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A Comparison of Two Sample Designs for the MEPS-IC

John P. SommersAgency for Healthcare Research and Quality

Anne T. KearneyU. S. Census Bureau

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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

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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

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Comparison of Old and New DesignsOLD NEW

•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

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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.

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Problem: How to Evaluate and Compare Sample Designs Across Years,

2002 vs. 2004

1. 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

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Quality MeasuresInitial 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

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Quality Measures

1. Relative Standard Error (RSE)

2. Square Root of the Design Effect

3. Unit RSE = Square root of sample size times RSE

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Tested Hypothesis

H p QM QM

H p QM QMA

0 2 0 0 2 2 0 0 4

2 0 0 2 2 0 0 4

0 5

0 5

( ) .

( ) .

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Pseudo National EstimatesMeasure Unit RSE Root Design

EffectRSE

Variable 2002 2004 2002 2004 2002 2004

Avg. Family Contribution 2.277 2.062 0.434 0.333 0.0151 0.0144

Avg. Family Premium 0.897 0.745 0.408 0.249 0.0059 0.0052

Avg. Single Contribution* 2.343 2.007 0.489 0.444 0.0155 0.0141

Avg. Single Premium 0.921 0.837 0.514 0.404 0.0061 0.0059

% Employed Where Ins. Offered 0.505 0.483 0.537 0.353 0.0034 0.0034

% Enrolled Where Ins. Offered* 1.268 1.061 0.442 0.335 0.0086 0.0074

% of Employees Enrolled 1.358 1.138 0.414 0.304 0.0092 0.0079

% of Establishments That Offer Health Insurance* 0.980 0.912 1.141 1.021 0.0066 0.0064

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Average Results of State EstimatesMeasure Avg. Unit

RSEAvg. Root

Design EffectAvg. RSE

Variable 2002 2004 2002 2004 2002 2004

Avg. Family Contribution 1.975 1.824 0.412 0.358 0.076 0.074

Avg. Family Premium 0.703 0.671 0.368 0.305 0.027 0.028

Avg. Single Contribution* 2.050 1.834 0.474 0.435 0.079 0.075

Average Single Premium 0.744 0.671 0.478 0.385 0.029 0.027

% Employed Where Insurance Offered 0.453 0.477 0.494 0.411 0.018 0.019

% Enrolled Where Insurance Offered* 1.149 1.053 0.417 0.345 0.045 0.042

% of All Employees Enrolled 1.246 1.142 0.395 0.309 0.048 0.046

% of Establishments That Offer Health Insurance* 0.974 0.902 1.068 0.957 0.038 0.036

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Average National Results by Firm Size

Measure Avg. Unit RSE

Avg. Rt. Design Effect

Avg. RSE

Variable 2002 2004 2002 2004 2002 2004

Firms with less than 50 employees 1.510 1.510 1.077 1.143 0.0155 0.0160

Firms with 50 or more employees 1.071 0.913 0.550 0.430 0.0095 0.0087

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Average National Results by Industry Measure

Avg. Unit RSE

Avg. Rt. Design Effect

Avg. RSE

Industry 2002 2004 2002 2004 2002 2004

Ag., Forestry and Fishing 1.737 2.173 0.615 0.691 0.088 0.131

Construction 1.473 1.397 0.776 0.752 0.038 0.038

Fin Svcs / Real Estate 0.944 0.959 0.651 0.468 0.019 0.018

Mfg. and Mining 1.094 0.843 0.506 0.412 0.021 0.016

Other Services 1.630 1.665 0.686 0.714 0.024 0.028

Professional Services 1.305 1.012 0.534 0.386 0.017 0.014

Retail Trade 1.209 1.075 0.881 0.960 0.021 0.021

Utilities and Trans. 1.225 1.187 0.460 0.453 0.045 0.042

Wholesale Trade 1.017 1.018 0.832 0.477 0.029 0.029

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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

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John.Sommers@ahrq.hhs.gov

Anne.Theresa.Kearney@census.gov