Practical Applications of Indirect Estimates of Race/Ethnicity & Lessons Learned Briefing to the Institute of Medicine Newport Beach, California

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1 Practical Applications of Indirect Estimates of Race/Ethnicity & Lessons Learned Briefing to the Institute of Medicine Newport Beach, California Allen Fremont, Marc Elliott, Nicole Lurie March 12, 2009

2 Work with plans illustrates how R/E data and GIS tools can help target disparities in quality Data and IT tools enabling stakeholders to: See the problem more clearly Learn ways to target interventions more effectively Recognize possibilities for shared action 2

3 Where most plans get stuck Monitoring & Dissemination Developing & Targeting Interventions Identifying Disparities Linking to Quality Measures Obtaining Race/Ethnicity Data 3

4 Indirect R/E measures can be used to assess disparities at plan or market level 4

5 Newer Indirect R/E estimates are also accurate enough to assess disparities at provider group level 5

6 Indirect R/E estimates provide QI decision makers with clearer picture of populations served Region A NORTHERN MRA 11% Region B WESTERN MRA 2% American Indian / Alaskan Native 28% 12% 31% 13% Asian / Pacific Islander Black 49% 53% White Region C SOUTHERN MRA Region D GREATER BOSTON MRA Hispanic 11% 2% 12% 24% 9% 36% 74% 31% 6

7 Indirect R/E estimates provide QI decision makers with clearer picture of populations served Distribution of Black Members Across Service Areas % BOSTON-PRIMARY SPRINGFIELD BROCKTON NEW BEDFORD QUINCY FALL RIVER PITTSFIELD WESTFIELD TAUNTON REVERE HOLYOKE SOMERVILLE NORTHAMPTON BARNSTABLE ATTLEBORO GREENFIELD MALDEN ADAMS FALMOUTH FRAMINGHAM PLYMOUTH WORCESTER ORLEANS LYNN WAREHAM WALTHAM LAWRENCE LOWELL SOUTHBRIDGE GARDNER-FITCHBURG WOBURN SALEM HAVERHILL ATHOL NANTUCKET OAK BLUFFS BEVERLY GLOUCESTER Members % Black Members 80% 60% 40% 20% Service Area 0% 7

8 Where are the African American members with uncontrolled Diabetes? Diabetics with HbA1c > 7 (Black) Number of Members % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Cumulative % Service Area 8

9 These diabetic members are concentrated in racially segregated neighborhoods 9

10 Not all members of a given racial/ethnic group at equal risk for poor care or outcomes Areas with large number of Hispanic plan members Clusters of members with low rates of indicated care 10

11 Identifying low quality areas & then assessing role of R/E & other factors can be instructive 11

12 Low performance hotspots may differ in important ways besides major race/ethnicity groups 12

13 Region 4 Provider Group Performance: LDL Test B C Regional Average A 13

14 Knowing that a given provider group s service area overlaps with hotspot can be instructive Ellipses show where 95% of group s diabetic members live 14

15 The same provider group may perform very differently in some areas and populations Provider A serves members in and around a hotspot of low performance Providers A s performance inside hot spot worse than outside 15

16 Or helping identify potential best practices for effectively caring for vulnerable populations Providers A s performance inside hot spot much worse than outside Though Provider B serves similar patients as A, B s performance good inside and outside hot spot Provider A could learn from practices by B 16

17 Mapping sociodemographic characteristics of communities in hotspot can increase understanding Limited English Proficiency Inside Cluster: 43 % Outside Cluster: 29 % which can help facilitate more effective community partnerships 17

18 Individual plans may find targeting hotspots alone relatively ineffective unless dominate market 11% 89% % Diabetics not covered % Diabetics covered by Plan A 18

19 The cost-effectiveness of community interventions may improve when plans pool efforts 24% 13% 53% 10% % Diabetics not covered % Diabetics covered by Plan A % Diabetics covered by Plan B % Diabetics covered by Plan C 19

20 Update on dissemination of newer approaches to indirect estimates of R/E Racial/Ethnic Health Equity Initiative (RAND-Brookings) Pilots in California, Colorado, Massachusetts Likely adoption by state of MA Wellpoint,* Kaiser, Cigna, Highmark, BMC, etc using routinely California IHA & Right Care Initiative Use by all major plans in California Assessing impact of P4P on disparities Hotspots mapping to support shared action among stakeholders at community level * WellPoint using their own modified algorithm, rather than RAND s 20

21 Allen Fremont, MD, PHD , x