KM Saif-Ur-Rahman, Md Shariful Islam, Joan Alaboson, Oluwadara Ola, Imran Hasan, Nazmul Islam, Shristi Mainali, Tina Martina, Eva Silenga, Mubita Muyangana, Taufique Joarder
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A narrative synthesis of the included interventions was conducted.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <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 (<i>n</i> = 15), maternal and child health care (<i>n</i> = 11), primary care (<i>n</i> = 8), infectious diseases including tuberculosis, leprosy, and HIV (<i>n</i> = 7), and mental health (<i>n</i> = 6). Included studies considered interventions using AI, and digital health of which mobile-phone-based interventions were prominent. m-health interventions were well adopted and easy to use and improved the record-keeping, service deliver, and patient satisfaction.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>AI and the application of digital technologies improve primary health care service delivery in resource-poor settings in various ways. However, in most of the cases, the application of AI and digital health is implemented through m-health. There is a great scope to conduct further research exploring the interventions on a large scale.</p>\n </section>\n </div>","PeriodicalId":16090,"journal":{"name":"Journal of Evidence‐Based Medicine","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jebm.12547","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence and digital health in improving primary health care service delivery in LMICs: A systematic review\",\"authors\":\"KM Saif-Ur-Rahman, Md Shariful Islam, Joan Alaboson, Oluwadara Ola, Imran Hasan, Nazmul Islam, Shristi Mainali, Tina Martina, Eva Silenga, Mubita Muyangana, Taufique Joarder\",\"doi\":\"10.1111/jebm.12547\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Aim</h3>\\n \\n <p>Technology including artificial intelligence (AI) may play a key role to strengthen primary health care services in resource-poor settings. This systematic review aims to explore the evidence on the use of AI and digital health in improving primary health care service delivery.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <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 “Rayyan” software. Data extraction and quality assessment were conducted independently by two review authors. A narrative synthesis of the included interventions was conducted.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <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 (<i>n</i> = 15), maternal and child health care (<i>n</i> = 11), primary care (<i>n</i> = 8), infectious diseases including tuberculosis, leprosy, and HIV (<i>n</i> = 7), and mental health (<i>n</i> = 6). Included studies considered interventions using AI, and digital health of which mobile-phone-based interventions were prominent. m-health interventions were well adopted and easy to use and improved the record-keeping, service deliver, and patient satisfaction.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>AI and the application of digital technologies improve primary health care service delivery in resource-poor settings in various ways. However, in most of the cases, the application of AI and digital health is implemented through m-health. 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Artificial intelligence and digital health in improving primary health care service delivery in LMICs: A systematic review
Aim
Technology including artificial intelligence (AI) may play a key role to strengthen primary health care services in resource-poor settings. This systematic review aims to explore the evidence on the use of AI and digital health in improving primary health care service delivery.
Methods
Three electronic databases were searched using a comprehensive search strategy without providing any restriction in June 2023. Retrieved articles were screened independently using the “Rayyan” software. Data extraction and quality assessment were conducted independently by two review authors. A narrative synthesis of the included interventions was conducted.
Results
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 (n = 15), maternal and child health care (n = 11), primary care (n = 8), infectious diseases including tuberculosis, leprosy, and HIV (n = 7), and mental health (n = 6). Included studies considered interventions using AI, and digital health of which mobile-phone-based interventions were prominent. m-health interventions were well adopted and easy to use and improved the record-keeping, service deliver, and patient satisfaction.
Conclusion
AI and the application of digital technologies improve primary health care service delivery in resource-poor settings in various ways. However, in most of the cases, the application of AI and digital health is implemented through m-health. There is a great scope to conduct further research exploring the interventions on a large scale.
期刊介绍：
The Journal of Evidence-Based Medicine (EMB) is an esteemed international healthcare and medical decision-making journal, dedicated to publishing groundbreaking research outcomes in evidence-based decision-making, research, practice, and education. Serving as the official English-language journal of the Cochrane China Centre and West China Hospital of Sichuan University, we eagerly welcome editorials, commentaries, and systematic reviews encompassing various topics such as clinical trials, policy, drug and patient safety, education, and knowledge translation.
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