The Medicaid Differential Project and Preliminary Results

1. Ron Prevost U.S. Census Bureau NAWRS 46th Annual Workshop August 22, 2006 The Medicaid Differential Project andPreliminary Results

2. Overview • Phase I & II Study Results – Continuation of Dave Baugh’s Presentation • Medicaid Study Elements - Phases III & IV • The Census Bureau’s Administrative Records Infrastructure • New and Emerging Applications of Administrative Records

3. Project Collaborators and Co-Authors • Collaborators: • US Census Bureau Collaborators: • Sally Obenski • Ron Prevost • Dean Michael Resnick • Marc Roemer • Office of the Assistant Secretary for Planning and Evaluation: • Rob Stewart • George Greenberg • Kate Bloniarz • Coauthors: • Centers for Medicare and Medicaid Services • Dave Baugh • Gary Ciborowski • State Health Access Data Assistance Center • Kathleen Thiede Call • Gestur Davidson • Lynn Blewett • Srand Corporation • Jacob Klerman

4. Preliminary explanations we are reporting on today • Universe differences: • Enforce CPS group quarter definitions on MSIS where we have administrative data address information • Look for duplicate persons in different states or same state • Measurement error: • Link CPS respondents to MSIS data for CY 2000 to examine survey reports of enrollees • Understand the covariates of misreporting

5. Building a common universe Not a valid record Group quarters, dead, not a valid record, in two states In CPS universe and in MSIS universe

6. Preparing MSIS data for comparison and linking to CPS • Removed MSIS dual eligible cases defined as a “group quarter” by Census • Ran the 2000 MSIS data through Census Bureau’s Person-ID validation system • A record is “valid” if in the appropriate format and demographic data is consistent • Removed duplicate valid records • Removed those MSIS enrollees not enrolled in “full benefits”

7. Matching the CPS universe • Number of MSIS Medicaid Records in 2000: • 44.3 M (total MSIS records) • - 1.5 M (records in more than one state or group quarter) • - 4.0 M (partial Medicaid benefits) • 38.8 M (the target Medicaid total)

8. Sample loss in the 2000 MSIS and 2001 CPS linking • MSIS: 9% of all MSIS records did not have a valid record and were not eligible to be linked to the CPS • CPS: 6.1% (respondents’ records not validated) • + 21.5% (respondents refused to have their ______ data linked) 27.6% (total not eligible to be linked to MSIS)

9. The matched CPS-MSIS respondents with reported data only • 12,341 CPS person records matched into the MSIS • 1,906 records had imputed or edited CPS data (15.5% of total). • Focusing on only those with explicitly reported data: 60% (responded they had Medicaid) • 9% (responded some other type of public coverage but not Medicaid) 17% (responded some type of private coverage, but not Medicaid) 15% (responded they were uninsured) 101% (over 100% due to rounding)

10. What factors are associated with measurement accuracy/error? • Length of time enrolled in Medicaid • Recency of enrollment in Medicaid • Poverty status impacts Medicaid reporting but does not impact the percent reporting they are uninsured • Adults 18-44 are less likely to report Medicaid enrollment • Adults 18-44 more likely to report being uninsured • Overall CPS rate of those with Medicaid reporting that they are uninsured is higher than other studies • Overall CPS rate of those with Medicaid reporting Medicaid is lower than other studies

11. Explanations of the undercount revisited: work remaining to be done • Phase III: Measure Universe Differences: • Use 7 Medicaid state files with name and address information to understand the impact of MSIS non-validation (one of the states is CA) • Use enhanced MSIS data to further analyze the CPS sample frame coverage • Phase IV: Assess Measurement Error: • Compare measurement error in the CPS to the National Health Interview Survey (NHIS) by linking the NHIS to the MSIS • Compare measurement error in CPS to state survey experiments

