Using a Decision-Support Smartphone application to enhance Community Health Volunteers’ effectiveness in reducing Maternal complications and reducing Newborn Deaths in the informal settlements of Nairobi, Kenya, Community Health Volunteers’ Decision Support

Improving maternal and newborn survival remain major aspirations for many countries in the global south. Slum settlements, a result of rapid urbanization 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 health care facilities with ability to provide adequate care. In this study we specifically plan to 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.

Objectives:
To develop and validate a decision-support algorithm within an m-health solution in improving maternal and newborn health outcomes in the urban slums of Kamukunji sub-County in Nairobi, Kenya.

Study Design: Quasi-experimental, difference in differences, with a control.
We propose to implement an innovative, m-health application known as mPAMANECH which uses dynamic mobile phone and web-portal solutions, to enable Community Health Volunteers (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, trained over a five-day period, conduct weekly home visits and make decisions (counsel, treat, refer) from memory or using unwieldy manual tools, and thus prone to making errors. mPAMANECH will have an in-built algorithm that makes it easier, faster and more likely for CHVs to make the right management decision. We will work with a network of community units-CUs and selected CHVs and maternity centres to pilot test the tool.