1. Integrated Health Care Survey Designs: Analytical Enhancements Achieved Through Linkage of Surveys and Administrative Data 2008 European Conference on Quality in Official Statistics (Q2008) 2008 European Conference on Quality in Official Statistics (Q2008) Steven B. Cohen, Ph.D.

2. Purpose of Discussion Integrated survey design features Integrated survey design features Related enhancements to data quality and analytical capacity Related enhancements to data quality and analytical capacity Capacity to reduce bias attributable to survey nonresponse Capacity to reduce bias attributable to survey nonresponse Applications to AHRQ Data Portfolio and Research Initiatives to inform health outcomes Applications to AHRQ Data Portfolio and Research Initiatives to inform health outcomes Limitations Limitations Future model for consideration Future model for consideration

3. Advancing Excellence in Health Care Health Outcomes Focus Part of AHRQ’s Mission AHRQ Mission: To improve the quality, safety, efficiency, and effectiveness of health care for all Americans

4. Advancing Excellence in Health Care Integrated survey design features Direct linkage between sample members in core survey with larger host survey; administrative records; or follow-up surveys Direct linkage between sample members in core survey with larger host survey; administrative records; or follow-up surveys Use of secondary data (e.g. aggregate data at the county/state level) as core component of survey Use of secondary data (e.g. aggregate data at the county/state level) as core component of survey Prior survey record of call data informs data collection strategies Prior survey record of call data informs data collection strategies Informs sample design, nonresponse and poststratification adjustments, imputation and data supplement for item nonresponse Informs sample design, nonresponse and poststratification adjustments, imputation and data supplement for item nonresponse Need for greater attention to ensuring confidentiality: limitations in public use data Need for greater attention to ensuring confidentiality: limitations in public use data

5. Advancing Excellence in Health Care Capacity to reduce bias attributable to survey nonresponse Adjustments for unit nonresponse Detailed information available on demographic/socio- economic characteristics of both respondents/and nonrespondents from sample frame of host survey administrative records Detailed information available on demographic/socio- economic characteristics of both respondents/and nonrespondents from sample frame of host survey administrative records Incorporation of secondary data Incorporation of secondary data Adjustments for item nonresponse Data replacement Data replacement Cold deck imputation Cold deck imputation

6. Agency for Healthcare Research and Quality Advancing Excellence in Health Care www.ahrq.gov

7. Advancing Excellence in Health Care Medical Expenditure Panel Survey (MEPS) Annual Survey of 15,000 households: provides national estimates of health care use, expenditures, insurance coverage, sources of payment, access to care and health care quality Permits studies of: Distribution of expenditures and sources of payment Distribution of expenditures and sources of payment Role of demographics, family structure, insurance Role of demographics, family structure, insurance Measurement of expenditures in managed care Measurement of expenditures in managed care Expenditures for specific conditions Expenditures for specific conditions Trends over time Trends over time

8. Advancing Excellence in Health Care Design Specifications Target Precision Specifications for national and regional estimates; policy relevant subgroups Target Precision Specifications for national and regional estimates; policy relevant subgroups Overall Design effect of 1.6 Overall Design effect of 1.6 200 PSU design (Max) 200 PSU design (Max) Overall/round specific survey response rate requirements Overall/round specific survey response rate requirements Linkage to NHIS Linkage to NHIS Multistage design Multistage design Disproportional sampling Disproportional sampling Longitudinal design Longitudinal design Minimize survey cost for fixed precision Minimize survey cost for fixed precision

9. Advancing Excellence in Health Care Key Features of MEPS-HC Survey of U.S. civilian noninstitutionalized population Survey of U.S. civilian noninstitutionalized population Sub-sample of respondents to the National Health Interview Survey (NHIS) Sub-sample of respondents to the National Health Interview Survey (NHIS) Oversample of minorities and other target groups Oversample of minorities and other target groups Panel Survey – new panel introduced each year Panel Survey – new panel introduced each year – Continuous data collection over 2 ½ year period – 5 in-person interviews (CAPI) – Data from 1st year of new panel combined with data from 2nd year of previous panel

10. MEPS Overlapping Panels (Panels 8 and 9) MEPS Household Component MEPS Panel 8 2003-2004 Round 2Round 3Round 4Round 5 Round 1Round 2Round 3 MEPS Panel 9 2004-2005 1/1/20031/1/2004 Round 1 NHIS2002 NHIS2003 Round 4Round 5

