QualityNet Conference September 21, 2006

1. Beth Hartman Ellis, PhD MaryAnne D. Hope, MS Health Services Advisory Group Phoenix, AZ QualityNet ConferenceSeptember 21, 2006

2. Medicare Health Outcomes SurveyBackground The Medicare Health Outcomes Survey (HOS) Assesses each Medicare Advantage (MA) health plan�s ability to maintain or improve the physical and mental health functioning of its Medicare beneficiaries over a two-year period Is sponsored by CMS Launched in 1998 First Medicare managed care outcomes measure More than 1.8 million Medicare beneficiaries surveyed to date

3. Medicare Health Outcomes SurveyMethodology MA members are surveyed at baseline, and respondents are resurveyed two years later A cohort comprises respondents from one baseline and associated follow up Baseline cohort of 1,000 beneficiaries randomly sampled from each participating plan In plans with less than 1,000, all MA beneficiaries are sampled Survey mailed to baseline sample Telephone follow up of non-respondents

4. Medicare Health Outcomes SurveyPopulation Beneficiaries included in the HOS Community dwelling Nursing home Institution Disabled under 65 End stage renal disease patients excluded

5. Survey Content

6. Research Goal for Current Study To examine physical health status after a two-year interval for living and deceased Medicare managed care beneficiaries

7. Analytic Sample for Current Study Medicare HOS 2002 � 2004 Cohort 5 Baseline and Follow Up data 60,317 beneficiaries 65 and over, physical component summary (PCS) score at Baseline 6,993 of these beneficiaries were deceased at follow up and included in the analyses

8. Excluded Groups at Follow Up Excluded Groups at follow up 1. Invalid survey at follow up (n=781) Beneficiaries not enrolled in the plan, bad address and non-working/unlisted phone number 2. Voluntarily disenrolled at follow up (n=18,603) Beneficiaries who left their plan between baseline and follow up 3. Involuntarily disenrolled at follow up (n=8,111) Beneficiaries whose plans were no longer available at follow up 4. Non-respondents at follow up (n=12,733) Beneficiaries who did not respond to the survey at follow up

9. Analytic Strategy for Current Study We employed the methodology by Diehr and colleagues (2001) for including the deceased in health outcomes research Healthy at follow up defined as a response of excellent, very good, or good to the question, �In general, would you say your health is�..�

10. Analytic Strategy for Current Study, cont�d Logistic regression used to obtain the probability of being healthy at follow up, estimated from the baseline PCS score Deceased assigned a value of zero Clustering among health plans assessed with the intraclass correlation coefficient - found to be 0.02, suggesting clustering (Cohen et al., 2003) Solution: multilevel model SAS PROC MIXED

11. Analytic Strategy for CurrentStudy, cont�d Race - White Income of $50,000 and over College graduate Male Married Not a Medicaid recipient Self-respondent Non-smoker No chronic conditions Negative response to 3 depression screening questions

12. Analytic Strategy for Current Study, cont�d Two multilevel models constructed Demographics only Demographics and health risks Smoker Positive depression screen Sum of an individual�s chronic conditions

13. Specific Predictors Demographics Race � African American, Hispanic, Asian/Pacific Islander, American Indian/Alaskan Native, Other Race Household Income Less than $10,000 $10,000 to $19,999 $20,000 - $29,999 $30,000 - $49,999 Missing income

14. Specific Predictors, cont�d Demographics, continued Educational level 8th grade or less Some high school High school graduate/GED Some college/2 year degree Gender Female Age Proxy respondent

15. Specific Predictors, cont�d Demographics, continued Marital Status Divorced/separated Widowed Never married Medicaid Status Dually eligible (Medicaid & Medicare) Smoking Status Smoker (every day/some days/smoked 100 cigarettes in your life)

16. Specific Predictors, cont�d Positive depression screen Positive response to any of the 3 depression screening questions in the HOS Comorbidities Individual�s sum of 9 chronic conditions

17. Demographics Model

18. Demographics and Health Risks Model

19. Excluded Groups Comparison at Baseline Effect sizes for proportions (Cohen, 1988) and Hedge�s g for means (Rosenthal & Rosnow, 1991) used to assess significance of findings

20. Excluded Groups Comparison at Baseline, cont�d The invalid survey group had significantly More Hispanics** Less Whites ** More with 8th grade education or less * More with less than $10,000 household income* * Small effect size > 0.20 = < 0.50 ** Medium effect size > 0.50 - < 0.80 *** Large effect size > 0.80

21. Excluded Groups Comparison at Baseline, cont�d The invalid survey group had significantly Less homeowners ** More dually eligible * More who had a positive depression screen * Older * Lower PCS and MCS scores * More impaired ADLs * * Small effect size > 0.20 = < 0.50 ** Medium effect size > 0.50 - < 0.80 *** Large effect size > 0.80

22. Conclusions Probability of not being healthy at follow up related to: Low socioeconomic status Low educational level Female Proxy respondent Medicaid recipient (dually eligible) Positive depression screen Chronic conditions Advanced age

23. Conclusions, cont�d Demographics and health risks model Better overall fit compared to the demographics only model Socioeconomic disparities exist in Medicare managed care for enrollees in this sample

24. Conclusions, cont�d Medicare managed care plans and QIOs should consider targeting beneficiaries with low income and low educational levels, depression, and comorbidities for disease management programs

25. Medicare HOS Webinars �Getting the Most out of Your Medicare HOS Reports� held September 14, 2006 Upcoming Webinars �A Guide for Researchers� October 18, 2006 �Mining Your HOS Data: A Toolkit� November 14, 2006 Check the HOS Website for information about specific dates

26. Contact Information Beth Hartman Ellis, PhD Bellis@azqio.sdps.org 602.665.6133 MaryAnne D. Hope, MS Mhope@azqio.sdps.org 602.745.6211 HOS Web Site: www.hosonline.org HOS Technical Support: Medicare HOS Information and Technical Support Telephone Line: 1-888-880-0077 E-Mail: hos@azqio.sdps.org

27. References Agency for Healthcare Research and Quality (2005). National Healthcare Disparities Report. Available at: www.ahrq.gov/qual/nhdr05/nhdr05htm. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed). Hillsdale, NJ: Lawrence Erlbaum Associates. Cohen, J., Cohen, P., West, S.G., & Aiken, L.S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed). Mahwah, NJ: Lawrence Erlbaum Associates. Diehr, P., Patrick, D.L., Spertus, J., et al. (2001). Transforming self-rated health and the SF-36 scales to include death and improve interpretability. Medical Care 39 (7): 670-680. Menard, S. (1995). Applied logistic regression analysis. Sage Series: Quantitative Applications in the Social Sciences. Thousand Oaks, CA: Sage Publications. Rosenthal, R. & Rosnow, R. L. (1991). Essentials of behavioral research methods and data analysis (2nd ed). Columbus, OH: McGraw-Hill. Singer, J. (1998). Using SAS PROC MIXED to fit multilevel models, hierarchial models, and individual growth models. Journal of Educational and Behavioral Statistics, 24(4), 323-355.