title: Association among change in medical costs, level of comorbidity, and change in adherence behavior.
abstract: Interventions to improve medication adherence are effective, but resource intensive. Interventions must be targeted to those who will potentially benefit most. We examined what heterogeneity exists in the value of adherence based on levels of comorbidity, and the changes in spending on medical services that followed changes in adherence behavior.
  
  
  
  Retrospective cohort study examining medical spending for 2 years (April 1, 2011, to March 31, 2013) in commercial insurance beneficiaries.
  
  
  
  Multivariable linear modeling was used to adjust for differences in patient characteristics. Analyses were performed at the patient/condition level in 2 cohorts: adherent at baseline and nonadherent at baseline.
  
  
  
  We evaluated 857,041 patients, representing 1,264,797 patient therapies consisting of 40% high cholesterol, 48% hypertension, and 12% diabetes. Among those with 3 or more conditions, annual savings associated with becoming adherent were $5341, $4423, and $2081 for patients with at least diabetes, hypertension, and high cholesterol, respectively. The increased costs for patients in this group who became nonadherent were $4653, $7946, and $4008, respectively. Depending on the condition and the direction of behavior change, savings were 2 to 7 times greater than the value for individuals with fewer than 3 conditions. In most cases, the value of preventing nonadherence (ie, persistence) was greater than the value of moving people who are nonadherent to an adherent state.
  
  
  
  There is important heterogeneity in the impact of medication adherence on medical spending. Clinicians and policy makers should consider this when promoting the change of adherence behavior.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Kymes
authors.forename: Richard L
authors.initials: RL
authors.lastname: Pierce
authors.affiliation: CVS Health, 9501 E Shea Blvd, Scottsdale, AZ 85260. E-mail: Charmaine.Girdish@CVSHealth.com.
authors.forename: Charmaine
authors.initials: C
authors.lastname: Girdish
authors.forename: Olga S
authors.initials: OS
authors.lastname: Matlin
authors.forename: Tryoen
authors.initials: T
authors.lastname: Brennan
authors.forename: William H
authors.initials: WH
authors.lastname: Shrank
mesh_terms: D000328:Adult; D000368:Aged; D015897:Comorbidity; D017046:Cost Savings; D003920:Diabetes Mellitus / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology / Q000523:psychology; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D006937:Hypercholesterolemia / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology / Q000523:psychology; D006973:Hypertension / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology / Q000523:psychology; D007342:Insurance Benefits / Q000191:economics* / Q000592:standards; D007345:Insurance Claim Review; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D055118:Medication Adherence / Q000523:psychology*; D008875:Middle Aged; D000071069:Multiple Chronic Conditions / Q000188:drug therapy / Q000191:economics* / Q000453:epidemiology / Q000523:psychology; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care / Q000191:economics / Q000706:statistics & numerical data; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology; D016903:Drug Monitoring