OBJECTIVE: The objective of this study was to differentiate between 3 measures of antidepressant adherence with regard to the number of patients deemed adherent to therapy and the association between adherence and resource utilization. DESIGN AND SETTING: The authors conducted a retrospective study of patients initiating selective serotonin reuptake inhibitor (SSRI) therapy for depression and/or anxiety between July 2001 and June 2002 in a large national managed care database. MAIN OUTCOME MEASURES: Rates of 6-month SSRI adherence were measured by 3 different metrics: length of therapy (LOT), medication possession ratio (MPR), and combined MPR/LOT. Differences in resource utilization for each adherence metric were measured for patients deemed as 1) adherent, 2) nonadherent, 3) therapy changers, and 4) dose titraters. RESULTS: There were 22,947 patients meeting study criteria. Although statistically different, 6-month adherence rates were numerically similar across all methods (LOT, 44.6%; MPR, 43.3%; and MPR/LOT, 42.9%, P < 0.001); approximately 57% of patients were nonadherent to therapy. Regardless of metric, the adherent cohort incurred the lowest yearly medical costs, followed by the nonadherent, titrate, and therapy change cohorts (P < 0.001 between adherent cohort and all other cohorts). The LOT method produced the greatest difference in yearly medical costs between adherent and nonadherent patients (Dollars 511) followed by MPR/LOT (Dollars 432) and MPR (Dollars 423). When antidepressant prescription costs were added to medical costs, patients requiring a therapy change and titrating therapy incurred higher costs than adherent patients, whereas nonadherent and adherent patients incurred similar costs. CONCLUSION: Regardless of adherence metric, approximately 43% of patients were adherent to antidepressant therapy, and adherent patients were associated with the lowest yearly medical costs.
OBJECTIVE: The objective of this study was to differentiate between 3 measures of antidepressant adherence with regard to the number of patients deemed adherent to therapy and the association between adherence and resource utilization. DESIGN AND SETTING: The authors conducted a retrospective study of patients initiating selective serotonin reuptake inhibitor (SSRI) therapy for depression and/or anxiety between July 2001 and June 2002 in a large national managed care database. MAIN OUTCOME MEASURES: Rates of 6-month SSRI adherence were measured by 3 different metrics: length of therapy (LOT), medication possession ratio (MPR), and combined MPR/LOT. Differences in resource utilization for each adherence metric were measured for patients deemed as 1) adherent, 2) nonadherent, 3) therapy changers, and 4) dose titraters. RESULTS: There were 22,947 patients meeting study criteria. Although statistically different, 6-month adherence rates were numerically similar across all methods (LOT, 44.6%; MPR, 43.3%; and MPR/LOT, 42.9%, P < 0.001); approximately 57% of patients were nonadherent to therapy. Regardless of metric, the adherent cohort incurred the lowest yearly medical costs, followed by the nonadherent, titrate, and therapy change cohorts (P < 0.001 between adherent cohort and all other cohorts). The LOT method produced the greatest difference in yearly medical costs between adherent and nonadherent patients (Dollars 511) followed by MPR/LOT (Dollars 432) and MPR (Dollars 423). When antidepressant prescription costs were added to medical costs, patients requiring a therapy change and titrating therapy incurred higher costs than adherent patients, whereas nonadherent and adherent patients incurred similar costs. CONCLUSION: Regardless of adherence metric, approximately 43% of patients were adherent to antidepressant therapy, and adherent patients were associated with the lowest yearly medical costs.
Authors: C Ron Cantrell; Julie L Priest; Christopher L Cook; Jack Fincham; Steven P Burch Journal: Popul Health Manag Date: 2010-12-13 Impact factor: 2.459
Authors: Edward M Gardner; Moises E Maravi; Cornelis Rietmeijer; Arthur J Davidson; William J Burman Journal: Appl Health Econ Health Policy Date: 2008 Impact factor: 2.561