title: Trajectories of Diabetes Medication Adherence and Hospitalization Risk: A Retrospective Cohort Study in a Large State Medicaid Program.
abstract: Numerous interventions are available to boost medication adherence, but the targeting of these interventions often relies on crude measures of poor adherence. Group-based trajectory models identify individuals with similar longitudinal prescription filling patterns. Identifying distinct adherence trajectories may be more useful for targeting interventions, although the association between adherence trajectories and clinical outcomes is unknown.
  
  
  
  To examine the association between adherence trajectories for oral hypoglycemics and subsequent hospitalizations among diabetes patients.
  
  
  
  Retrospective cohort study.
  
  
  
  A total of 16,256 Pennsylvania Medicaid enrollees, non-dually eligible for Medicare, initiating oral hypoglycemics between 2007 and 2009.
  
  
  
  We used group-based trajectory models to identify trajectories of oral hypoglycemics in the 12 months post-treatment initiation, using monthly proportion of days covered (PDC) as the adherence measure. Multivariable Cox proportional hazard models were used to examine the association between trajectories and time to first diabetes-related hospitalization/emergency department (ED) visits in the following year. We used the C-index to compare prediction performance between adherence trajectories and dichotomous cutpoints (annual PDC <80 vs. ≥80 %).
  
  
  
  The mean annual PDC was 0.58 (SD 0.32). Seven trajectories were identified: perfect adherers (9 % of the cohort), nearly perfect adherers (31.4 %), moderate adherers (21.0 %), low adherers (11.0 %), late discontinuers (6.8 %), early discontinuers (9.7 %), and non-adherers with only one fill (11.1 %). Compared to perfect adherers, trajectories of moderate adherers (HR = 1.48, 95 % CI 1.25, 1.75), low adherers (HR = 1.51, 95 % CI 1.25, 1.83), and non-adherers with only one fill (HR = 1.35, 95 % CI 1.09, 1.67) had greater risk of diabetes-related hospitalizations/ED visits. Predictive accuracy was improved using trajectories compared to dichotomized cutpoints (C-index = 0.714 vs. 0.652).
  
  
  
  Oral hypoglycemic treatment trajectories were highly variable in this large Medicaid cohort. Low and moderate adherers and those filling only one prescription had a modestly higher risk of hospitalizations/ED visits compared to perfect adherers. Trajectory models may be valuable in identifying specific non-adherence patterns for targeting interventions.
authors.affiliation: Department of Pharmacy Practice and Science, College of Pharmacy, University of Arizona, Tucson, AZ, USA. lociganic@pharmacy.arizona.edu.
authors.forename: Wei-Hsuan
authors.initials: WH
authors.lastname: Lo-Ciganic
authors.affiliation: Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.|Center for Pharmaceutical Policy and Prescribing, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Julie M
authors.initials: JM
authors.lastname: Donohue
authors.affiliation: Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
authors.forename: Bobby L
authors.initials: BL
authors.lastname: Jones
authors.affiliation: Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Subashan
authors.initials: S
authors.lastname: Perera
authors.affiliation: Center for Pharmaceutical Policy and Prescribing, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA.|Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA.
authors.forename: Joshua M
authors.initials: JM
authors.lastname: Thorpe
authors.affiliation: Center for Pharmaceutical Policy and Prescribing, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA.|Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA.
authors.forename: Carolyn T
authors.initials: CT
authors.lastname: Thorpe
authors.affiliation: Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, USA.
authors.forename: Zachary A
authors.initials: ZA
authors.lastname: Marcum
authors.affiliation: Center for Pharmaceutical Policy and Prescribing, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.|Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA.
authors.forename: Walid F
authors.initials: WF
authors.lastname: Gellad
mesh_terms: D000328:Adult; D003920:Diabetes Mellitus / Q000188:drug therapy* / Q000191:economics / Q000453:epidemiology; D005260:Female; D005500:Follow-Up Studies; D006760:Hospitalization / Q000639:trends*; D006801:Humans; D007004:Hypoglycemic Agents / Q000191:economics / Q000627:therapeutic use*; D008297:Male; D008484:Medicaid / Q000191:economics / Q000639:trends*; D055118:Medication Adherence; D008875:Middle Aged; D010414:Pennsylvania / Q000453:epidemiology; D012189:Retrospective Studies; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
chemical_list: D007004:Hypoglycemic Agents
keywords: Medicaid; diabetes; group-based trajectory models; medication adherence; oral hypoglycemics