The MEPS-HC PME files from the same period were used to estimate prescribed medicine utilization and expenditures for 2005-2008.
Data from MEPS-HC PME files were merged with MEPSHC consolidated full year files using the respondent unique identifier and the panel number to obtain the final analytical dataset.
Standard errors were adjusted for the complex sampling design of the MEPS-HC using the Taylor Series approach.
In the MEPS-HC data, we cannot directly determine the degree of appropriate versus inappropriate antibiotic use, but the conditions associated with antibiotic purchases provide some evidence.
The usage and expenditure values cover the following medical care categories as they are itemized in the MEPS-HC data files:
In an effort to construct the standardized population to closely resemble the healthcare usage and spending patterns of ESHI plan enrollees, MEPS-HC individual records are selected based on several criteria.
To supplement the expenditure data provided from the MEPS-HC
respondents and improve the accuracy of resultant expenditure estimates, the MEPS includes a medical provider survey.
Information on these four panels is based on the sample of 20,092 individuals in MEPS-HC
In addition, the MEPS-HC
contains questions rigorously developed for the Consumer Assessment of Healthcare Providers and Systems (CAHPS) about getting needed care right away, getting appointments for routine care when wanted, problems seeing specialists, and problems getting care, tests, or treatment.
, which began in 1996, is a household-based survey that contains individual and household-level estimates of health care expenditures and use, health insurance coverage, and a wide range of other health-related and socioeconomic characteristics.
A very important constraint in our modeling was that any variable used in the plan choice model from the employer data also had to be available in the MEPS-HC
to permit a simulation.
We construct synthetic workforces by statistically matching MEPS-HC
workers to MEPS-IC establishments in a two-step process that first uses establishment-level characteristics to draw a sample of workers for each establishment and then uses information on worker characteristics to fine-tune the match.