{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T17:59:49Z","timestamp":1790359189093,"version":"4.1.0"},"reference-count":32,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["513679"],"award-info":[{"award-number":["513679"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Artificial Intelligence for Public Health (AI4PH) Health Research Training Platform","award":["Artificial Intelligence for Public Health and Health Equity Trainee Scholarship Program"],"award-info":[{"award-number":["Artificial Intelligence for Public Health and Health Equity Trainee Scholarship Program"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Primary health care (PHC) is the cornerstone of health systems worldwide, yet faces growing pressures from aging populations, workforce shortages, and constrained resources. While artificial intelligence (AI) and machine learning (ML) are increasingly used for clinical tasks such as diagnostics and decision support, their potential to address organizational and system-level processes remains underexplored. This scoping review maps AI and ML applications targeting non-clinical, organizational, and system-level functions in PHC, examining techniques employed, application purposes, data sources, and implementation maturity, and identifying evidence gaps to inform future research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This scoping review will be conducted using the Arksey and O\u2019Malley framework and reported according to PRISMA-ScR. We will search Ovid MEDLINE, EBSCO CINAHL, Ovid Embase, Cochrane Library (Wiley), Ovid PsycINFO, and IEEE Xplore, as well as grey literature sources, from January 2010 to December 2025, with a pre-submission update. Two independent reviewers will screen titles, abstracts, and full texts. Eligible studies include empirical research describing, evaluating, implementing, or developing AI and ML applications at the meso-level (organizational, e.g., care scheduling, population stratification) and macro-level (system-wide, e.g., workforce planning, funding allocation) of PHC. Studies on micro-level clinical applications, non-empirical research, and secondary literature will be excluded. Applications will be classified using a two-layer taxonomy (AI technique family and core algorithm) and mapped to PHC building blocks adapted from WHO operational frameworks. Synthesis will examine technique-building block intersections, application purposes, data sources, implementation maturity, and evidence gaps. The protocol is registered in Open Science Framework (osf.io\/wzj5x).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This review will provide a timely synthesis of AI and ML applications at organizational and system levels of PHC, identifying which building blocks have been addressed, which remain underexplored, and where the field stands in terms of implementation readiness. The findings will inform a targeted research agenda and provide actionable evidence for decision-makers seeking to leverage AI and ML for PHC strengthening.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0329426","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T17:24:37Z","timestamp":1790357077000},"page":"e0329426","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence and machine learning for organizational and system-level functions in primary health care: A scoping review protocol"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6268-559X","authenticated-orcid":true,"given":"Pablo","family":"Galvez-Hernandez","sequence":"first","affiliation":[{"name":"University of Toronto Scarborough","place":["Toronto, Ontario, Canada"],"department":["Department of Health and Society"]},{"name":"Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto","place":["Toronto, Ontario, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li-Anne","family":"Audet","sequence":"additional","affiliation":[{"name":"Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto","place":["Toronto, Ontario, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahra","family":"Shakeri","sequence":"additional","affiliation":[{"name":"Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto","place":["Toronto, Ontario, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walter P.","family":"Wodchis","sequence":"additional","affiliation":[{"name":"Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto","place":["Toronto, Ontario, Canada"]},{"name":"Institute for Better Health, Trillium Health Partners","place":["Toronto, Ontario, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,25]]},"reference":[{"key":"pone.0329426.ref001","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4842-3799-1","volume-title":"Machine