# Presentation: 950463

## Ron Prevost
U.S. Census Bureau
NAWRS 46th Annual Workshop
August 22, 2006

**U.S. Census Bureau**
**NAWRS 46****th**** Annual Workshop**
**August 22, 2006**

**The Medicaid Differential Project and****Preliminary Results**

## 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

## 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

## 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

## Building a common universe

- Group quarters, dead, not a valid record, in two states

- Not a valid record

- In CPS universe and in MSIS universe

## 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”

## 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)

## 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)

## 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)

## 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

## 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

## 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

## 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

## 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

## Safeguarding Administrative Records at the Census Bureau

**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

## 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

## The Census Bureau’s Administrative Records Program Evolution 

**Today**

**Program begins**

**mid 1990s**

**July 1993**

**1996**

**AR Research staff created**

**Survey launched to gather info on potential AR files**

**Early 1990s**

**Statistical uses of AR conference held**

**July 1993**

**1999/2000**

**Projects included AREX 2000 and the 1999 StARS prototype**

**1999**

**Centralized  program emerges**

**Data Stewardship program begins**

**2001**

**AR Test for 2000 Census**

**Race Model Addresses Quality Concerns**

**PVS Increases Linking Capacity**

**Infrastructure investments allow new interagency collaborations**

**2004**

**2002**

**2005**

## 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

## 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

## 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

## 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

## 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.

## Contact Information

- Ronald C. Prevost
- U.S. Census Bureau
- Washington D.C. 20233-8100
- Email: _[Ronald.C.](mailto:Ronald.C.Prevost@Census.Gov)__[Prevost](mailto:Ronald.C.Prevost@Census.Gov)__[@Census.Gov](mailto:Ronald.C.Prevost@Census.Gov)_
- Phone: (301) 763-2264
- Cell:     (202) 641-2246