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Switching From Retrospective to Current Year Data Collection in the Medical Expenditure Panel Survey-Insurance Component (MEPS-IC). Anne T. Kearney U.S. Census Bureau John P. Sommers Agency for Healthcare Research and Quality ICES III Session 7. Important Terms.
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Switching From Retrospective to Current Year Data Collection in the Medical Expenditure Panel Survey-Insurance Component (MEPS-IC) Anne T. Kearney U.S. Census Bureau John P. Sommers Agency for Healthcare Research and Quality ICES III Session 7
Important Terms • Retrospective Design: collects data for the year prior to the collection period • Current Year Design: collects data in effect at the time of collection • Survey Year: the year of data being collected in the field • Single Unit Establishment vs. Multi-Unit Establishment
Outline • Background on MEPS-IC • Why Switch to Current?/Barriers to Switching • Impact on Frame and Reweighting Methodology • Details of Current Year Trial Methods • Results • Summary
Background on MEPS-ICGeneral • Annual establishment survey that provides estimates of insurance availability and costs • Sample of 42,000 private establishments • National and state-level estimates • Retrospective design
Background on MEPS-ICTiming Example • Let’s say retrospective design in survey year 2002 • Create frame/sample in March 2003 using 2001 data from the business register (BR) • Create SU birth frame with 2002 data from BR • In the field from roughly July-December 2003 • Reweighting in March-April 2004 using 2002 data from the BR • Estimation and publication in May-June 2004
Why Switch to a Current Year Design? • Estimates published about 1 year sooner • Some establishments report current data already; current data is at their fingertips • Most survey estimates are conducive to current year design • Better coverage of businesses that closed after the survey year and before the field operation • Some data users in favor of going current
Barriers to Switching to a Current Year Design • One year older data for frame building • One year older data for reweighting • These could possibly make our estimates very different which we believe means worse • Other data users believe retrospective design is better for collecting certain items
Impact on Frame Example: Let’s use 2002 survey year again:
Impact on ReweightingNonresponse Adjustment • We use an iterative raking procedure • We do the NR Adjustment using 3 sets of • cells: • Sector Groups • SU/MU • State by Size Group
Impact on ReweightingPoststratification • We use an iterative raking procedure using 2 • sets of cells: • State by Size Group and SU/MU • Under the retrospective design for the 2002 survey:
Details of Trial Methods • One issue for frame: • What to do with the births • One issue for nonresponse adjustment: • What employment data to use for cell assignments • Three issues for poststratification: • What employment data to use for cell assignments • What employment data to use for total employment • What payroll data to use to create the list of establishments for total employment
ResultsDefinitions • National level estimates • Estimates by firm size • Establishments categorized by their firm employment
ResultsSurvey Year 2002 * Indicates significant difference
ResultsSurvey Year 2002 * Indicates significant difference
ResultsSurvey Year 2003 * Indicates significant difference
Summary • Many positives with going current – timing • Possible frame and reweighting problems but prior year data are a good substitute • Tested 4 Trial Methods and found: • Estimates of premiums look good and rates looked reasonable • Establishment and employment estimates are different but not most important estimates
Summary (cont.) • We are planning to switch to a current year design for survey year 2008 using a methodology similar to Method 5. • We have similar research planned for the governments sample and also plan to continue the research on the private sector with more recent data.
Anne.Theresa.Kearney@census.gov John.Sommers@ahrq.hhs.gov