Application of a Multistate Model to Evaluate Visit Burden and Patient Stability to Improve Sustainability of Human Immunodeficiency Virus Treatment in Zambia

Clinical Infectious Diseases MAJOR ARTICLE Application of a Multistate Model to Evaluate Visit Burden and Patient Stability to Improve Sustainability of Human Immunodeficiency Virus Treatment in Zambia Monika Roy,1 Charles Holmes,2,3 Izukanji Sikazwe,2 Thea Savory,2 Mwanza wa Mwanza,2 Carolyn Bolton Moore,2,4 Kafula Mulenga,2 Nancy Czaicki,1 David V. Glidden,5 Nancy Padian,6 and Elvin Geng1 1 Division of HIV/AIDS, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco General Hospital; 2Centre for Infectious Diseases Research in Zambia, Lusaka; 3Johns Hopkins University School of Medicine, Baltimore, Maryland; 4University of Alabama, Birmingham; and 5Department of Epidemiology and Biostatistics, University of California, San Francisco, and 6Division of Epidemiology, University of California Berkeley The global public health community has embraced differentiated service delivery (DSD), a suite of strategies that varies the timing, location, and intensity of services for persons living with human immunodeficiency virus (PLWHIV) as a principle strategy to address challenges in accessing care and to improve the quality of HIV service provision. In the second decade of the global HIV response, a growing proportion of patients considered clinically stable were still being asked to make frequent (often monthly) facility visits at considerable personal cost. These visits also contributed to congestion at clinic facilities, leaving overstretched clinical providers with little time to provide care to those more acutely ill. DSD models involve various strategies to target these stable patients, including increased Received 21 December 2017; editorial decision 23 March 2018; accepted 6 April 2018; published online 7 April, 2018. Correspondence: M. Roy, Division of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco General Hospital, 995 Potrero Ave, Bldg 80, San Francisco, CA 94110 (). Clinical Infectious Diseases®  2018;67(8):1269–77 © The Author(s) 2018. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: . DOI: 10.1093/cid/ciy285 spacing between visits (ie, 3- or 6-month antiretroviral therapy [ART] supply or clinical visits) [1–7], provision of ART in healthcare worker–led [8–14] or community-based peer-led groups [13, 15–21], and individual distribution of medications in the community [2, 13, 22–25]. As DSD models for stable patients gain favor in Africa, data about potential visit burden reduction through application of DSD to stable patients, the rate at which patients become stable after starting treatment, and the durability of clinical stability once achieved can help guide DSD implementation strategies. Existing published data are limited to cross-sectional assessments of DSD eligibility [6] and therefore fail to capture the real-world dynamics of patient stability, yielding potentially inaccurate estimates of efficiency gains and programmatic needs with DSD application. We used data from a network of ART clinics in Zambia to better characterize the incidence, prevalence, and durability of clinical stability according to conventional criteria. Our objectives were, first, to characterize visit volume and appointment frequency to identify visits potentially reducible by application of DSD models to stable patients; second, to understand the Dynamics of Patient Stability in Zambia • CID 2018:67 (15 October) • 1269 Background. Differentiated service delivery (DSD) for human immunodeficiency virus (HIV)–infected persons who are clinically stable on antiretroviral therapy (ART) has been embraced as a solution to decrease access barriers and improve quality of care. However, successful DSD implementation is dependent on understanding the prevalence, incidence, and durability of clinical stability. Methods. We evaluated visit data in a cohort of HIV-infected adults who made at least 1 visit between 1 March 2013 and 28 February 2015 at 56 clinics in Zambia. We described visit frequency and appointment intervals using conventional stability criteria and used a mixed-effects linear regression model to identify predictors of appointment interval. We developed a multistate model to characterize patient stability over time and calculated incidence rates for transition between states. Results. Overall, 167 819 patients made 3 418 018 post–ART initiation visits between 2004 and 2015. Fifty-four percent of visits were pharmacy refill-only visits, and 24% occurred among patients on ART for >6 months and whose current CD4 was >500 cells/ mm3. Median appointment interval at clinician visits was 59 days, and time on ART and current CD4 were not strong predictors of appointment interval. Cumulative incidence of clinical stability was 66.2% at 2 years after enrollment, but transition to instability (31 events per 100 person-years) and lapses in care (41 events per100 person-years) were common. Conclusions. Current facility-based care was characterized by high visit burden due to pharmacy refills and among treatment-experienced patients. Differentiated service delivery models targeted toward stable patients need to be adaptive given that clinical stability was highly transient and lapses in care were common. Keywords. human immunodeficiency virus (HIV); differentiated care; differentiated service delivery; Zambia; sustainability. current system’s ability to differentiate care based on clinical stability by identifying predictors of appointment interval; and third, to determine how quickly patients become stable, for how long they remain stable, and the reasons for being or becoming unstable using a novel multistate modeling approach. METHODS Patients Measurements Sociodemographic and clinical characteristics of patients, including all visit and appointment dates, were obtained from the patient’s electronic medical record (EMR) in the Zambian national data system, SmartCare. Enrollment CD4 cell count was defined as the closest CD4 cell count recorded within 365 days before or 30 days after the initial visit date. Current CD4 count was defined as the closest CD4 count recorded before a given visit date within the previous 12 months. On a given visit to the clinic, patients may have encounters with ≥1 providers (ie, clinicians, pharmacists, or adherence counselors). We categorized visits based on the highest level of healthcare provider seen: a “clinician visit” (with or without a pharmacy encounter), a “pharmacy-only visit” (with or without an adherence counter), or an “adherence-only visit.” Appointment intervals were defined as the time between the visit date and the next scheduled appointment. In instances where patients encountered both the clinician and the pharmacist at a given visit, the earliest of these two appointment dates was used to define the next assigned return to clinic date or combined appointment (...truncated)