title: Medical care price indexes for patients with employer-provided insurance: nationally representative estimates from MarketScan Data.
abstract: OBJECTIVE
  Commonly observed shifts in the utilization of medical care services to treat diseases may pose problems for official price indexes at the Bureau of Labor Statistics (BLS) that do not account for service shifts. We examine how these shifts may lead to different price estimates than those observed in official price statistics at the BLS.
  
  
  METHODS
  We use a convenience sample of enrollees with employer-provided insurance from the MarketScan database for the years 2003 to 2007. Population weights that consider the age, sex, and geographic distribution of enrollees are assigned to construct representative estimates.
  
  
  METHODS
  We compare two types of price indexes: (1) a Service Price Index (SPI) that is similar to the BLS index, which holds services fixed and measures the prices of the underlying treatments; (2) a Medical Care Expenditure Index (MCE) that measures the cost of treating diseases and allows for utilization shifts.
  
  
  RESULTS
  Over the entire period of study the CAGR of the SPI grows 0.7 percentage points faster than the preferred MCE index.
  
  
  CONCLUSIONS
  Our findings suggest that the health component of inflation may be overstated by 0.7 percentage points per year, and real GDP growth may be understated by a similar amount. However, more work may be necessary to precisely replicate the indexes of the BLS to obtain a more accurate measure of these price differences.
authors.affiliation: Bureau of Economic Analysis, Washington, DC, USA.
authors.forename: Abe
authors.initials: A
authors.lastname: Dunn
authors.forename: Eli
authors.initials: E
authors.lastname: Liebman
authors.forename: Sarah
authors.initials: S
authors.lastname: Pack
authors.forename: Adam Hale
authors.initials: AH
authors.lastname: Shapiro
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002648:Child; D002675:Child, Preschool; D003625:Data Collection / Q000379:methods*; D005260:Female; D006264:Health Benefit Plans, Employee / Q000191:economics* / Q000706:statistics & numerical data*; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006296:Health Services / Q000191:economics* / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D012111:Residence Characteristics / Q000706:statistics & numerical data; D012737:Sex Factors; D014481:United States; D055815:Young Adult