title: Utilization of genetic tests: analysis of gene-specific billing in Medicare claims data.
abstract: We examined the utilization of precision medicine tests among Medicare beneficiaries through analysis of gene-specific tier 1 and 2 billing codes developed by the American Medical Association in 2012.
  
  
  
  We conducted a retrospective cross-sectional study. The primary source of data was 2013 Medicare 100% fee-for-service claims. We identified claims billed for each laboratory test, the number of patients tested, expenditures, and the diagnostic codes indicated for testing. We analyzed variations in testing by patient demographics and region of the country.
  
  
  
  Pharmacogenetic tests were billed most frequently, accounting for 48% of the expenditures for new codes. The most common indications for testing were breast cancer, long-term use of medications, and disorders of lipid metabolism. There was underutilization of guideline-recommended tumor mutation tests (e.g., epidermal growth factor receptor) and substantial overutilization of a test discouraged by guidelines (methylenetetrahydrofolate reductase). Methodology-based tier 2 codes represented 15% of all claims billed with the new codes. The highest rate of testing per beneficiary was in Mississippi and the lowest rate was in Alaska.
  
  
  
  Gene-specific billing codes significantly improved our ability to conduct population-level research of precision medicine. Analysis of these data in conjunction with clinical records should be conducted to validate findings.Genet Med advance online publication 26 January 2017.
authors.affiliation: RTI International, Waltham, Massachusetts, USA.|Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA.
authors.forename: Julie A
authors.identifier: 0000-0003-0108-2127
authors.initials: JA
authors.lastname: Lynch
authors.affiliation: RTI International, Waltham, Massachusetts, USA.|Boston University School of Medicine, Boston, Massachusetts, USA.|Veterans Health Administration, Bedford, Massachusetts, USA.
authors.forename: Brygida
authors.initials: B
authors.lastname: Berse
authors.affiliation: Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
authors.forename: W David
authors.identifier: 0000-0002-9606-6594
authors.initials: WD
authors.lastname: Dotson
authors.affiliation: Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
authors.forename: Muin J
authors.identifier: 0000-0002-9887-443X
authors.initials: MJ
authors.lastname: Khoury
authors.affiliation: RTI International, Research Triangle Park, North Carolina, USA.
authors.forename: Nicole
authors.identifier: 0000-0002-3111-3775
authors.initials: N
authors.lastname: Coomer
authors.affiliation: RTI International, Waltham, Massachusetts, USA.
authors.forename: John
authors.identifier: 0000-0002-2530-4727
authors.initials: J
authors.lastname: Kautter
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor; D003430:Cross-Sectional Studies; D005260:Female; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D008175:Lung Neoplasms / Q000191:economics / Q000473:pathology / Q000628:therapy; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D008875:Middle Aged; D057285:Precision Medicine / Q000191:economics / Q000706:statistics & numerical data; D012189:Retrospective Studies; D014481:United States
chemical_list: D014408:Biomarkers, Tumor