ArticleJMIR research protocols2022
Investigating the Potential for Clinical Decision Support in Sub-Saharan Africa With AFYA (Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania): Protocol for a Prospective, Observational Pilot Study.
Article in JMIR research protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04958577 (Clinic Waiting Room-based Pilot of Swahili Language Artificial Intelligence-driven Symptom Assessments in Primary Health Care Facilities, Dar es Salaam, Tanzania), which is not on this map. Cited by 3 papers.
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Clinic Waiting Room-based Pilot of Swahili Language Artificial Intelligence-driven Symptom Assessments in Primary Health Care Facilities, Dar es Salaam, Tanzania
Who cites it
3 citing papers in PubMed.
- Natural Language Processing Technologies for Public Health in Africa: Scoping Review.Journal of medical Internet research · 2025Article
- Discovering Subgroups of Children With High Mortality in Urban Guinea-Bissau: Exploratory and Validation Cohort Study.JMIR public health and surveillance · 2024Article
- Characteristics of Users and Nonusers of Symptom Checkers in Germany: Cross-Sectional Survey Study.Journal of medical Internet research · 2023Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLow- and middle-income countries face difficulties in providing adequate health care. One of the reasons is a shortage of qualified health workers. Diagnostic decision support systems are designed to aid clinicians in their work and have the potential to mitigate pressure on health care systems.
objectiveThe Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania (AFYA) study will evaluate the potential of an English-language artificial intelligence-based prototype diagnostic decision support system for mid-level health care practitioners in a low- or middle-income setting.
methodsThis is an observational, prospective clinical study conducted in a busy Tanzanian district hospital. In addition to usual care visits, study participants will consult a mid-level health care practitioner, who will use a prototype diagnostic decision support system, and a study physician. The accuracy and comprehensiveness of the differential diagnosis provided by the diagnostic decision support system will be evaluated against a gold-standard differential diagnosis provided by an expert panel.
resultsPatient recruitment started in October 2021. Participants were recruited directly in the waiting room of the outpatient clinic at the hospital. Data collection will conclude in May 2022. Data analysis is planned to be finished by the end of June 2022. The results will be published in a peer-reviewed journal.
conclusionsMost diagnostic decision support systems have been developed and evaluated in high-income countries, but there is great potential for these systems to improve the delivery of health care in low- and middle-income countries. The findings of this real-patient study will provide insights based on the performance and usability of a prototype diagnostic decision support system in low- or middle-income countries.
trial registrationClinicalTrials.gov NCT04958577; http://clinicaltrials.gov/ct2/show/NCT04958577. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34298.
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