Monitoring the transition to new antiretroviral treatment regimens through an enhanced data system in Kenya.

BACKGROUND: While the scale-up of HIV services has improved national health management information systems (HMIS), there remain challenges in using routine data to guide the introduction of optimized antiretroviral (ARV) drugs. METHODS: Building on the recent enhancements to the HMIS in Kenya and coinciding with the introduction of a new ARV regimen, tenofovir+lamivudine+dolutegravir (TLD), we developed and implemented an enhanced data system (EDS) to improve availability of safety and efficacy data among people living with HIV (PLHIV) in Kenya. Using data from one health facility, we showcase how the EDS can be used to monitor ARV transition and identify missed opportunities to transition eligible patients to optimized regimes. RESULTS: The EDS was designed to create a comprehensive PLHIV database by triangulating patient-level data from the EMR, the pharmacy ARV dispensing tool (ADT) and HIV viral load (VL) databases. On a monthly basis, the database is de-identified and uploaded into a national data warehouse, with interactive dashboards. Using the EDS, we determined that of the 5,500 PLHIV ≥15 years on first-line ART at one facility, 4,233 (77%) had transitioned to optimized ARVs. Of the 1,267 still on legacy regimens, 459 (36%) were determined to be eligible and prioritized to switch. CONCLUSIONS: This project illustrates how enhancements to the national HMIS can facilitate the use of routine patient-level data to monitor the transition to new ARVs and inform the national HIV response.

Implementation of a comprehensive program including psycho-social and treatment literacy activities to improve adherence to HIV care and treatment for a pediatric population in Kenya.

BACKGROUND: To achieve good clinical outcomes with HAART, patient adherence to treatment and care is a key factor. Since the literature on how to care for pediatric HIV patients is limited, we describe here adherence interventions implemented in our comprehensive care program in a resource-limited setting in Kenya. METHODS: We based our program on factors reported to influence adherence to HIV care and treatment. We describe, in detail, our program with respect to how we adapted our clinical settings, implemented psycho-social support activities for children and their caregivers and developed treatment literacy for children and teenagers living with HIV/AIDS. RESULTS: This paper focused on the details of the program, with the treatment outcomes as secondary. However, our program appeared to have been effective; for 648 children under 15 years of age who were started on HAART, the Kaplan-Meier mortality survival estimate was 95.27% (95%CI 93.16-96.74) at 12 months after the time of initiation of HAART. CONCLUSION: Our model of pediatric HIV/AIDS care, focused on a child-centered approach with inclusion of caregivers and extended family, addressed the main factors influencing treatment adherence. It appeared to produce good results and is replicable in resource-limited settings.

Rates and Predictors of Non-Adherence to Antiretroviral Therapy among HIV-Positive Individuals in Kenya: Results from the Second Kenya AIDS Indicator Survey, 2012.

INTRODUCTION: Understanding the levels and associated factors of non-adherence to antiretroviral therapy (ART) is crucial in designing interventions to improve adherence and health outcomes of ART. We assessed non-adherence to ART among HIV-infected persons reporting ART use in a nationally representative survey in Kenya. METHODS: The Kenya AIDS Indicator Survey 2012 was a population-based, household survey of persons aged 18 months-64 years conducted in 2012-2013. Self-reported information was collected on demographics, sexual behaviour, HIV status, and ART use. Blood was collected for HIV testing, and if HIV infected, CD4 and viral load testing. HIV-positive specimens were tested for the presence of antiretroviral (ARV) drugs using a qualitative ARV assay using liquid chromatography-tandem mass spectrometry. HIV-positive persons who reported receiving ART but did not have the ARV biomarker present were defined as being non-adherent to their ARV medication. We restricted our analysis to HIV-infected persons aged 15-64 years who reported receiving ART and had laboratory-confirmed results from ARV testing. Multivariate logistic regression was used to identify variables associated with non-adherence. RESULTS: A total of 648 (5.6%; CI 4.9-6.3) tested HIV-positive of whom 559 (86.3%) had sufficient volume of blood to be tested for ARV drugs. Of those, 271 (47.7%; CI 41.8-53.6) self-reported HIV-positive status during the interview and 186 (69.1%; CI 62.2-76.0) of those reported taking ART. The ARV biomarker was absent in 18 of 186 individuals (9.4%; CI 4.9-13.8) who thus were defined as being non-adherent to ART. Non-adherence was associated with being aged 15-29 years (AOR 8.39; CI 2.26-31.22, p = 0.002) compared to aged 30-64 years, rural residence (AOR 5.87; CI 1.39-25.61, p = 0.016) compared with urban residence and taking recreational drugs in the past 30 days (AOR 5.89; CI 1.30-26.70, p = 0.022). CONCLUSION: Overall, less than 10% of Kenyans aged 15-64 years on ART were not adhering to their HIV medication, highlighting the success of the Kenyan national ART program. Our findings, however, point to the need for targeted interventions particularly for young persons, those in rural areas to improve adherence outcomes, as well as delivery of treatment programs that include psychosocial support as a preventative measure to minimize substance abuse and the risk of treatment failure.

HIV with non-communicable diseases in primary care in Kibera, Nairobi, Kenya: characteristics and outcomes 2010-2013.

BACKGROUND: Antiretroviral therapy (ART) has increased the life expectancy of people living with HIV (PLHIV); HIV is now considered a chronic disease. Non-communicable diseases (NCDs) and HIV care were integrated into primary care clinics operated within the informal settlement of Kibera, Nairobi, Kenya. We describe early cohort outcomes among PLHIV and HIV-negative patients, both of whom had NCDs. METHODS: A retrospective analysis was performed of routinely collected clinic data from January 2010 to June 2013. All patients >14 years with hypertension and/or diabetes were included. RESULTS: Of 2206 patients included in the analysis, 210 (9.5%) were PLHIV. Median age at enrollment in the NCD program was 43 years for PLHIV and 49 years for HIV-negative patients (p<0.0001). The median duration of follow up was 1.4 (IQR 0.7-2.1) and 1.0 (IQR 0.4-1.8) years for PLHIV and HIV-negative patients, respectively (p=0.003). Among patients with hypertension, blood pressure outcomes were similar, and for those with diabetes, outcomes for HbA1c, fasting glucose and cholesterol were not significantly different between the two groups. The frequency of chronic kidney disease (CKD) was 12% overall. Median age for PLHIV and CKD was 50 vs 55 years for those without HIV (p=0.005). CONCLUSIONS: In this early comparison of PLHIV and HIV-negative patients with NCDs, there were significant differences in age at diagnosis but both groups responded similarly to treatment. This study suggests that integrating NCD care for PLHIV along with HIV-negative patients is feasible and achieves similar results.