1 A Comparison of Two Sample Designs for the MEPS-IC John P. Sommers Agency for Healthcare Research and Quality Anne T. Kearney U. S. Census Bureau.

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Presentation transcript:

1 A Comparison of Two Sample Designs for the MEPS-IC John P. Sommers Agency for Healthcare Research and Quality Anne T. Kearney U. S. Census Bureau

2 Presentation Outline 1.What is the MEPS-IC? 2.The Two Private Sector Sample Designs 3.Purpose of this Study 4.Measures Used to Compare 5.Results 6.Lessons Learned

3 The Medical Expenditure Panel Survey - Insurance Component (MEPS-IC) 1.Annual survey of Business Establishments and Governments 2.Information Collected on Offer Rates, Enrollments, Costs and Characteristics of Employer Health Insurance

4 Comparison of Old and New Designs OLDNEW 14 strata per state Strata boundaries are employment size classes Min sample in 40 states 31 largest states have minimum each year Average state variance components Optimal allocation using 2 variables 15 strata per state Strata boundaries are predicted: % offering and # enrollees Min sample in all states Average state variance components Optimal allocation using 3 variables

5 Purpose of this Study To determine if the new sample design fully implemented in 2004 improved our estimates of variances for eight key variables of interest.

6 Problem: How to Evaluate and Compare Sample Designs Across Years, 2002 vs Could not compare standard errors due to the natural increase in some standard errors as mean values increase 2.Changes in sample allocation to states: 2002 had fewer sample units 2002 did not have min sample sizes in all states

7 Quality Measures Initial Step 1.We did comparisons over the 31 largest states since they had similar sample size before nonresponse in both years 2.These 31 largest states have over 90% of universe 3.We created pseudo-national level estimates from these 31 states

8 Quality Measures 1.Relative Standard Error (RSE) 2.Square Root of the Design Effect 3.Unit RSE = Square root of sample size times RSE

9 Tested Hypothesis

10 Pseudo National Estimates MeasureUnit RSERoot Design Effect RSE Variable Avg. Family Contribution Avg. Family Premium Avg. Single Contribution* Avg. Single Premium % Employed Where Ins. Offered % Enrolled Where Ins. Offered* % of Employees Enrolled % of Establishments That Offer Health Insurance*

11 Average Results of State Estimates MeasureAvg. Unit RSE Avg. Root Design Effect Avg. RSE Variable Avg. Family Contribution Avg. Family Premium Avg. Single Contribution* Average Single Premium % Employed Where Insurance Offered % Enrolled Where Insurance Offered* % of All Employees Enrolled % of Establishments That Offer Health Insurance*

12 Average National Results by Firm Size MeasureAvg. Unit RSE Avg. Rt. Design Effect Avg. RSE Variable Firms with less than 50 employees Firms with 50 or more employees

13 Average National Results by Industry Measure Avg. Unit RSE Avg. Rt. Design Effect Avg. RSE Industry Ag., Forestry and Fishing Construction Fin Svcs / Real Estate Mfg. and Mining Other Services Professional Services Retail Trade Utilities and Trans Wholesale Trade

14 Lessons Learned Targeted and most other estimates improved at the State and National Level Effect of new sample design on estimates for subpopulations appears to depend upon the prevalence within the subcategory of offering insurance to employees

15