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Although prehospital triage innovations are rapidly emerging, evidence regarding the balance between costs and benefits as well as implementation issues remains limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aims and Objectives<\/jats:title>\n                    <jats:p>This review aims to synthesise published evidence on health economics and implementation determinants of prehospital triage tools for acute suspected ischaemic stroke patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>A systematic search was conducted across five databases (CINAHL, Cochrane, EMBASE, PubMed, and Web of Science) between 1995 and 2025. Results were reported narratively, and reporting quality was assessed using CHEERS, STROBE\u2010simulation, COREQ, CONSORT, SQUIRE, and GRAMMS. Included were empirical studies of EMS\u2010operated prehospital triage innovations for acute suspected stroke patients. The main outcome measures were health economic outcomes (e.g., ICER) and system\u2010level implementation determinants (CFIR constructs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      From 6491 screened studies, thirty\u2010one were included: thirteen studies included health economic outcomes and eighteen reported implementation determinants. Prehospital triage tools assessed were: MSU (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200914), telemedicine (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200913), clinimetrics (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091), prehospital MRI (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091), biomarkers (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091), and an AI\u2010based microwave tool (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091). Most studies (68%) were of high reporting quality. Positive results regarding cost\u2010effectiveness were reported (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200911), including cost\u2010savings (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091), as well as implementation determinants (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200911). However, evidence on sustained implementation was limited. Barriers included innovation design, complexity, workflow compatibility, work and IT infrastructure, and costs.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Included studies suggest most prehospital stroke triage tools are cost\u2010effective, but implementation remains largely context\u2010dependent. Barriers, including innovation complexity, role delineation, workflow fit, design, and costs, highlight the need for future studies to integrate health economics into an implementation science framework alongside clinical outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jep.70634","type":"journal-article","created":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T18:12:06Z","timestamp":1791137526000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Health Economic &amp; Implementation Determinants of Prehospital Stroke Triage Tools: A Systematic Review"],"prefix":"10.1111","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4958-1276","authenticated-orcid":false,"given":"Nadja","family":"Alexandrov","sequence":"first","affiliation":[{"name":"Health Technology Assessment, Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen Groningen the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9754-1193","authenticated-orcid":false,"given":"Durk\u2010Jouke van","family":"der Zee","sequence":"additional","affiliation":[{"name":"Health Technology Assessment, Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen Groningen the Netherlands"},{"name":"Department of Operations Faculty of Economics and Business, University of Groningen Groningen Groningen the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7630-2417","authenticated-orcid":false,"given":"Maud B. 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