[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120618-en":3,"doc-seo-120618-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120618,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Scoping review on the economic aspects of machine learning applications in healthcare","Artificial intelligence and machine learning technologies are increasingly used in healthcare, raising demand for evidence on their safety and value. Economic evaluations are critical for informing healthcare decision-making and resource allocation. This scoping review mapped and synthesized current approaches to assessing the economic aspects of machine learning-based technologies implemented in healthcare. The review followed updated JBI scoping guidance to identify and compare study methods and reporting against CHEERS-AI.","This is an electronic reprint of the original article.  \nThis reprint may differ from the original in pagination and typographic detail.  \nvon Gerich, Hanna; Helenius, Mikael; Hörhammer, Iiris; Moen, Hans; Peltonen, Laura Maria  \nScoping review on the economic aspects of machine learning applications in healthcare  \nPublished in:  \nInternational Journal of Medical Informatics  \nDOI:  \n10.1016/j.ijmedinf.2025.106103  \nPublished: 01/01/2026  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nPublished under the following license:  \nCC BY  \nPlease cite the original version:  \nvon Gerich, H. , Helenius, M. , Hörhammer, I. , Moen, H. , & Peltonen, L. M. (2026) . Scoping review on the economic aspects of machine learning applications in healthcare. International Journal of Medical Informatics, 205, 1-10 . Article 106103. [https://doi.org/10.1016/j.ijmedinf.2025.106103](https://doi.org/10.1016/j.ijmedinf.2025.106103)  \nThis material is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you foryour research use or educational purposes in electronic or print form. You must obtain permission for anyother use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user.  \nInternational Journal of Medical Informatics 205 (2026) 106103  \nContents lists available at ScienceDirect  \nInternational Journal of Medical Informatics  \njournal [homepage: www.elsevier.com/locate/ijmedinf](homepage: www.elsevier.com/locate/ijmedinf)  \n| Review article\u003Cbr>Scoping review on the economic aspects of machine learning applications in healthcare\u003Cbr>Hanna von Gericha,b,*, Mikael Heleniusc,a, Iiris H¨orhammer d, Hans Moend, Laura-Maria Peltonene\u003Cbr>a Department of Nursing Science, University of Turku, Finland\u003Cbr>b Department of Health and Social Management, University of Eastern Finland, Finland c Turku University Hospital, Finland\u003Cbr>d Department of Computer Science, Aalto University, Finland\u003Cbr>e Department of Health and Social Management, University of Eastern Finland, and Kuopio University Hospital, Finland |  |  |\n| --- | --- | --- |\n| A R T I C L E I N F O |  | A B S T R A C T |\n| Keywords:\u003Cbr>Artificial intelligence Machine learning Costs and Cost Analysis Healthcare |  | Background: The development and use of artificial intelligence and machine learning technologies in healthcare have increased, prompting a need for evidence on their safety and value. Economic evaluations support healthcare decision-making and resource allocation. This scoping review aimed to map and synthesize current approaches to evaluating the economic aspects of machine learning based technologies implemented in healthcare.\u003Cbr>Methods: Following the updated JBI guidance for scoping reviews, six databases (PubMed, CINAHL, Cochrane Library, Embase, Scopus, and IEEE Xplore) were searched for studies evaluating the economic aspects of machine learning-based technologies within healthcare. No exclusions were applied to healthcare settings, healthcare professionals or used economic evaluation methods. The results of data extraction were analyzed using descriptive statistics and inductive coding. The reporting of the studies was compared against the CHEERS-AI statement.\u003Cbr>Results: A total of 6332 references were retrieved, with 18 studies included in the review. The studies comprised economic evaluations (n = 9), impact evaluations (n = 5), and performance evaluations (n = 4), with costeffectiveness analysis being the most frequently used economic evaluation method (n = 8). The comparison of the studies to the reporting guidelines revealed gaps in the reporting of details from economic evaluations and the artificial intelligence nature of the technologies. Overall, the study alignment with the CHEERS-AI items on average was 39.6 %, with 64.1 % alignment with econom","cbCaijtVdQTkRtyj","https://ap.wps.com/l/cbCaijtVdQTkRtyj","pdf",1098737,1,11,"English","en",105,"# Abstract\n# Introduction\n# Methods and Data Sources\n# Results\n## Study types and economic evaluation approaches\n## Reporting quality gaps vs CHEERS-AI\n# Conclusions","[{\"question\":\"What was the purpose of the scoping review on economic aspects of machine learning in healthcare?\",\"answer\":\"To map and synthesize current approaches for evaluating the economic aspects of machine learning-based technologies implemented in healthcare, supporting healthcare decision-making and resource allocation.\"},{\"question\":\"How were studies selected and analyzed in the review?\",\"answer\":\"Six databases were searched (PubMed, CINAHL, Cochrane Library, Embase, Scopus, IEEE Xplore) for studies evaluating economic aspects of machine learning technologies in healthcare. Extracted data were analyzed using descriptive statistics and inductive coding.\"},{\"question\":\"What did the review find about the types of economic evaluations and reporting quality?\",\"answer\":\"Eighteen studies were included, covering economic evaluations, impact evaluations, and performance evaluations, with cost-effectiveness analysis used most often. Comparisons to CHEERS-AI showed notable reporting gaps, especially in details describing economic evaluations and the artificial intelligence nature of the technologies.\"}]","Scoping review on the economic aspects of machine learning applications in healthcare | PDF",1785730929,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"scoping-review-on-the-economic-aspects-of-machine-learning-applications-in-healthcare","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/scoping-review-on-the-economic-aspects-of-machine-learning-applications-in-healthcare/120618/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What was the purpose of the scoping review on economic aspects of machine learning in healthcare?","Question",{"text":75,"@type":76},"To map and synthesize current approaches for evaluating the economic aspects of machine learning-based technologies implemented in healthcare, supporting healthcare decision-making and resource allocation.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were studies selected and analyzed in the review?",{"text":80,"@type":76},"Six databases were searched (PubMed, CINAHL, Cochrane Library, Embase, Scopus, IEEE Xplore) for studies evaluating economic aspects of machine learning technologies in healthcare. Extracted data were analyzed using descriptive statistics and inductive coding.",{"name":82,"@type":73,"acceptedAnswer":83},"What did the review find about the types of economic evaluations and reporting quality?",{"text":84,"@type":76},"Eighteen studies were included, covering economic evaluations, impact evaluations, and performance evaluations, with cost-effectiveness analysis used most often. 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