The role of a decision-support smartphone application in enhancing community health volunteers’ effectiveness to improve maternal and newborn outcomes in Nairobi, Kenya: quasi-experimental research protocol

Abstract

IntroductionImproving maternal and newborn survival remains major aspirations for many countries in the Global South. Slum settlements, a result of rapid urbanisation in many developing countries including Kenya, exhibit high levels of maternal and neonatal mortality. There are limited referral mechanisms for sick neonates and their mothers from the community to healthcare facilities with ability to provide adequate care. In this study, we specifically plan to develop and assess the added value of having community health volunteers (CHVs) use smartphones to identify and track mothers and children in a bid to reduce pregnancy-related complications and newborn deaths in the urban slums of Kamukunji subcounty in Nairobi, Kenya.Methods and analysisThis is a quasi-experimental study. We are implementing an innovative, mHealth application known as mobile Partnership for Maternal, Newborn and Child Health (mPAMANECH) which uses dynamic mobile phone and web-portal solutions to enable CHVs make timely decisions on the best course of action in their management of mothers and newborns at community level. The application is based on existing guidelines and protocols in use by CHVs. Currently, CHVs conduct weekly home visits and make decisions from memory or using unwieldy manual tools, and thus prone to making errors. mPAMANECH has an in-built algorithm that makes it easier, faster and more likely for CHVs to make the right management decision. We are working with a network of selected CHVs and maternity centres to pilot test the tool. To measure the impact of the intervention, baseline and end-line surveys will be conducted. Data will be obtained through qualitative and quantitative methods.Ethics and disseminationEthical approval for the study was obtained from the African Medical Research Foundation. Key messages from the results will be packaged and disseminated through meetings, conference presentations, reports, fact sheets and academic publications to facilitate uptake by policy-makers.

Barriers to vaccine uptake in the fishing and island communities of Uganda: a qualitative study

“…Because VHTs would have mobilised caregivers and the health workers would know how many vaccines, by type are required, wait time will be reduced. The mobile application is a dynamic solution that allows a direct connection between households, VHTs, and health facilities and two-way information flow for the benefit of the client [11]. As such, data is accessible (to authorized caregivers) at different levels of the continuum of care.…”

“…To respond to vaccine uptake and utilisation challenges, a specialized package of interventions is being run for island and landing sites residents, using an existing mobile health application developed to support community health workers [11]. In the current intervention, community health workers (village health teams-VHTs) use the application to register pregnant women and those with children under five in order to connect them to health workers and a subsidized boat taxi service manned by trained boat riders.…”

“…The ultimate goal of this set of interventions is to reduce the vaccine client waiting time and cost of seeking services and improve timeliness of vaccination and coverage among islands and fishing communities. The program is premised on documented successes of similar programs in LMICs including in neighbouring Tanzania (11,12).…”

Challenges and prospects for implementation of community health volunteers’ digital health solutions in Kenya: a qualitative study

“…The CUs were purposively selected. The selection was guided by the sub-county health management team based on the CUs with poor maternal and child indicators and hence would bene t from the intervention [24]. The project pre-requisite requirements were all CHVs to have undergone basic community health strategy, and MNCH technical training; the latter includes danger signs during pregnancy, new-born and postpartum period.…”

“…Building on lessons learned across SSA and with the aim of strengthen community health information and referral system at the community level in Kenya. We therefore developed an innovative digital application [19] that was also in response to a speci c call for innovations to improve maternal and newborn wellbeing and survival in six counties identi ed as having the worst maternal and newborn health indicators; Bungoma, Garissa, Homa Bay, Kakamega, Turkana and Nairobi City [20] Within Nairobi, informal settlements (slums) were identi ed as an area of focus given that they, compared to other areas of the city, have the very high maternal, newborn and child mortality rates [21]. The work was further informed by the government's call to harness the role of digital technologies in health, as highlighted above [22].…”