learning and AI for healthcare","author":"A Panesar","year":"2019"},{"issue":"2","key":"pone.0329426.ref002","doi-asserted-by":"crossref","first-page":"020303","DOI":"10.7189\/jogh.08.020303","article-title":"Artificial intelligence, machine learning and health systems","volume":"8","author":"T Panch","year":"2018","journal-title":"J Glob Health"},{"issue":"9","key":"pone.0329426.ref003","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0274276","article-title":"A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data","volume":"18","author":"H Abdulazeem","year":"2023","journal-title":"PLoS One"},{"issue":"1","key":"pone.0329426.ref004","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1111\/1475-6773.13871","article-title":"Predictive modeling of service discontinuation in transitional age youth with recent behavioral health service use","volume":"57","author":"C Bory","year":"2022","journal-title":"Health Serv Res"},{"key":"pone.0329426.ref005","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.puhe.2020.04.040","article-title":"The promise of big data for precision population health management in the US","volume":"185","author":"A Han","year":"2020","journal-title":"Public Health"},{"key":"pone.0329426.ref006","doi-asserted-by":"crossref","first-page":"107814","DOI":"10.1016\/j.cmpb.2023.107814","article-title":"Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy","volume":"242","author":"N Altini","year":"2023","journal-title":"Comput Methods Programs Biomed"},{"issue":"2","key":"pone.0329426.ref007","article-title":"Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study","volume":"4","author":"P Bachtiger","year":"2022","journal-title":"Lancet Digit Health"},{"issue":"9","key":"pone.0329426.ref008","doi-asserted-by":"crossref","DOI":"10.2196\/29839","article-title":"Application of artificial intelligence in community-based primary health care: systematic scoping review and critical appraisal","volume":"23","author":"S Abbasgholizadeh Rahimi","year":"2021","journal-title":"J Med Internet Res"},{"issue":"6","key":"pone.0329426.ref009","doi-asserted-by":"crossref","DOI":"10.2196\/35053","article-title":"Emerging artificial intelligence-empowered mHealth: scoping review","volume":"10","author":"P Bhatt","year":"2022","journal-title":"JMIR Mhealth Uhealth"},{"key":"pone.0329426.ref010","volume-title":"Monitoring the building blocks of health systems: a handbook of indicators and their measurement strategies","author":"World Health Organization","year":"2010"},{"issue":"8","key":"pone.0329426.ref011","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1001073","article-title":"Building the field of health policy and systems research: framing the questions","volume":"8","author":"K Sheikh","year":"2011","journal-title":"PLoS Med"},{"key":"pone.0329426.ref012","volume-title":"Operational framework for primary health care: transforming vision into action","author":"World Health Organization, United Nations Children\u2019s Fund","year":"2020"},{"issue":"3","key":"pone.0329426.ref013","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0320317","article-title":"Mobilizing community health assets through intersectoral collaboration for social connection: associations with social support and well-being in a nationwide population-based study in Catalonia","volume":"20","author":"P Galvez-Hernandez","year":"2025","journal-title":"PLoS One"},{"key":"pone.0329426.ref014","author":"Organisation for Economic Co-operation and Development","year":"2023","journal-title":"Health at a glance 2023: OECD indicators"},{"key":"pone.0329426.ref015","volume-title":"Primary health care measurement framework and indicators: monitoring health systems through a primary health care lens","author":"World Health Organization, United Nations Children\u2019s Fund","year":"2022"},{"key":"pone.0329426.ref016","doi-asserted-by":"crossref","DOI":"10.2196\/50379","article-title":"Generating contextual variables from web-based data for health research: tutorial on web scraping, text mining, and spatial overlay analysis","volume":"10","author":"P Galvez-Hernandez","year":"2024","journal-title":"JMIR Public Health Surveill"},{"issue":"1","key":"pone.0329426.ref017","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1186\/s12913-020-05868-1","article-title":"At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care","volume":"20","author":"LA Orlando","year":"2020","journal-title":"BMC Health Serv Res"},{"issue":"4","key":"pone.0329426.ref018","doi-asserted-by":"crossref","DOI":"10.2196\/medinform.6530","article-title":"Weighting primary care patient panel size: a novel electronic health