11. Advancing Excellence in Health Care MEPS Household Component Sample Design Oversampling of policy relevant domains 1996 Minorities (Blacks & Hispanics) 1997 Minorities Low income Children with activity limitations Children with activity limitations Adults with functional limitations Adults with functional limitations Predicted high expenditure cases Predicted high expenditure cases Elderly Elderly 1998-2001 Minorities 2002+Minorities, Asians, Low Income

12. Advancing Excellence in Health Care MEPS Components Household Component (HC) - 15, 000 households, Household Component (HC) - 15, 000 households, 37, 000 individuals Medical Provider Component (MPC) - designed to supplement /replace household reported expenditure data Medical Provider Component (MPC) - designed to supplement /replace household reported expenditure data Insurance Component (IC) - 30,000 establishments; elicits insurance availability, premium contribution, and benefit provision information; can be used to generate estimates at the state level Insurance Component (IC) - 30,000 establishments; elicits insurance availability, premium contribution, and benefit provision information; can be used to generate estimates at the state level IC sample linked to HC designed to supplement or replace household reported health coverage data

13. Advancing Excellence in Health Care MEPS - Integrated Survey Design Features National Health Interview Survey serves as sample frame for Household Component National Health Interview Survey serves as sample frame for Household Component Census Bureau Business Register serves as Insurance Component sample frame Census Bureau Business Register serves as Insurance Component sample frame Secondary data on health care measures supplement surveys Linked survey of medical providers Secondary data on health care measures supplement surveys Linked survey of medical providers Linked survey of employers Linked survey of employers Distinct data sources linked for longitudinal analyses Distinct data sources linked for longitudinal analyses

14. Advancing Excellence in Health Care Demographics (ref. person) [9] Household Characteristics [5] Socio-Economic Status [6]Geographic[4]Health[5] Age DU size Poverty status Census region Health status Race/ethnicity Refused phone # Refused phone #Education MSA size Need help - personal care Marital status Income MSA/central city Not working - health reasons Gender Type of PSU Employment status Urban/rural Any Asian in HH Any Black in HH Interview language Type of home (house, apt., etc.) Family medical expense category No. of nights in hospital U.S. Citizen Time w/out phone Home ownership Health care coverage Born in U.S. 29 potential predictors (HH or reference person characteristics) of DU level NR based on NHIS data (all eligible MEPS sample persons)

15. Advancing Excellence in Health Care Testing for Panel Effect

16. Advancing Excellence in Health Care Medical Provider Component Purpose Compensate for household item nonresponse Compensate for household item nonresponse Gold standard for expenditure estimates Gold standard for expenditure estimates Greater accuracy and detail Greater accuracy and detail Imputation source Imputation source Supports methodological studies Supports methodological studies

17. Advancing Excellence in Health Care Medical Provider Component Targeted Sample All associated hospitals and associated physicians All associated hospitals and associated physicians All associated office-based physicians All associated office-based physicians All associated home health agencies All associated home health agencies All associated pharmacies All associated pharmacies Data Collected Dates of visit Dates of visit Diagnosis and procedure codes Diagnosis and procedure codes Charges and payments Charges and payments

18. Advancing Excellence in Health Care MPC: Correction Source for Item Nonresponse Y ij = Imputed $ ij nonresponsenonresponse Y ij = Household $ ij 1 nonresponsereported Y ij = Provider $ ij reportedNonresponse reportedReported MEPS value - Y ij ProviderHousehold Source for event level expenditures 1 Recalibrated as necessary based on analyses of concordance between sources

19. Advancing Excellence in Health Care Determination of Factors for Expenditure Imputation Factors associated with predicting medical expenditures Factors associated with item nonresponse Hot Deck Imputation: Classification Variables for Donors and Recipients

20. Agency for Healthcare Research and Quality Advancing Excellence in Health Care www.ahrq.gov The Utility of Extended Longitudinal Profiles in Predicting Future Health Care Expenditures

21. Advancing Excellence in Health Care Predictive Models Model 1: Logistic Model with prior year’s medical expenditures and precursor information (t-1). Model 1: Logistic Model with prior year’s medical expenditures and precursor information (t-1). (Y=1 top 10% in $s; 0 otherwise) Model 2: Logistic Model with prior year’s medical expenditures (t-1) and precursor information (t-1 and t-2). Model 2: Logistic Model with prior year’s medical expenditures (t-1) and precursor information (t-1 and t-2).

