U.S. hospitals actually provided similar or better quality of care to minority compared with white patients in their own hospitals. • …suggests possibility of eliminating within-hospital disparities in care. • However, because the magnitudes of disparities within any single institution (within the HQA program) are small and because minorities are concentrated at poorer performing facilities, our simulations suggest that improving the worst to the best in terms of within-facility disparities would not reduce national aggregate disparities that much. Weissman2008AcadHlth_P4P_disparities.ppt

19. END OF PRESENTATION Weissman2008AcadHlth_P4P_disparities.ppt

20. % of Patients Treated in Low Performing* Hospitals – All Groups Ranking Method * Below 20th Percentile Weissman2008AcadHlth_P4P_disparities.ppt