title: Prospective validation of eight different adherence measures for use with administrative claims data among patients with schizophrenia.
abstract: OBJECTIVE
  The aim of this study was to compare the predictive validity of eight different adherence measures by studying the variability explained between each measure and hospitalization episodes among Medicaid-eligible persons diagnosed with schizophrenia on antipsychotic monotherapy.
  
  
  METHODS
  This study was a retrospective analysis of the Arkansas Medicaid administrative claims data. Continuously eligible adult schizophrenia (ICD-9-CM = 295.**) patients on antipsychotic monotherapy were identified in the recruitment period from July 2000 through April 2004. Adherence rates to antipsychotic therapy in year 1 were calculated using eight different measures identified from the literature. Univariate and multivariable logistic regression models were used to prospectively predict all-cause and mental health-related hospitalizations in the follow-up year.
  
  
  RESULTS
  Adherence rates were computed for 3395 schizophrenic patients with a mean age of 42.9 years, of which 52.5% (n = 1782) were females, and 52.8% (n = 1793) were white. The proportion of days covered (PDC) and continuous measure of medication gaps measures of adherence had equal C-statistics of 0.571 in predicting both all-cause and mental health-related hospitalizations. The medication possession ratio (MPR) continuous multiple interval measure of oversupply were the second best measures with equal C-statistics of 0.568 and 0.567 for any-cause and mental health-related hospitalizations. The multivariate adjusted models had higher C-statistics but provided the same rank order results.
  
  
  CONCLUSIONS
  MPR and PDC were among the best predictors of any-cause and mental health-related hospitalization, and are recommended as the preferred adherence measures when a single measure is sought for use with administrative claims data for patients not on polypharmacy.
authors.affiliation: Department of Pharmacy Administration, College of Pharmacy, The Ohio State University, Columbus, OH, USA.
authors.forename: Sudeep
authors.initials: S
authors.lastname: Karve
authors.forename: Mario A
authors.initials: MA
authors.lastname: Cleves
authors.forename: Mark
authors.initials: M
authors.lastname: Helm
authors.forename: Teresa J
authors.initials: TJ
authors.lastname: Hudson
authors.forename: Donna S
authors.initials: DS
authors.lastname: West
authors.forename: Bradley C
authors.initials: BC
authors.lastname: Martin
mesh_terms: D000293:Adolescent; D000328:Adult; D014150:Antipsychotic Agents / Q000627:therapeutic use*; D001131:Arkansas; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004363:Drug Utilization / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007344:Insurance Claim Reporting; D016015:Logistic Models; D008297:Male; D008484:Medicaid; D008875:Middle Aged; D012559:Schizophrenia / Q000188:drug therapy*; D014481:United States; D055815:Young Adult; D016903:Drug Monitoring
chemical_list: D014150:Antipsychotic Agents