Understanding Ethnic Disparities in Advance Care Planning

1. Why are White Nursing Home Residents Twice as Likely as African Americans to Have an Advance Directive? Understanding Ethnic Differences in Advance Care Planning Jennifer L. Troyer Departments of Economics and Health Behavior and Administration University of North Carolina at Charlotte William J. McAuley Departments of Sociology and Gerontology and Communication Center for Social Science Research George Mason University

2. Introduction • Providers, family members, and patients often spend a considerable amount of time weighing treatment options when a patient is seriously ill and nearing the end of life. • Patients may make wishes about treatment decisions known through advance care planning. • Patient Self-Determination Act of 1991

3. Purpose of Study • The rise in the adoption of advance directives has not been equal across ethnic groups. • African American nursing home residents are much less likely to have an advance directive. • Question remains unaddressed by researchers: • Can we explain part of the ethnic gap in advance care planning by considering group differences in the following? • Personal factors • Micro-environmental characteristics of the facility • Social and economic environment represented by the county in which the facility is located

4. Literature • Many studies find ethnic differences in advance care planning when controlling for some resident characteristics. • Demographic characteristics • Health status characteristics • One study (Castle and Mor 1998) looks at how facility characteristics influence advance directive adoption.

5. Literature • Few studies consider geographic variation. • Castle and Mor (1998) – 10 states • Kiely et al. (2001) – 4 states • Levin et al. (1999) – 3 regions • Buchanan et al. (2004) – rural/urban

6. Primary Research Objective • To determine the extent to which ethnic differences in advance care planning are attributable to differences in • the personal characteristics of African American and White nursing home residents, • the facilities in which they reside, • and the counties in which the facilities are located.

7. Data • Medical Expenditure Panel Survey – Nursing Home Component from the Agency for Healthcare Research and Quality • The data include a nationally representative sample of individuals who were nursing home residents as of January 1, 1996. • Include information on facility characteristics • Matched to Area Resource File • 93% White or African American • Use 2,665 (of 3,209) residents in 730 nursing homes

8. Data • Measuring the presence of an advance directive • At least one of four types of advance care plans: • Living will • Do not resuscitate order • Do not hospitalize order • Limits on feeding, medication, other treatments

9. Data: Resident Characteristics • Demographic Characteristics • Age • Long Stay • Education • Gender • Funded by Medicaid? • Living Child? • Health Status • Binary Indicators for Diagnoses, Conditions • Functional Ability

10. Data: Facility and Geographic Characteristics • Facility Characteristics • Ownership Type • Chain Affiliation • Size • Occupancy Rate • % Medicaid Residents • Nursing Staff • Geographic (Market) Characteristics – County • Urban/Rural • Per Capita Income • % High School • % Poverty • % Black • % 65 or older

11. Data: Group Differences in Mean Characteristics • 63.4% of White residents have advance directive vs. 27% of African-American residents • Resident Characteristics • Differences in education – whites more likely to have high school diploma • Differences in presence of living child – whites more likely to have a living child • Facility Characteristics • African-American residents more likely to be in a for-profit facility • African-American residents in facilities with higher proportion of Medicaid-funded residents • County Characteristics • African-American residents in counties with lower rates of high school completion

12. Methods • Probit Estimates: Full Sample • The effect of ethnicity on the probability of having an advance directive is estimated, controlling for resident, facility, and county characteristics. • Probability of Having an Advance Directive = f ( ethnicity, resident characteristics, facility characteristics, county characteristics) • Gives us the effect of ethnicity on the probability of advance care planning, when controlling for other factors.

13. Methods • Probit Estimates Using Sub-Samples: African American and White • Estimates are done using two samples: • African American residents • White residents • Probability of Having an Advance Directive = f (resident characteristics, facility characteristics, county characteristics) • Estimates show whether characteristics have the same impact on the likelihood of having an advance care plan for the two groups.

14. Methods • Using Probit Estimates from Sub-Samples: African American and White • Estimates may be used (with sub-sample means) to determine how much of the difference in the probability of having an advance directive between the two ethnic groups may be attributable to differences in average group characteristics. • Probability Gap Between the Two Groups = (Portion Explained by Differences in Group Characteristics) + (Portion Unexplained by Group Differences) • Portion Explained by Differences in Group Characteristics can be broken down further to look at: • How much resident, facility, and market characteristics help to explain the probability gap. • How much each measured characteristic helps to explain the probability gap.

15. Methods • Estimated with whole sample and two sub-samples • Using the estimates of  for the African American sample ( ) and White ( ) sample, the vectors of African American (XiB) and White (XiW) characteristics, and the size of the African American (nB) and White (nW) samples, the predicted probability of having and advance directive may be computed for each of the two samples, S=B and S=W:

16. Methods • Then, the predicted difference in the probability of advance directive adoptions between the two groups is:

17. Methods • Using a weighted average of the estimated coefficients for African American and White residents, *, the degree to which is explained by differences in the measured characteristics of African American and White residents is:

18. Methods • Marginal effects presented in tables. • For continuous variables in Xi, such as per capita income in the county, the marginal change in the kth continuous variable, Xk, on the probability of having an advance directive • For binary variables in Xi, the effect of switching the kth binary variable from 0 to 1 is

19. Results • Full Sample: • When controlling for resident, facility, and market characteristics, African American residents are 23% less likely to have an advance care plan. • Sub-Sample Estimates: • For both groups: • Alzheimer’s  more likely to have advance directive • High poverty and more 65+  more likely to have advance directive • Differences: • Long stay (2+ years) increases the probability of having an advance directive for African American residents but not white residents • Urban location and more poverty  less likely to have advance directive for African Americans, but no effect for white residents

20. Results

21. Results • Important Resident Characteristics • High-school diploma, presence of living child, age 85+ • Important Facility Characteristics • Higher proportion of Medicaid-funded residents • Important County Characteristics • Higher proportion of individuals in poverty and metropolitan area

22. Conclusions • Consistent with prior research, we find a significant and large difference in the probability of advance care planning for white vs. African American residents. • Contribution of our paper: • Nationally representative sample • Consider three levels of explanatory variables • Determine the relative impact of variables on the African American-White difference in advance care planning • Nearly half of the ethnic gap in advance care planning is attributable to differences in group characteristics. • Facility and market characteristics do play an important role.

23. Conclusions • Suggestions for Future Research and Limitations • Location-specific Measures • Facility-specific Measures • More resident Health Status controls • More information on religious values, attitudes, expectations of residents