A Cluster Randomised Trial on the Impact of Integrating Early Infant HIV Diagnosis with the Expanded Programme on Immunization on Immunization and HIV Testing Rates in Rural Health Facilities in Southern Zambia

<div><p>Background</p><p>We assessed the integration of early infant HIV diagnosis with the expanded programme for immunization in a rural Zambian setting with the aim of determining whether infant and postpartum maternal HIV testing rates would increase without harming immunization uptake.</p><p>Methods</p><p>In an unblinded, location stratified, cluster randomised controlled trial, 60 facilities in Zambia’s Southern Province were equally allocated to a control group, Simple Intervention group that received a sensitization meeting and the resupply of HIV testing commodities in the event of a stock-out, and a Comprehensive Intervention group that received the Simple Intervention as well as on-site operational support to facilitate the integration of HIV testing services with EPI.</p><p>Findings</p><p>The average change in number of first dose diphtheria, pertussis, and tetanus vaccine (DPT1) provided per month, per facility was approximately 0.86 doses higher [90% confidence interval (CI) -1.40, 3.12] in Comprehensive Intervention facilities compared to the combined average change in the Simple Intervention and control facilities. The interventions resulted in a 16.6% [90% CI: -7%, 46%, P-value = 0.26] and 10% [90% CI: -10%, 36%, P-value = 0.43] greater change in average monthly infant DBS testing compared to control for the Simple and Comprehensive facilities respectively. We also found 15.76 (90% CI: 7.12, 24.41, P-value < 0.01) and 10.93 (90% CI: 1.52, 20.33, P-value = 0.06) additional total maternal re-tests over baseline for the Simple and Comprehensive Facilities respectively.</p><p>Conclusions</p><p>This study provides strong evidence to support Zambia’s policy of integration of HIV testing and EPI services. Actions in line with the interventions, including HIV testing material supply reinforcement, can increase HIV testing rates without harming immunization uptake. In response, Zambia’s Ministry of Health issued a memo to remind health facilities to provide HIV testing at under-five clinics and to include under-five HIV testing as part of district performance assessments.</p><p>Trial Registration</p><p>ClinicalTrials.gov Registration Number: <a href="https://clinicaltrials.gov/ct2/show/study/NCT02479659?term=early+infant+diagnosis+and+HIV+and+Zambia&rank=1" target="_blank">NCT02479659</a></p></div

The average number of infant DBS testing during baseline and intervention periods per facility, by intervention.

<p>The blue bars represent the average number of infant DBS tests per facility in each study arm at baseline. The red bars represent the corresponding average number of infant DBS tests during the six month intervention period.</p

Multivariate Linear Regression Results for the Montly Average Number of DPT1 Doses Comparing Comprehensive Group to Combined Control & Simple Groups.

<p>Multivariate Linear Regression Results for the Montly Average Number of DPT1 Doses Comparing Comprehensive Group to Combined Control & Simple Groups.</p

Linear Regression Results of Intervention Arm on Logged Outcome (Number of DBS Tests per Facility per Month).

<p>Linear Regression Results of Intervention Arm on Logged Outcome (Number of DBS Tests per Facility per Month).</p

Quality improvement intervention to increase adherence to ART prescription policy at HIV treatment clinics in Lusaka, Zambia: A cluster randomized trial

<div><p>Introduction</p><p>In urban areas, crowded HIV treatment facilities with long patient wait times can deter patients from attending their clinical appointments and picking up their medications, ultimately disrupting patient care and compromising patient retention and adherence.</p><p>Methods</p><p>Formative research at eight facilities in Lusaka revealed that only 46% of stable HIV treatment patients were receiving a three-month refill supply of antiretroviral drugs, despite it being national policy for stable adult patients. We designed a quality improvement intervention to improve the operationalization of this policy. We conducted a cluster-randomized controlled trial in sixteen facilities in Lusaka with the primary objective of examining the intervention’s impact on the proportion of stable patients receiving three-month refills. The secondary objective was examining whether the quality improvement intervention reduced facility congestion measured through two proxy indicators: daily volume of clinic visits and average clinic wait times for services.</p><p>Results</p><p>The mean change in the proportion of three-month refills among control facilities from baseline to endline was 10% (from 38% to 48%), compared to a 25% mean change (an increase from 44% to 69%) among intervention facilities. This represents a significant 15% mean difference (95% CI: 2%-29%; <i>P</i> = 0.03) in the change in proportion of patients receiving three-month refills. On average, control facilities had 15 more visits per day in the endline than in the baseline, while intervention facilities had 20 fewer visits per day in endline than in baseline, a mean difference of 35 fewer visits per day (<i>P</i> = 0.1). The change in the mean facility total wait time for intervention facilities dropped 19 minutes between baseline and endline when compared to control facilities (95% CI: -10.2–48.5; <i>P</i> = 0.2).</p><p>Conclusion</p><p>A more patient-centred service delivery schedule of three-month prescription refills for stable patients is viable. We encourage the expansion of this sustainable intervention in Zambia’s urban clinics.</p></div

Summary and baseline characteristics by intervention arm.

<p>* The intervention arms were regressed as indicator variables on each outcome. After the regression, an F-test was used to test for equality between the three evaluation arms. At the time of sampling, all samples with p-values of less than 0.90 for DBS, DPT, and ANC averages were removed from consideration. Since that time, more complete data are available, explaining the 0.89 p-value for the DBS tests at the final sample.</p><p>Summary and baseline characteristics by intervention arm.</p

Multivariate Linear Regression Results for 6 Week Retests and Total Number of Retests.

<p>Multivariate Linear Regression Results for 6 Week Retests and Total Number of Retests.</p