Nancy L Czaicki1, Charles B Holmes, Izukanji Sikazwe, Carolyn Bolton, Theodora Savory, Mwanza Wa Mwanza, Crispin Moyo, Nancy S Padian, Elvin H Geng. 1. aDivision of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, California, USAbCentre for Infectious Disease Research in Zambia, Lusaka, ZambiacJohns Hopkins University School of Medicine, Baltimore, Maryland, USAdMinistry of Health of Zambia, Lusaka, ZambiaeDivision of HIV/AIDS, Department of Medicine, University of California, San Francisco, San Francisco General Hospital, San Francisco, California, USA.
Abstract
OBJECTIVES: The distribution of adherence to antiretroviral therapy (ART) can indicates whether barriers are concentrated or more distributed. We quantified the medication possession ratio (MPR) and characterized the distribution of medication nonpossession in a network of clinics in Zambia to identify 'hotspots' and predictors of poorer adherence. METHODS: We analyzed a population of adults on ART for more than 3 months who made at least one clinic visit between 1 January 2013 and 28 February 2015. Pharmacy refill and clinical information were obtained through the electronic medical record system used in routine care. We constructed a Lorenz curve to visualize the distribution of poor adherence and used a multilevel logistic regression model to examine factors associated with MPR. RESULTS: Among 131 767 patients in 56 clinics [64% women, median age 34 years (interquartile range (IQR) 29-41), median CD4 cell count at ART initiation 351 cells/μl (IQR 220-517)], the median MPR was 85.8% (IQR 70.8-96.8). During months 7-12 on ART, 45.6% of patients had 100% MPR and 10.5% accounted for 50% of medication nonpossession. Across clinics, median MPR ranged from 49.1 to 98.5, and clinic accounted for 12% of the variability in adherence after adjusting for individual and clinic-level characteristics. CONCLUSION: A small fraction of patients account for the majority of days of medication nonpossession. Further characterization of these subpopulations is needed to target interventions. Clinic also accounted for much variability in MPR. Health systems interventions targeting clinic 'hot spots' may represent an efficient use of resources to improve ART adherence.
OBJECTIVES: The distribution of adherence to antiretroviral therapy (ART) can indicates whether barriers are concentrated or more distributed. We quantified the medication possession ratio (MPR) and characterized the distribution of medication nonpossession in a network of clinics in Zambia to identify 'hotspots' and predictors of poorer adherence. METHODS: We analyzed a population of adults on ART for more than 3 months who made at least one clinic visit between 1 January 2013 and 28 February 2015. Pharmacy refill and clinical information were obtained through the electronic medical record system used in routine care. We constructed a Lorenz curve to visualize the distribution of poor adherence and used a multilevel logistic regression model to examine factors associated with MPR. RESULTS: Among 131 767 patients in 56 clinics [64% women, median age 34 years (interquartile range (IQR) 29-41), median CD4 cell count at ART initiation 351 cells/μl (IQR 220-517)], the median MPR was 85.8% (IQR 70.8-96.8). During months 7-12 on ART, 45.6% of patients had 100% MPR and 10.5% accounted for 50% of medication nonpossession. Across clinics, median MPR ranged from 49.1 to 98.5, and clinic accounted for 12% of the variability in adherence after adjusting for individual and clinic-level characteristics. CONCLUSION: A small fraction of patients account for the majority of days of medication nonpossession. Further characterization of these subpopulations is needed to target interventions. Clinic also accounted for much variability in MPR. Health systems interventions targeting clinic 'hot spots' may represent an efficient use of resources to improve ART adherence.
Authors: Kristin M Wall; William Kilembe; Bellington Vwalika; Lisa B Haddad; Naw Htee Khu; Ilene Brill; Udodirim Onwubiko; Elwyn Chomba; Amanda Tichacek; Susan Allen Journal: J Womens Health (Larchmt) Date: 2017-08 Impact factor: 2.681
Authors: Charles B Holmes; Izukanji Sikazwe; Kombatende Sikombe; Ingrid Eshun-Wilson; Nancy Czaicki; Laura K Beres; Njekwa Mukamba; Sandra Simbeza; Carolyn Bolton Moore; Cardinal Hantuba; Peter Mwaba; Caroline Phiri; Nancy Padian; David V Glidden; Elvin Geng Journal: PLoS Med Date: 2018-01-12 Impact factor: 11.069
Authors: Chanda Mwamba; Anjali Sharma; Njekwa Mukamba; Laura Beres; Elvin Geng; Charles B Holmes; Izukanji Sikazwe; Stephanie M Topp Journal: BMJ Glob Health Date: 2018-10-25