Using Microsimulation Modeling to Identify Linguistic Outreach and Enrollment Needs

1. Daphna Gans, Ph.D.UCLA Center for Health Policy ResearchMarch 14th, 2013 Eighth National Conference on Quality Health Care for Culturally Diverse Populations (March 11-14, 2013) Oakland Marriott City Center, Oakland, CA Using Microsimulation Modeling to Identify Linguistic Outreach and Enrollment Needs

2. Acknowledgment Support for this analysis was provided by: The California Pan-Ethnic Health Network Policy Brief: Gans D, Kinane CM, Watson G, Roby DH, Graham-Squire D, Needleman J, Jacobs K, Kominski GF, Dexter D., and Wu E. Achieving Equity by Building a Bridge from Eligible to Enrolled. Los Angeles, CA: UCLA Center for Health Policy Research and California Pan-Ethnic Health Network, 2012 http://www.healthpolicy.ucla.edu/pubs/files/enrolledpbfeb2012.pdf Please note: Results may vary slightly when using newer version of the CalSIM model.

3. Goals of this Project • Predict English proficiency and preferred language among projected eligible Californians and enrollees in various insurance markets under the ACA • Focus on those eligible for subsidized coverage through the California Health Benefit Exchange (the subsidized Exchange) • Compare take-up rates with or without the Limited English Proficient (LEP) effect • Provide recommendations for policymakers to maximize enrollment of LEP individuals

4. Overview Part I – The Need to Account for Limited English Proficiency Part II – Limited English Proficiency Modeling Part III – Limited English Proficiency Analyses Using California Simulation of Insurance Markets (CalSIM) 1.8 Part IV – Recommendations

5. Overview Part I – The Need to Account for Limited English Proficiency Part II – Limited English Proficiency Modeling Part III – Limited English Proficiency Analyses Using California Simulation of Insurance Markets (CalSIM) 1.8 Part IV – Recommendations

6. Rationale for including English Language Proficiency • People of color represent roughly 60% of California’s population • Nearly 7 million Californians are considered Limited English Proficient (LEP) • LEP individuals are less informed of the ACA’s benefits • Language barriers currently likely impacting participation in public programs

7. English Language Proficiency • “Individuals who do not speak English as their primary language and who have a limited ability to read, write, speak, or understand English may be limited English proficient, or ‘LEP,’ and may be eligible to receive language assistance with respect to a particular type of service, benefit, or encounter.” TheOffice of Civil Rights • Individuals who report speaking English “less than very well” Agency for Healthcare Research and Quality (AHRQ) ; Shin & Kominski 2000

8. Overview Part I – The Need to Account for Limited English Proficiency Part II – Limited English Proficiency Modeling Part III – Limited English Proficiency Analyses Using California Simulation of Insurance Markets (CalSIM) 1.8 Part IV – Recommendations

9. Limited English Proficiency (LEP) Predictive Modeling • The core data set for CalSIM – Medical Expenditure Panel Survey, Household Component (MEPS-HC) – does not contain data on English proficiency, but contains reported comfort level with speaking English • Individuals reporting that they were uncomfortable speaking English in MEPS were classified as LEP • To determine LEP for the remainder of respondents who speak a language other than English at home (1%) the CalSIM model uses a probabilistic model fit to the 2009 California Health Interview Survey (CHIS)

10. LEP Predictive Modeling Using CHIS 2009 Confidential Data • Logistic regression • Dependent variable: Binary LEP status • Predictors: language spoken at home, survey interview language, race/ethnicity, level of education, and age at which the individual moved to the United States (if not U.S. born) • Controls for gender, income, employment status, employer firm size, ability to understand primary care provider, and immigration status • Model statistics indicate goodness of fit

11. Integrating LEP Status into CalSIM Model • Each adult is randomly assigned LEP status with predicted probability estimated from model parameters • Include an adjustment to the predicted probabilities of individual insurance coverage take up for LEP individuals based on empirical analysis from Alegriaet al. (2006) • Reflects the degree of difference between insurance take-up and remaining uninsured among Latino and Asian populations attributed to LEP • Marginal distributions of LEP from CHIS are included in CalSIM weighting process to control for larger LEP distribution in California

12. Overview Part I – The Need to Account for Limited English Proficiency Part II – Limited English Proficiency Modeling Part III – Limited English Proficiency Analyses Using California Simulation of Insurance Markets (CalSIM) 1.8 Part IV – Recommendations

13. Eligibility for Medi-Cal (5.3 Million) and the Subsidized Exchange (2.7 Million), by Race/Ethnicity, 2013 66% Minority 75% Minority 52% 2.10 mil 47% 1.34 mil

14. Eligibility for Medi-Cal (5.3 Million) and the Subsidized Exchange (2.7 Million) , by Language Proficiency, 2013

15. Predicted Percentage of LEP Adults among Predicted Coverage Status Populations, 2019

16. Language Other than English Spoken at Home among LEP Non Elderly Adults Enrollees, Medi-Cal (1.5 Million) and the Subsidized Exchange (500,000), 2019

17. Comparing Take-up Rates with and without LEP effects • CalSIM without modeling LEP accounts for the base scenario assumptions • Individual enrollment decision is based on income, cost, chronic conditions • Assumes LEP is not a hindering factor to enrollment; or • Represents ideal conditions where all individuals regardless of English mastery can enroll • CalSIM with LEP modeling models accounts for the marginal effect of LEP on take-up holding other factors constant

18. Eligible and Enrolled LEP Adult Population in the Subsidized Exchange, with and without Integrating LEP into CalSIM, 2019

19. Enrollment Rate for the LEP Population: Potential Gap Between Eligible and Enrolled • Under ideal conditions, 56% of the eligible LEP individuals are expected to enroll • If Limited English Proficiency is a factor in enrollment behavior, only 46%of the eligible LEP individuals are expected to enroll • A potential gap affecting about 119,000 individuals

20. Overview Part I – The Need to Account for Limited English Proficiency Part II – Limited English Proficiency Modeling Part III – Limited English Proficiency Analyses Using California Simulation of Insurance Markets (CalSIM) 1.8 Part IV – Recommendations

21. Bridging the Gap from Eligible to Enrolled • Planning for the Medicaid Expansion and Exchange is very important • The Exchange is invested in properly planning for the population expected to enroll • Providers, counties and communities all need to get involved in planning • Proactive action is needed so we can to take advantage of federal Medicaid and Exchange subsidy dollars • Currently only 61% of individuals eligible actually enroll in Medicaid, and many of them do it due to a health episode

22. Bridging the Gap from Eligible to Enrolled • Proactive measures: • Auto-enrollment • Facilitate safe and confidential transition from the multiple current public programs to Medi-Cal or the Exchange • Improve capacity of physicians and other clinicians to deal with this new demand for services • Use CalSIM predicted number of eligible and projected enrolled LEP individuals and languages spoken at home as guidance in planning outreach and other materials • Cultural and linguistic differences should be included in planning • Target assistance resources to consumers with the highest needs • Invest in culturally and linguistically appropriate marketing and outreach • Involve communities of color in decision-making processes

23. Daphna Gans, Ph.D.UCLA Center for Health Policy ResearchContact information:dgans@ucla.edu(310) 794-6196 Using Microsimulation Modeling to Identify Linguistic Outreach and Enrollment Needs.