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Building Wave Response Rates in a Longitudinal Survey: Essential for Nonsampling Error Reduction or Last In - First Out?. Steven B. Cohen Fred Rohde and William Yu Agency for Healthcare Research and Quality. Purpose of Discussion.
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Building Wave Response Rates in a Longitudinal Survey: Essential for Nonsampling Error Reduction or Last In - First Out? Steven B. Cohen Fred Rohde and William Yu Agency for Healthcare Research and Quality
Purpose of Discussion • Need for essential longitudinal data on health care coverage, use and expenditures to inform health care policy and practice • Description of the Medical Expenditure Panel Survey (MEPS): purpose, longitudinal design and analytical capacity • Focus on field efforts to achieve target response rates
Purpose of Discussion • Evaluations of the quality of the MEPS nonresponse adjustment strategies • Determination of characteristics for cases fielded at end of field period (EOF) & conversion of temporary refusals (TNR). • Examine ROI for inclusion of these cases.
Purpose of Discussion • Examine impact on annual and longitudinal response rates; completion of self administered questionnaires (SAQ) • Impact on key survey estimates of health insurance coverage and expenditures • Implications of alternative field strategies
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 • Role of demographics, family structure, insurance • Expenditures for specific conditions • Trends over time
Key Features of MEPS-HC • Survey of U.S. civilian noninstitutionalized population • Sub-sample of respondents to the National Health Interview Survey (NHIS) • Linkage to NHIS • Oversample of minorities and other target groups • 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
MEPS Overlapping Panels(Panels 8 and 9) MEPS Household Component MEPS Panel 8 2003-2004 1/1/2003 1/1/2004 NHIS 2002 Round 1 Round 2 Round 3 Round 4 Round 5 NHIS 2003 Round 1 Round 2 Round 3 Round 4 Round 5 MEPS Panel 9 2004-2005
MEPS Household ComponentSample Design Oversampling of policy relevant domains 1996 Minorities (Blacks & Hispanics) 1997 Minorities Low income Children with activity limitations Adults with functional limitations Predicted high expenditure cases Elderly 1998-2001 Minorities 2002+ Minorities, Asians, Low Income 15,000 households; ~35,000 persons
Target Precision Specifications for national and regional estimates; policy relevant subgroups Overall Design effect of 1.6 200 PSU design (Max) Overall/round specific survey response rate requirements Linkage to NHIS Multistage design Disproportional sampling Longitudinal design Minimize survey cost for fixed precision Design Specifications
MEPS, 1996–2006: Number of uninsured, under age 65 Number in millions Source: Center for Financing, Access, and Cost Trends, AHRQ, Household Component of the Medical Expenditure Panel Survey, 1996–2005 Full-Year and 1996–2006 Point-in-Time Files
Trends in Concentration Percentage of expenditures Source: National Medical Care Expenditure Survey, 1977; National Medical Expenditure Survey, 1987; Medical Expenditure Panel Survey, 1996 and 2005.
MEPS Field Force • Westat is data collection organization • 500 interviewers • Sample allocated in ~ 200 PSUs, spread across all 50 states • extensive training modules • Information on socio-demographic characteristics of households available based on linkage with NHIS • Remuneration for survey participation
Tool Chest of Methods to Maximize Survey Response • Recruitment of experienced and bilingual interviewer • 10+ days training (including procedures for obtaining signed consents) • Uses of MEPS data as reference materials for interviewers • Periodic retraining and special trainings (e.g. methods to improve response rates) • Respondent remuneration • Advance mailings from co-sponsors of survey • Monthly planning calendar and MEPS DVD • Daily emails to interviewers regarding interviewing progress • Multiple contacts for refusal conversions
MEPS Target Response Rates by Round and Overall *NHIS response rate among households designated for MEPS. Note: Year 1 and the Overall response rate include the NHIS response rate.
Person Level (survey attrition) Nonresponse Adjustment Covariates • Factors associated with survey attrition (after R1) • Indicator for initial refusal to R1 interview • Family size • Age • MSA, census region • Marital status (family reference person) • Race/ethnicity • Education of reference person • Employment status • Health insurance status • Total expenditures (in yr 1 for yr 2 adj.) • # doctor visits (in yr 1) • Self reported health status
Person Level Adjustments:Annual Estimates • Each MEPS panel weighted separately • Nonresponse adjustment for complete nonresponse and for survey attrition • Final Poststratification adjustment –CPS 12/31: age, race/ethnicity, sex, region, MSA status, poverty status
Capacity of MEPS to Produce Comparable NHIS Estimates of Health Insurance Coverage
Characteristics of Respondents Fielded at End of First Round or Temporary Refusal Initial Refusals: Higher likelihood: • MSA residence; Northeast region; white Non-Hispanic; elderly; excellent health; some high school; family size 2+; Attrite in future waves of data collection End of Field Period Cases Higher likelihood: • Race: Asian or Black • in excellent health • Attrite in future waves of data collection
Testing for Reluctant Response Effect on Coverage Estimates ------------------------------------------------------- DF Wald F P-Value ------------------------------------------------------- OVERALL MODEL 22 107.98 0.0000 JULY INTERVIEW 1 2.38 0.1244 TEMP. REFUSALS 1 0.92 0.3393 SEX 1 98.02 <0.0001 RACE/ETHNICITY 3 58.42 <0.0001 MARITAL STATUS 4 16.90 <0.0001 EDUCATION 4 10.94 <0.0001 POVERTY STATUS 4 43.97 <0.0001 MSA STATUS 1 4.34 0.0382 INDIVIDUAL INCOME 1 35.52 <0.0001 MEDICAL $ 1 35.79 <0.0001 ------------------------------------------------------- -2 * Normalized Log-Likelihood Full Model: 13037.78 Pseudo R2: :0.194167
Conditional Response Rates by Month of Round 1 Response: Panel 9
Impact on MSE of Mean Medical Expenditure Estimates for alternative field strategies
Impact on MSE of Proportion with Medical Expenses in excess of $10,000 for alternative field strategies
Summary • Need for accurate and reliable national data on health insurance coverage to inform policy and practice • MEPS design features and analytical capacity • Statistical, methodological and operational design features to adjust for nonresponse and attrition • Evaluation of estimation strategies to correct for survey attrition • Examination of ROI for inclusion of difficult cases • Options identified for more efficient and effective field strategies