Anjuli Wagner
Nominated From: University of Washington
Research Site: Kenya
Research Area: Infectious Disease
Primary Mentor: Grace John-Stewart
Research Project
Optimizing pediatric HIV testing using a systems analysis and improvement approach (SAIA)
UNAIDS has set ambitious 90-90-90 targets for HIV: 90% of HIV-infected people will know their status, 90% linked to care, and 90% virally suppressed [1]. Children experience severe deficits in HIV testing and treatment [2]; in Kenya, nearly 60% of HIV-infected children are undiagnosed and just 31% are on treatment [3]. In the absence of antiretroviral treatment (ART), children with HIV experience high mortality—50% die before their second birthday [4]. Treatment dramatically reduces mortality [5]; however, the benefits of ART are limited when treatment is deferred until children are symptomatic with HIV [6, 7]. It is critical to scale up strategies for pediatric HIV testing prior to symptomatic illness.
Children born before the scale up of PMTCT programs, and children who continue to slip through the cracks in the PMTCT cascade remain untested and at risk for severe illness and death. There is an absence of scaled systems to routinely test these children prior to symptomatic illness [8]. Targeted HIV testing for children of HIV-infected adults in care is an efficient, evidence-based strategy for case detection, identifying a high prevalence of pediatric HIV [8]. Yet, programmatic scale-up of this targeted strategy remains low; over half the children with HIV-infected parents in Kenya have never been tested for HIV [3]. There is an absence of tested interventions to improve the scale and performance of pediatric HIV testing strategies.
The pediatric HIV testing and care cascade is similar to the PMTCT cascade; systems interventions that have been effective in reducing PMTCT drop-off may be applicable. Translating and testing the application of these previously developed interventions to new cascades is an efficient approach to innovation. Industrial and systems engineering have developed robust methods for systems optimization; cascade flow analysis, process mapping, and continuous quality improvement provide flexible tools for locally-informed changes for systems optimization.
Pediatric HIV testing in Kenya currently has time-bound resources, political will, and evidence-based guidance for case detection, but no proven interventions for achieving scale & optimizing delivery of services. PEPFAR and the Global Fund have committed time-bound funds to pediatric case detection through the Accelerating Children’s HIV/AIDS Treatment Initiative (ACT) [9]. The National AIDS and STI Control Programme (NASCOP) within the Ministry of Health in Kenya is currently conducting a rapid results initiative (RRI) focused on pediatric and adolescent HIV case detection. There are several evidence-based practices for efficient pediatric case detection being considered for adoption by NASCOP [10, 11](personal communication). However, there are no tested interventions for bringing these interventions to scale and optimizing their performance.
The Systems Analysis and Improvement Approach (SAIA) trial (R01, PI: Sherr) tested a 5-step approach to reduce PMTCT cascade drop off, which was effective in increasing ARV uptake in pregnancy in Kenya (Rustagi, manuscript in preparation). The Counseling and Testing for Children at Home (CATCH) study (R21, PI: John-Stewart) tested targeted pediatric HIV testing for the children of HIV-infected adults in care and found it to be efficient for case detection, but with low uptake. Applying the SAIA approach for systems optimization to the CATCH model provides an opportunity to increase the scale and reach of targeted pediatric testing. If found to
be effective for pediatric HIV testing, the SAIA approach represents a flexible, and locally-adaptable intervention to address systems-level barriers to optimize pediatric HIV testing and care, reducing pediatric morbidity and mortality and promoting long-term growth and development.
Specific Aims:
Aim 1: To determine facility-level factors associated with high and low pediatric testing rates at facilities throughout Kenya, we will compare commodity procurement, facility volume and location, human resources, information systems, and management between facilities with high rates and those with low rates of pediatric HIV testing.
Aim 2: To adapt and pilot the SAIA 5-step systems analysis and improvement approach to increase the rate of pediatric HIV testing. We will adapt the SAIA cascade analysis tool, process mapping, and iterative quality improvement tools and approach to be specific to pediatric HIV testing in a model where children of HIV-infected adults in care are targeted for testing. We will pilot the SAIA intervention to pediatric HIV testing in three low-performing clinics in Kenya to determine acceptability and feasibility, but not efficacy.
Mentors
- Grace John-Stewart, University of Washington
- Kenneth Sherr, University of Washington
- Peter Cherutich, Kenyan Ministry of Health
Publications
