OBJECTIVES: 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. STUDY DESIGN: Retrospective cohort study examining medical spending for 2 years (April 1, 2011, to March 31, 2013) in commercial insurance beneficiaries. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
OBJECTIVES: 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. STUDY DESIGN: Retrospective cohort study examining medical spending for 2 years (April 1, 2011, to March 31, 2013) in commercial insurance beneficiaries. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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: Cozumel S Pruette; Shayna S Coburn; Cyd K Eaton; Tammy M Brady; Shamir Tuchman; Susan Mendley; Barbara A Fivush; Michelle N Eakin; Kristin A Riekert Journal: Pediatr Nephrol Date: 2018-08-16 Impact factor: 3.714
Authors: Timothy P Ryan; Ryan D Morrison; Jeffrey J Sutherland; Stephen B Milne; Kendall A Ryan; J Scott Daniels; Anita Misra-Hebert; J Kevin Hicks; Eric Vogan; Kathryn Teng; Thomas M Daly Journal: PLoS One Date: 2017-09-28 Impact factor: 3.240
Authors: Patrick J Campbell; David R Axon; Ann M Taylor; Matthew Pickering; Heather Black; Terri Warholak; Chanadda Chinthammit Journal: J Am Heart Assoc Date: 2020-08-26 Impact factor: 5.501