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Schmude M, Salim N, Azadzoy H, Bane M, Millen E, O’Donnell L, Bode P, Türk E, Vaidya R, Gilbert S
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
Investigating the potential for clinical decision support through a symptom assessment app in Sub-Saharan Africa (AFYA (AI-based Assessment of health symptoms in Tanzania)): Protocol for a pilot prospective, observational study
Marcel Schmude;
Nahya Salim;
Hila Azadzoy;
Mustafa Bane;
Elizabeth Millen;
Lisa O’Donnell;
Philipp Bode;
Ewelina Türk;
Ria Vaidya;
Stephen Gilbert
ABSTRACT
Background:
Low and middle income countries face difficulties in providing adequate healthcare. One of the reasons is a shortage of qualified health workers. Diagnostic decision support systems (DDSS) are developed to aid clinicians in their work and have the potential to mitigate the pressure on healthcare systems.
Objective:
The AFYA study (AI-based Assessment oF health sYmptoms in TAnzania) will evaluate the potential of an English language AI-based prototype-DDSS, in the hands of mid-level health care practitioners, to provide clinical decision support in a lower or middle income setting.
Methods:
This is an observational, prospective clinical study conducted in a busy Tanzanian district hospital. In addition to their usual care visit, study participants will have a consultation with a mid-level healthcare practitioner using a prototype-DDSS and a study physician. The accuracy and comprehensiveness of the DDSS differential diagnosis list will be evaluated against the gold standard differential diagnosis determined by an expert panel.
Results:
Patient recruitment is has started in October 2021. Participants will be recruited directly in the waiting room of an outpatient clinic. Data collection is expected to conclude by the end of December 2021. Data analysis is planned to be finished by June 2022. The results will be published in peer-reviewed journals.
Conclusions:
The findings of this real-patient study will provide insights based on the performance and usability of a prototype DDSS in a LMIC setting. Clinical Trial: NCT04958577
Citation
Please cite as:
Schmude M, Salim N, Azadzoy H, Bane M, Millen E, O’Donnell L, Bode P, Türk E, Vaidya R, Gilbert S
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