Designing mHealth for maternity services in primary health facilities in a low-income setting - Lessons from a partially successful implementation

Abstract

<p><i>Background</i>: Increasing mobile phone ownership, functionality and access to mobile-broad band internet services has triggered growing interest to harness the potential of mobile phone technology to improve health services in low-income settings. The present project aimed at designing an mHealth system that assists midlevel health workers to provide better maternal health care services by automating the data collection and decision-making process. This paper describes the development process and technical aspects of the system considered critical for possible replication. It also highlights key lessons learned and challenges during implementation.</p>

<p><i>Methods</i>: The mHealth system had front-end and back-end components. The front-end component was implemented as a mobile based application while the back-end component was implemented as a web-based application that ran on a central server for data aggregation and report generation. The current mHealth system had four applications; namely, data collection/reporting, electronic health records, decision support, and provider education along the continuum of care including antenatal, delivery and postnatal care. The system was pilot-tested and deployed in selected health centers of North Shewa Zone, Amhara region, Ethiopia.</p>

<p><i>Results</i>: The system was used in 5 health centers since Jan 2014 and later expanded to additional 10 health centers in June 2016 with a total of 5927 electronic forms submitted to the back-end system. The submissions through the mHealth system were slightly lower compared to the actual number of clients who visited those facilities as verified by record reviews. Regarding timeliness, only 11% of the electronic forms were submitted on the day of the client visit, while an additional 17% of the forms were submitted within 10 days of clients’ visit. On average forms were submitted 39 days after the day of clients visit with a range of 0 to 150 days.</p>

<p><i>Conclusions</i>: In conclusion, the study illustrated that an effective mHealth intervention can be developed using an open source platform and local resources. The system impacted key health outcomes and contributed to timely and complete data submission. Lessons learned through the process including success factors and challenges are discussed.