Article Text
Abstract
Health workers in low-resource settings often lack the support and tools to follow evidence-based clinical recommendations for diagnosing, treating and managing sick patients. Digital technologies, by combining patient health information and point-of-care diagnostics with evidence-based clinical protocols, can help improve the quality of care and the rational use of resources, and save patient lives. A growing number of electronic clinical decision support algorithms (CDSAs) on mobile devices are being developed and piloted without evidence of safety or impact. Here, we present a target product profile (TPP) for CDSAs aimed at guiding preventive or curative consultations in low-resource settings. This document will help align developer and implementer processes and product specifications with the needs of end users, in terms of quality, safety, performance and operational functionality. To identify the characteristics of CDSAs, a multidisciplinary group of experts (academia, industry and policy makers) with expertise in diagnostic and CDSA development and implementation in low-income and middle-income countries were convened to discuss a draft TPP. The TPP was finalised through a Delphi process to facilitate consensus building. An agreement greater than 75% was reached for all 40 TPP characteristics. In general, experts were in overwhelming agreement that, given that CDSAs provide patient management recommendations, the underlying clinical algorithms should be human-interpretable and evidence-based. Whenever possible, the algorithm’s patient management output should take into account pretest disease probabilities and likelihood ratios of clinical and diagnostic predictors. In addition, validation processes should at a minimum show that CDSAs are implementing faithfully the evidence they are based on, and ideally the impact on patient health outcomes. In terms of operational needs, CDSAs should be designed to fit within clinic workflows and function in connectivity-challenged and high-volume settings. Data collected through the tool should conform to local patient privacy regulations and international data standards.
- diagnostics and tools
- child health
- public health
- treatment
- health systems
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Footnotes
Handling editor Soumitra S Bhuyan
Contributors KGP and SD conceived the study. KGP generated the methodology, designed the survey and analysed the data. KGP produced the first draft of the paper. CR-A, VD’A, RS, FGM and SD provided edits and comments to the first draft. All authors reviewed and approved the final version of the manuscript.
Funding This work was funded by the Fondation Botnar and supported by the Global Antimicrobial Resistance Innovation Fund (GAMRIF), a UK aid programme. The funders had no role in the study design, data collection and analysis, or preparation of the manuscript.
Competing interests VD’A reports grants from Fondation Botnar, during the conduct of the study. In addition, VD’A has a patent free licence on a CDSA called ALMANACH.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.