{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T19:01:01Z","timestamp":1792609261390,"version":"4.5.0"},"reference-count":81,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2023,9,10]],"date-time":"2023-09-10T00:00:00Z","timestamp":1694304000000},"content-version":"vor","delay-in-days":9,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Evidence Based Medicine"],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Aim<\/jats:title><jats:p>Technology including artificial intelligence (AI) may play a key role to strengthen primary health care services in resource\u2010poor settings. This systematic review aims to explore the evidence on the use of AI and digital health in improving primary health care service delivery.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Three electronic databases were searched using a comprehensive search strategy without providing any restriction in June 2023. Retrieved articles were screened independently using the \u201cRayyan\u201d software. Data extraction and quality assessment were conducted independently by two review authors. A narrative synthesis of the included interventions was conducted.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 4596 articles were screened, and finally, 48 articles were included from 21 different countries published between 2013 and 2021. The main focus of the included studies was noncommunicable diseases (<jats:italic>n<\/jats:italic>\u00a0=\u00a015), maternal and child health care (<jats:italic>n<\/jats:italic>\u00a0=\u00a011), primary care (<jats:italic>n<\/jats:italic>\u00a0=\u00a08), infectious diseases including tuberculosis, leprosy, and HIV (<jats:italic>n<\/jats:italic>\u00a0=\u00a07), and mental health (<jats:italic>n<\/jats:italic>\u00a0=\u00a06). Included studies considered interventions using AI, and digital health of which mobile\u2010phone\u2010based interventions were prominent. m\u2010health interventions were well adopted and easy to use and improved the record\u2010keeping, service deliver, and patient satisfaction.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>AI and the application of digital technologies improve primary health care service delivery in resource\u2010poor settings in various ways. However, in most of the cases, the application of AI and digital health is implemented through m\u2010health. There is a great scope to conduct further research exploring the interventions on a large scale.<\/jats:p><\/jats:sec>","DOI":"10.1111\/jebm.12547","type":"journal-article","created":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T06:13:37Z","timestamp":1694412817000},"page":"303-320","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Artificial intelligence and digital health in improving primary health care service delivery in LMICs: A systematic review"],"prefix":"10.1111","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8702-7094","authenticated-orcid":false,"given":"KM","family":"Saif\u2010Ur\u2010Rahman","sequence":"first","affiliation":[{"name":"College of Medicine Nursing and Health Sciences University of Galway  Galway Ireland"},{"name":"Evidence Synthesis Ireland and Cochrane Ireland University of Galway  Galway Ireland"},{"name":"Health Systems and Population Studies Division 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