Abstract
Over the last ten years there has been a proliferation of mHealth solutions to support patient diagnosis and treatment. Coupled with this, increased attention and resources have been attributed to the development of technologies to improve patient health care outcomes in low resource settings. Most significantly, it is the development of highly extensible, portable and scalable technologies which have received the most attention. As part of an mHealth intervention in Malawi Africa, an agnostic clinical guideline decision-support rule engine has been developed which uses classification and treatment rules for assessing a sick child defined in XML; namely, Integrated Management of Childhood Illness (IMCI) and Community Case Management (CCM). Using a two-phased approach, 1) the rules underpinning the cloud-based mobile eCCM application were devised based on the widely accepted WHO/UNICEF paper based guidelines and 2) subsequently validated and extended through a user workshop conducted in Malawi, Africa.
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Connor, Y.O., Sullivan, T.O., Gallagher, J., Heavin, C., Donoghue, J.O. (2014). Developing eXtensible mHealth Solutions for Low Resource Settings. In: Prasath, R., O’Reilly, P., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8891. Springer, Cham. https://doi.org/10.1007/978-3-319-13817-6_35
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DOI: https://doi.org/10.1007/978-3-319-13817-6_35
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