record-derived measure using machine learning","volume":"4","author":"A Rajkomar","year":"2016","journal-title":"JMIR Med Inform"},{"issue":"1","key":"pone.0329426.ref019","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s12875-023-01969-y","article-title":"Machine learning in general practice: scoping review of administrative task support and automation","volume":"24","author":"NL S\u00f8rensen","year":"2023","journal-title":"BMC Prim Care"},{"issue":"1","key":"pone.0329426.ref020","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s12962-023-00492-2","article-title":"The application of artificial intelligence in health financing: a scoping review","volume":"21","author":"M Ramezani","year":"2023","journal-title":"Cost Eff Resour Alloc"},{"issue":"1","key":"pone.0329426.ref021","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1080\/1364557032000119616","article-title":"Scoping studies: towards a methodological framework","volume":"8","author":"H Arksey","year":"2005","journal-title":"Int J Soc Res Methodol"},{"issue":"7","key":"pone.0329426.ref022","doi-asserted-by":"crossref","first-page":"467","DOI":"10.7326\/M18-0850","article-title":"PRISMA Extension for Scoping Reviews (PRISMA-ScR): checklist and explanation","volume":"169","author":"AC Tricco","year":"2018","journal-title":"Ann Intern Med"},{"issue":"4","key":"pone.0329426.ref023","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1136\/svn-2017-000101","article-title":"Artificial intelligence in healthcare: past, present and future","volume":"2","author":"F Jiang","year":"2017","journal-title":"Stroke Vasc Neurol"},{"issue":"3","key":"pone.0329426.ref024","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1097\/XEB.0000000000000050","article-title":"Guidance for conducting systematic scoping reviews","volume":"13","author":"MDJ Peters","year":"2015","journal-title":"Int J Evid Based Healthc"},{"key":"pone.0329426.ref025","unstructured":"Lefebvre C, Glanville J, Briscoe S, Featherstone R, Littlewood A, Metzendorf MI, et al. Cochrane Handbook for Systematic Reviews of Interventions version 6.5.1 Cochrane, 2025. Available from cochrane.org\/handbook."},{"key":"pone.0329426.ref026","author":"Yale University","year":"2015"},{"issue":"2","key":"pone.0329426.ref027","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1177\/0049124118799372","article-title":"Interrater reliability in systematic review methodology: exploring variation in coder decision-making","volume":"50","author":"J Belur","year":"2018","journal-title":"Sociol Methods Res"},{"key":"pone.0329426.ref028","volume-title":"Artificial intelligence and machine learning in public healthcare: opportunities and societal impact","author":"KC Santosh","year":"2022"},{"issue":"7","key":"pone.0329426.ref029","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1016\/j.jval.2019.02.012","article-title":"Machine learning for health services researchers","volume":"22","author":"P Doupe","year":"2019","journal-title":"Value Health"},{"issue":"5","key":"pone.0329426.ref030","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/BF03405354","article-title":"Primary care (PC) and primary health care (PHC): what is the difference","volume":"97","author":"LK Muldoon","year":"2006","journal-title":"Can J Public Health"},{"issue":"12","key":"pone.0329426.ref031","doi-asserted-by":"crossref","first-page":"3343","DOI":"10.1007\/s11136-021-02766-9","article-title":"Implications of response shift for micro-, meso-, and macro-level healthcare decision-making using results of patient-reported outcome measures","volume":"30","author":"R Sawatzky","year":"2021","journal-title":"Qual Life Res"},{"key":"pone.0329426.ref032","doi-asserted-by":"crossref","first-page":"111237","DOI":"10.1016\/j.jclinepi.2023.111237","article-title":"Librarian involvement in systematic reviews was associated with higher quality of reported search methods: a cross-sectional survey","volume":"166","author":"C Pawliuk","year":"2024","journal-title":"J Clin Epidemiol"}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0329426","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T17:24:42Z","timestamp":1790357082000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0329426"}},"subtitle":[],"editor":[{"given":"Mohammad","family":"Saadati","sequence":"first","affiliation":[{"name":"Khoy University of Medical Sciences","place":["IRAN, ISLAMIC REPUBLIC OF"]}],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,9,25]]},"references-count":32,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,9,25]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0329426","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,25]]}}}