OBJECTIVE: Adherence to combination antiretroviral therapy is critical for clinical and virologic success in HIV-infected patients. To combat poor adherence, clinicians must identify nonadherent patients so they can implement interventions. However, little is known about the accuracy of these assessments. We sought to describe the accuracy of clinicians' estimates of patients' adherence to combination antiretroviral therapy. SETTING: Public HIV clinic. DESIGN: Prospective cohort study. During visits, we asked clinicians (nurse practitioners, residents and fellows, and their supervising attending physicians) to estimate the percentage of antiretroviral medication taken by patients over the last 4 weeks and predicted adherence over the next 4 weeks. Adherence was measured using electronic monitoring devices, pill counts, and self-reports, which were combined into a composite adherence measure. PATIENTS AND PARTICIPANTS: Clinicians estimated 464 episodes of adherence in 82 patients. RESULTS: Among the 464 adherence estimates, 264 (57%) were made by principal care providers (31% by nurse practitioners, 15% by fellows, 6% by residents, and 5% by staff physicians) and 200 (43%) by supervising attending physicians. Clinicians' overestimated measured adherence by 8.9% on average (86.2% vs 77.3%). Greater clinician inaccuracy in adherence prediction was independently associated with higher CD4 count nadir (1.8% greater inaccuracy for every 100 CD4 cells, P=.005), younger patient age (3.7% greater inaccuracy for each decade of age, P=.02), and visit number (P=.02). Sensitivity of detecting nonadherent patients was poor (24% to 62%, depending on nonadherence cutoff). The positive predictive value of identifying a patient as nonadherent was 76% to 83%. CONCLUSIONS: Clinicians tend to overestimate medication adherence, inadequately detect poor adherence, and may therefore miss important opportunities to intervene to improve antiretroviral adherence.
OBJECTIVE: Adherence to combination antiretroviral therapy is critical for clinical and virologic success in HIV-infected patients. To combat poor adherence, clinicians must identify nonadherent patients so they can implement interventions. However, little is known about the accuracy of these assessments. We sought to describe the accuracy of clinicians' estimates of patients' adherence to combination antiretroviral therapy. SETTING: Public HIV clinic. DESIGN: Prospective cohort study. During visits, we asked clinicians (nurse practitioners, residents and fellows, and their supervising attending physicians) to estimate the percentage of antiretroviral medication taken by patients over the last 4 weeks and predicted adherence over the next 4 weeks. Adherence was measured using electronic monitoring devices, pill counts, and self-reports, which were combined into a composite adherence measure. PATIENTS AND PARTICIPANTS: Clinicians estimated 464 episodes of adherence in 82 patients. RESULTS: Among the 464 adherence estimates, 264 (57%) were made by principal care providers (31% by nurse practitioners, 15% by fellows, 6% by residents, and 5% by staff physicians) and 200 (43%) by supervising attending physicians. Clinicians' overestimated measured adherence by 8.9% on average (86.2% vs 77.3%). Greater clinician inaccuracy in adherence prediction was independently associated with higher CD4 count nadir (1.8% greater inaccuracy for every 100 CD4 cells, P=.005), younger patient age (3.7% greater inaccuracy for each decade of age, P=.02), and visit number (P=.02). Sensitivity of detecting nonadherent patients was poor (24% to 62%, depending on nonadherence cutoff). The positive predictive value of identifying a patient as nonadherent was 76% to 83%. CONCLUSIONS: Clinicians tend to overestimate medication adherence, inadequately detect poor adherence, and may therefore miss important opportunities to intervene to improve antiretroviral adherence.
Authors: H Liu; C E Golin; L G Miller; R D Hays; C K Beck; S Sanandaji; J Christian; T Maldonado; D Duran; A H Kaplan; N S Wenger Journal: Ann Intern Med Date: 2001-05-15 Impact factor: 25.391
Authors: C C Carpenter; D A Cooper; M A Fischl; J M Gatell; B G Gazzard; S M Hammer; M S Hirsch; D M Jacobsen; D A Katzenstein; J S Montaner; D D Richman; M S Saag; M Schechter; R T Schooley; M A Thompson; S Vella; P G Yeni; P A Volberding Journal: JAMA Date: 2000-01-19 Impact factor: 56.272
Authors: A Tuldrà; C R Fumaz; M J Ferrer; R Bayés; A Arnó; M Balagué; A Bonjoch; A Jou; E Negredo; R Paredes; L Ruiz; J Romeu; G Sirera; C Tural; D Burger; B Clotet Journal: J Acquir Immune Defic Syndr Date: 2000-11-01 Impact factor: 3.731
Authors: Michael J Stirratt; Jacqueline Dunbar-Jacob; Heidi M Crane; Jane M Simoni; Susan Czajkowski; Marisa E Hilliard; James E Aikens; Christine M Hunter; Dawn I Velligan; Kristen Huntley; Gbenga Ogedegbe; Cynthia S Rand; Eleanor Schron; Wendy J Nilsen Journal: Transl Behav Med Date: 2015-07-09 Impact factor: 3.046
Authors: Mallory O Johnson; Timothy R Elliott; Torsten B Neilands; Stephen F Morin; Margaret A Chesney Journal: Health Psychol Date: 2006-05 Impact factor: 4.267
Authors: Becky L Genberg; Yoojin Lee; William H Rogers; Cynthia Willey; Ira B Wilson Journal: AIDS Patient Care STDS Date: 2013-10 Impact factor: 5.078