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

Author:

Schmude MarcelORCID,Salim NahyaORCID,Azadzoy HilaORCID,Bane MustafaORCID,Millen ElizabethORCID,O’Donnell LisaORCID,Bode PhilippORCID,Türk EwelinaORCID,Vaidya RiaORCID,Gilbert StephenORCID

Abstract

Background Low- 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. Objective The 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. Methods This 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. Results Patient 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. Conclusions Most 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 Registration ClinicalTrials.gov NCT04958577; http://clinicaltrials.gov/ct2/show/NCT04958577 International Registered Report Identifier (IRRID) DERR1-10.2196/34298

Publisher

JMIR Publications Inc.

Subject

General Medicine

Reference43 articles.

1. Global health workforce shortage to reach 12.9 million in coming decadesWorld Health Organization2022-05-12https://apps.who.int/mediacentre/news/releases/2013/health-workforce-shortage/en/index.html

2. Analysis of clinical knowledge, absenteeism and availability of resources for maternal and child health: a cross-sectional quality of care study in 10 African countries

3. Service Delivery Indicators Health Survey 2014 - Harmonized Public Use DataWorld Bank2022-05-12https://microdata.worldbank.org/index.php/catalog/2582/related-materials

4. Mortality due to low-quality health systems in the universal health coverage era: a systematic analysis of amenable deaths in 137 countries

5. Decision-support tools via mobile devices to improve quality of care in primary healthcare settings

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3