ArticleBMC medical informatics and decision making2018
Designing mHealth for maternity services in primary health facilities in a low-income setting - lessons from a partially successful implementation.
Article in BMC medical informatics and decision making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The mHealth clinical decision-making tools for maternal and perinatal health care in Sub-Saharan Africa: A systematic review.PloS one · 2025Pooled it
- The effect of an interactive mobile health intervention to improve community-based essential neonatal care practices among postpartum women in northeast Ethiopia: a cluster randomized controlled trial.International health · 2025Trial
- Trial
- Challenges for a Maternal-Care Health Recommender System in Indonesia: Formative Preimplementation Qualitative Study.JMIR formative research · 2026Article
- Development, Implementation, and Usability Evaluation of the CANMI App to Monitor the Quality of Maternal and Child Nutrition Care in Primary Health Units: Mixed Methods Pilot Study.JMIR formative research · 2025Article
- Implementation research logic model in the design and execution of eHealth innovations for maternal and newborn healthcare in Ethiopia.Health research policy and systems · 2025Article
- Spatial patterns and predictors of missing key contents of care during prenatal visits in Ethiopia: Spatial and multilevel analyses.PloS one · 2024Article
- Patient Satisfaction with the Implementation of Telehealth in Ambulatory Care during the COVID-19 Pandemic: A Single Institution Experience.BioMed research international · 2024Article
- Healthcare Workers' Perspectives of mHealth Adoption Factors in the Developing World: Scoping Review.International journal of environmental research and public health · 2023Article
- Tailoring Mobile Data Collection for Intervention Research in a Challenging Context: Development and Implementation in the Malakit Study.JMIR formative research · 2022Article
- Article
- Digital Solutions for Community and Primary Health Workers: Lessons From Implementations in Africa.Frontiers in digital health · 2022Review
- The potential use of digital health technologies in the African context: a systematic review of evidence from Ethiopia.NPJ digital medicine · 2021Review
- Implementation science in maternity care: a scoping review.Implementation science : IS · 2021Article
- An Exploratory Study of Current Sources of Adolescent Sexual and Reproductive Health Information in Kenya and Their Limitations: Are Mobile Phone Technologies the Answer?International journal of sexual health : official journal of the World Association for Sexual Health · 2021Article
- Effectiveness of a mobile phone application to increase access to sexual and reproductive health information, goods, and services among university students in Uganda: a randomized controlled trial.Contraception and reproductive medicine · 2020Article
- Barriers to Sustainable Telemedicine Implementation in Ethiopia: A Systematic Review.Telemedicine reports · 2020Review
- Addressing comprehensive primary healthcare in Gujarat through mHealth intervention: Early implementation experience with TeCHO+ programme.Journal of family medicine and primary care · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIncreasing 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.
methodsThe 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.
resultsThe 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.
conclusionsIn 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.