New Data on Geographic Variation in Medicare

The Centers for Medicare & Medicaid Services (CMS) has developed data that enables researchers and policymakers to evaluate geographic variation in the utilization and quality of health care services for the Medicare fee-for-service population. They have aggregated this data into a Geographic Variation Public Use File that has demographic, spending, utilization, and quality indicators at the state level (including the District of Columbia, Puerto Rico, and the Virgin Islands), hospital referral region (HRR) level, and county level.

The Geographic Variation Public Use File has twelve separate files – two files with state and county-level data, four files with only state-level data, and six files with HRR-level data. The files are presented in two different formats. The “Table” files present indicators for all states, counties, or HRRs, and can easily be exported from Excel to another data analysis program for additional analysis, while the corresponding “Report” files allow users to compare a specific state, county, or HRR to national Medicare benchmarks. The state- and HRR-level data is presented for beneficiaries under the age of 65, beneficiaries that are 65 or older, and all beneficiaries regardless of age. However, the county-level data is only available for all beneficiaries. Each file has a brief Methods section outlining the sample population and methodology that they used to calculate these indicators and a Documentation section which explains the individual indicators in more detail. Finally, there is also a Methodological Overview paper and a Technical Supplement on Standardization that provides additional information on the methodology they used to standardize claim payment amounts.

CMS most recently updated the Geographic Variation Public Use File in December 2013. (The file was originally posted in July 2011 and updated in July 2012, January 2013, and May 2013.) The December 2013 update adds data for calendar year 2012 and incorporates several minor revisions to the CMS methodology.

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