MOPED538

Title

Achieving the “third 90” in western Kenya: A quality improvement collaborative (QIC) to improve viral load utilization at 30 health facilities in Siaya County, Kenya

Presenter

Gillian Dougherty

Authors

G. Dougherty¹, D. Achwoka², S. Akoth³, R. Boccanera⁴, M. Hawken³, M. Kimani⁵, I. Leting³, C. Madevu-Matson⁶, R. Mutei³, L. Nyaga⁵, C. Onyango³, C. Ouma⁷, I. Rondinelli⁶, P. Rumunyu⁸, F. Tsiouris⁶, A. Wakoli³, L. Walker⁹, M. Rabkin⁶

Institutions

¹Columbia University, Mailman School of Public Health, New York, United States, ²Centers for Disease Control and Prevention (CDC), Nairobi, Kenya, ³ICAP at Columbia University, Nairobi, Kenya, ⁴Health and Human Services Department, Bethesda, United States, ⁵NASCOP KENYA, Nairobi, Kenya, ⁶ICAP at Columbia University, Mailman School of Public Health, New York, United States, ⁷ICAP at Columbia University, Mailman School of Public Health, Nairobi, Kenya, ⁸Center for Health Solutions, Nairobi, Kenya, ⁹ICAP at Columbia University, Mailman School of Public Health, New York, United Kingdom

Background: Scaling up routine HIV viral load testing (VLT) is a priority for Kenya''s National AIDS Control Program (NASCOP), which has successfully expanded VLT coverage with the support of partners. National guidelines recommend that clients on antiretroviral therapy (ART) with unsuppressed VL(UVL) defined as > 1,000 copies/mL -receive enhanced adherence counseling (EAC) at monthly intervals for three months, followed by repeat VLT to guide ART management. Despite rollout of national policies, guidelines and training, VL utilization has been suboptimal.
Methods: In collaboration with NASCOP, HRSA and CDC, ICAP at Columbia University designed and implemented a QIC at 30 health facilities in Siaya County, Kenya, from April 2017 to May 2018 to optimize VL utilization (timely EAC, repeat VLT, and appropriate ART management) for clients with UVL. Key indicators were collected at baseline and throughout QIC implementation, which included training on QI methods and VL results management for 196 health care workers followed by monthly QI coaching visits and quarterly learning session workshops. Each facility QI team identified contextually appropriate interventions; used QI methods and tools to conduct rapid tests of change; and analyzed monthly progress using run charts. Facility teams presented on their performance and shared best practices at quarterly learning sessions.
Results: QI teams tested interventions over 14 months including: test result management, improved staff and client education, staffing modifications, workflow process modifications, commodity management, documentation, and data quality improvements. In aggregate, completion of three EAC sessions within 4 months of test results improved from 18% at baseline to 80% during QIC implementation. On average, it took facilities 2.6 months (median 2, range 0-10) to achieve 90% EAC completion and this performance was sustained for 8 out of 14 months. In addition, appropriate switching to second-line ART for clients with persistent UVL improved from 35% to 78%.
Conclusions: QIC interventions improved VL results utilization by helping facilities generate local innovations to ensure timely identification of UVL, delivery of EAC sessions, and switch to second-line ART when indicated. In addition to building QI capacity and improving targeted outcomes, the VL QIC validated a “change package” of successful initiatives that has been disseminated within Kenya.

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