12. Continued • Administrative and survey data processing, editing and imputation • Evaluate how well the CPS edits and imputations work at both the micro level and the overall macro level • Evaluate additional state-level Medicaid data • Survey sample coverage error and survey nonresponse bias • Link the address data from the 7 states to the Census Bureau’s Master Address File to determine sample coverage problems • Assess whether those addresses with a Medicaid enrollee are more likely to not participate in Census Bureau surveys

13. Study Conclusions • We have presented preliminary results that are subject to change after further investigation • At the moment we conclude that survey measurement error is playing the most significant role in producing the undercount • Some Medicaid enrollees answer that they have other types of coverage and some answer that they are uninsured • The overall goal of the project is to improve the CPS for supporting health policy analysis • Especially refining estimates of the uninsured

14. The Census Bureau’s Mandate for Administrative Records Use • Title 13, Section 6: • Use administrative records information as extensively as possible in lieu of conducting direct inquires • Census Bureau Strategic Plan: • Reduce reporting burden and minimize cost to taxpayer by acquiring and developing high-quality data from sources maintained by other government and commercial entities

15. Consistent Application of Policies To ensure that projects have the appropriate legal authorization, comply with existing data agreements, and provide adequate controls to protect confidentiality and privacy Administrative Controls Numerous levels of approval Need-to-know access Removal of identifiable information Administrative Records Tracking System Security and confidentiality training Safeguarding Administrative Records at the Census Bureau

16. Census Bureau Programs that Use Administrative Records • Economic Directorate’s Business Register • Intercensal Estimates • Master Address File • Small Area Income and Poverty Estimates • Longitudinal Employer-Household Dynamics • National Longitudinal Mortality Study • Current and Periodic Demographic Surveys

17. The Census Bureau’s Administrative Records Program Evolution Infrastructure investments allow new interagency collaborations Projects included AREX 2000 and the 1999 StARS prototype Survey launched to gather info on potential AR files Race Model Addresses Quality Concerns Program begins AR Research staff created 1996 July 1993 1999/2000 2002 2005 Early 1990s 1999 2001 2004 mid 1990s July 1993 Today AR Test for 2000 Census Data Stewardship program begins Statistical uses of AR conference held PVS Increases Linking Capacity Centralized program emerges

18. The Census Bureau’s Administrative Records Infrastructure • STARS National Files including: • IRS personal tax returns, salary reports, and information returns • Medicare & Medicaid • Indian Health Service • HUD files (TRACS, MTCS, PIH, and CHUMS) • Selective Service • Supplemental Security Income • Unemployment Insurance Wage Files (selected states) • MAF – National Change Of Address File • Social Security Numident File • Creation of the Census Numident file • Look-up file that provides demographic data

19. Current and Emerging Census Bureau Demographic Applications (1) • Tested for assigning missing characteristics to census records • Used to assist coverage improvement operations target areas requiring follow-up • Enhanced the decennial Group Quarters frame with commercial and state address lists • Reducing ACS small area variance with model-assisted estimation based on AR

20. Current and Emerging Census Bureau Demographic Applications (2) • Using integrated data sets to better understand the differences between survey and administrative data • Improve survey instrument design, editing, imputation, and weighting • Provide statistics to improve an agency’s approach to measure program effectiveness • Provide measures to improve agency micro-simulation models • Identify areas for agency-targeted program outreach

21. Current and Emerging Census Bureau Demographic Applications (3) • Reacting to disaster and other near-real time requirements • Katrina’s effect on the federal statistical system and our lack of current response data highlighted need • Acquired the USPS National Change of Address File and FEMA’s emergency management and flood insurance files • Developing next generation StARS – near real-time measurements

22. Conclusions • Integrated data architectures are the future of American statistics • As the demand for data increases and budgets decrease data re-use many be the only cost-effective option • Technical and policy related challenges must be addressed • This approach will support evidence-based public policy research and decisions.

23. Contact Information • Ronald C. Prevost • U.S. Census Bureau • Washington D.C. 20233-8100 • Email: Ronald.C.Prevost@Census.Gov • Phone: (301) 763-2264 • Cell: (202) 641-2246