title: Identifying a sample of HIV-positive beneficiaries from Medicaid claims data and estimating their treatment costs.
abstract: OBJECTIVE
  We sought to identify people living with HIV/AIDS from Medicare and Medicaid claims data to estimate Medicaid costs for treating HIV/AIDS in California. We also examined how alternate methods of identifying the relevant sample affect estimates of per capita costs.
  
  
  METHODS
  We analyzed data on Californians enrolled in Medicaid with an HIV/AIDS diagnosis reported in 2007 Medicare or Medicaid claims data. We compared alternative selection criteria by examining use of antiretroviral drugs, HIV-specific monitoring tests, and medical costs. We compared the final sample and average costs with other estimates of the size of California's HIV/AIDS population covered by Medicaid in 2007 and their average treatment costs.
  
  
  RESULTS
  Eighty-seven percent (18,290) of potentially identifiable HIV-positive individuals satisfied at least 1 confirmation criterion. Nearly 80% of confirmed observations had claims for HIV-specific tests, compared with only 3% of excluded cases. Female Medicaid recipients were particularly likely to be miscoded as having HIV. Medicaid treatment spending for Californians with HIV averaged $33,720 in 2007.
  
  
  CONCLUSIONS
  The proposed algorithm displays good internal and external validity. Accurately identifying HIV cases in claims data is important to avoid drawing biased conclusions and is necessary in setting appropriate HIV managed-care capitation rates.
authors.affiliation: Both authors are with the Department of Public Policy, Luskin School of Public Affairs, University of California Los Angeles.
authors.forename: Arleen A
authors.initials: AA
authors.lastname: Leibowitz
authors.forename: Katherine
authors.initials: K
authors.lastname: Desmond
mesh_terms: D002140:California; D003627:Data Interpretation, Statistical; D005260:Female; D006679:HIV Seropositivity / Q000191:economics* / Q000628:therapy; D017048:Health Care Costs; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D019458:Insurance Coverage / Q000592:standards* / Q000639:trends; D008297:Male; D008484:Medicaid / Q000191:economics* / Q000331:legislation & jurisprudence / Q000639:trends; D006278:Medicare / Q000191:economics* / Q000331:legislation & jurisprudence / Q000639:trends; D058991:Patient Protection and Affordable Care Act; D014481:United States