OBJECTIVES: To examine the relationship between patient characteristics and medication adherence trajectories for patients with congestive heart failure (CHF). STUDY DESIGN: Historical prospective study. METHODS: We conducted a secondary analysis of data assembled for the Practice Variation and Care Outcomes (PRAVCO) study, which examined patterns of cardiovascular care. We used group based trajectory modeling to define medication adherence trajectories, and then modeled factors associated with belonging to a trajectory group during the 6year period from 2005 to 2010 (n = 10,986). We focused on the use of angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs) for secondary prevention of CHF. RESULTS: Four trajectory groups were optimal in characterizing adherence level patterns: 1) low adherence group, with an initial average adherence rate of 62% that dropped to between 40% and 50%; 2) increasing adherence group, with an initial average adherence rate of 55% that increased to 90%; 3) decreasing adherence group, with an initial average adherence rate above 90% that decreased to 60%; 4) high adherence group, with an average adherence rate consistently above 90%. Age, region, education, smoking, and race were all significantly associated with the likelihood of belonging to a particular trajectory. Nonwhites were less likely to be in the high adherence group, and smoking was more common in the low adherence group (22%) than in the high group (10%); increasing body mass index and Charlson Comorbidity Index (CCI) scores were also associated with being in the low adherence group. CONCLUSIONS: Population characteristics associated with sustained low adherence might be used to target interventions and improve vulnerable patients' prospects of heart health.
OBJECTIVES: To examine the relationship between patient characteristics and medication adherence trajectories for patients with congestive heart failure (CHF). STUDY DESIGN: Historical prospective study. METHODS: We conducted a secondary analysis of data assembled for the Practice Variation and Care Outcomes (PRAVCO) study, which examined patterns of cardiovascular care. We used group based trajectory modeling to define medication adherence trajectories, and then modeled factors associated with belonging to a trajectory group during the 6year period from 2005 to 2010 (n = 10,986). We focused on the use of angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs) for secondary prevention of CHF. RESULTS: Four trajectory groups were optimal in characterizing adherence level patterns: 1) low adherence group, with an initial average adherence rate of 62% that dropped to between 40% and 50%; 2) increasing adherence group, with an initial average adherence rate of 55% that increased to 90%; 3) decreasing adherence group, with an initial average adherence rate above 90% that decreased to 60%; 4) high adherence group, with an average adherence rate consistently above 90%. Age, region, education, smoking, and race were all significantly associated with the likelihood of belonging to a particular trajectory. Nonwhites were less likely to be in the high adherence group, and smoking was more common in the low adherence group (22%) than in the high group (10%); increasing body mass index and Charlson Comorbidity Index (CCI) scores were also associated with being in the low adherence group. CONCLUSIONS: Population characteristics associated with sustained low adherence might be used to target interventions and improve vulnerable patients' prospects of heart health.
Authors: Candace H Feldman; Jamie Collins; Zhi Zhang; S V Subramanian; Daniel H Solomon; Ichiro Kawachi; Karen H Costenbader Journal: Semin Arthritis Rheum Date: 2018-01-08 Impact factor: 5.532
Authors: Rutugandha Paranjpe; Michael L Johnson; Ekere J Essien; Jamie C Barner; Omar Serna; Esteban Gallardo; Zahra Majd; Marc L Fleming; Nancy Ordonez; Marcia M Holstad; Susan M Abughosh Journal: Patient Prefer Adherence Date: 2020-10-13 Impact factor: 2.711
Authors: Deborah A Taira; Brendan K Seto; James W Davis; Todd B Seto; Doug Landsittel; Wesley K Sumida Journal: J Pharm Health Serv Res Date: 2017-08-07