22. Advancing Excellence in Health Care Evaluation of Model Performance Develop Model on 2004-2005 MEPS Panel, 2003 NHIS Validate Model on 2006-2007 MEPS Panel, 2005 NHIS Model 1: Logistic Model with prior year’s medical expenditures and precursor information (t-1). Model 1: Logistic Model with prior year’s medical expenditures and precursor information (t-1). Model 2: Logistic Model with prior year’s medical expenditures (t-1) and precursor information (t-1 and t-2). Model 2: Logistic Model with prior year’s medical expenditures (t-1) and precursor information (t-1 and t-2).

23. Advancing Excellence in Health Care Insurance Component - Purpose Availability of health insurance Availability of health insurance Access to health insurance Access to health insurance Cost of health insurance Cost of health insurance Benefit and payment provisions of private health insurance Benefit and payment provisions of private health insurance

24. Advancing Excellence in Health Care Insurance Component - Sample 30,000 establishments: derived from Census Bureau frame 30,000 establishments: derived from Census Bureau frame Supports national and state estimates Supports national and state estimates Employers linked to HC sample Employers linked to HC sample Data released in tabular form on MEPS website Data released in tabular form on MEPS website

25. Advancing Excellence in Health Care Key Administrative Data Available for MEPS Insurance Component 1. Industry 2. Payroll 3. Age of Firm 4. Establishment Size 5. Enterprise Size 6. Location 7. Multi/Single Unit Firm 8. Form of Organization

26. Advancing Excellence in Health Care Uses of Administrative Data in the Insurance Component 1. Sampling 2. Imputation 3. Editing 4. Modeling 5. Table Production 6. Weight Adjustment for Non Response and Control Totals

27. Advancing Excellence in Health Care Key Improvements Due to Use of Administrative Data in the Insurance Component 1. Reduces Respondent Burden 2. Improves Sampling Precision 3. Helps Find Respondent Errors 4. Improves Weight Adjustment 5. Allows Estimates Be Made for Numerous Key Categories 6. Essential for Modeling and Research

28. Advancing Excellence in Health Care Health Workforce Analysis: Area Resource File Area Resource File (ARF) is a health resource information system that enables policymakers, researchers, planners and others to analyze the current state of health care access at the county level. Content includes geographic codes and classifications; health professions supply and detailed demographics; health facility numbers and types; hospital utilization; population characteristics and economic data; environment; and health professions training resources. Sponsored by HRSA

29. Advancing Excellence in Health Care AHRQ Data Center Provides researchers access to non-public use MEPS data (except directly identifiable information) and other restricted data sets; Provides researchers access to non-public use MEPS data (except directly identifiable information) and other restricted data sets; Mode of data analysis Mode of data analysis – on a secure LAN at AHRQ, Rockville – task order agreement with data contractor – combinations of both.

30. Advancing Excellence in Health Care User Supplied Secondary Data Data Type and/or Source Data Type and/or Source – Area Resource File – Health Care Market Variables @ zip code level – Proprietary county level HMO variables – State and MSA level data from Interstudy Publications – State level Medicaid and poverty variables – County level unemployment rates – State level data from BLS – NHIS – Urban Institute – Academy for Health Services Research and Policy – Census Bureau – HCFA – Proprietary state level data – State income tax rates – Centers for Medicare and Medicaid Services Research Focus Research Focus – Changes in Medicaid and SCHIP – Access to Care Issues – Changes in Health Insurance Coverage – Disparities in Health Care Expenditures for Families – State Level Health Care Expenditures

31. Advancing Excellence in Health Care Limitations Greater restrictions in data access for public use Competing demands on host sample frames More frequent survey contacts reduce overall response rate Requires greater coordination across data sources and organizations

32. Advancing Excellence in Health Care Summary Capacity of integrated survey designs to serve as cost efficient sampling frames Capacity of integrated survey designs to serve as cost efficient sampling frames Capacity of integrated survey designs to reduce bias attributable to nonresponse Capacity of integrated survey designs to reduce bias attributable to nonresponse Related enhancements to data quality and analytical capacity Related enhancements to data quality and analytical capacity MEPS applications MEPS applications Limitations Limitations Discussion questions Discussion questions