 ePOCT+ and the medAL-suite: Development of an electronic clinical decision support algorithm and digital platform for pediatric outpatients in low- and middle-income countriesRainer Tan, Ludovico Cobuccio, Fenella Beynon, Gillian A Levine, Nina Vaezipour, Lameck Bonaventure Luwanda, Chacha Mangu, Alan Vonlanthen, Olga De Santis, Nahya Salim, Karim Manji, Helga Naburi, Lulu Chirande, Lena Matata, Method Bulongeleje, Robert Moshiro, Andolo Miheso, Peter Arimi, Ousmane Ndiaye, Moctar Faye, Aliou Thiongane, Shally Awasthi, Kovid Sharma, Gaurav Kumar, Josephine Van De Maat, Alexandra Kulinkina, Victor Rwandarwacu, Théophile Dusengumuremyi, John Baptist Nkuranga, Emmanuel Rusingiza, Lisine Tuyisenge, Mary-Anne Hartley, Vincent Faivre, Julien Thabard, Kristina Keitel and Valérie D’Acremont PLOS Digital Health, 2023, vol. 2, issue 1, 1-17 Abstract: Electronic clinical decision support algorithms (CDSAs) have been developed to address high childhood mortality and inappropriate antibiotic prescription by helping clinicians adhere to guidelines. Previously identified challenges of CDSAs include their limited scope, usability, and outdated clinical content. To address these challenges we developed ePOCT+, a CDSA for the care of pediatric outpatients in low- and middle-income settings, and the medical algorithm suite (medAL-suite), a software for the creation and execution of CDSAs. Following the principles of digital development, we aim to describe the process and lessons learnt from the development of ePOCT+ and the medAL-suite. In particular, this work outlines the systematic integrative development process in the design and implementation of these tools required to meet the needs of clinicians to improve uptake and quality of care. We considered the feasibility, acceptability and reliability of clinical signs and symptoms, as well as the diagnostic and prognostic performance of predictors. To assure clinical validity, and appropriateness for the country of implementation the algorithm underwent numerous reviews by clinical experts and health authorities from the implementing countries. The digitalization process involved the creation of medAL-creator, a digital platform which allows clinicians without IT programming skills to easily create the algorithms, and medAL-reader the mobile health (mHealth) application used by clinicians during the consultation. Extensive feasibility tests were done with feedback from end-users of multiple countries to improve the clinical algorithm and medAL-reader software. We hope that the development framework used for developing ePOCT+ will help support the development of other CDSAs, and that the open-source medAL-suite will enable others to easily and independently implement them. Further clinical validation studies are underway in Tanzania, Rwanda, Kenya, Senegal, and India.Author summary: In accordance with the principles of digital development we describe the process and lessons learnt from the development of ePOCT+, a clinical decision support algorithm (CDSA), and medAL-suite, a software, to program and implement CDSAs. The clinical algorithm was adapted from previous CDSAs in order to address challenges in regards to the limited scope of illnesses and patient population addressed, the ease of use, and limited performance of specific algorithms. Clinical algorithms were adapted and improved based on considerations of what symptoms and signs would be appropriate for primary care health workers, and how well these clinical elements predic a particular disease or severe outcome. We hope that by sharing our multi-stakeholder approach to the development of ePOCT+, it can help others in the development of other CDSAs. The medAL-creator software was developed to allow clinicians without IT programming experience to program the clinical algorithm using a drag-and-drop interface, intended to allow a wider range of health authorities and implementers to develop and adapt their own CDSA. The medAL-reader application, deploys the algorithm from medAL-creator to end-users following the usual healthcare processes within a consultation. Date: 2023 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pdig00:0000170 DOI: 10.1371/journal.pdig.0000170 Access Statistics for this article More articles in PLOS Digital Health from Public Library of Science |
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