Journal of evaluation in clinical practice · 2026
Health Economic & Implementation Determinants of Prehospital Stroke Triage Tools: A Systematic Review.
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Alexandrov Nadja, der Zee Durk-Jouke van, Eurlings Maud B R C, van Stigt Maritta N, Theunissen Monique, Buskens Erik, van der Waaij Koen M, Gommer Erik D, Coutinho Jonathan M, Uyttenboogaart Maarten, Lahr Maarten M H
Аннотация
RATIONALE: Effective prehospital stroke triage enables faster treatment and better patient outcomes. Although prehospital triage innovations are rapidly emerging, evidence regarding the balance between costs and benefits as well as implementation issues remains limited.
AIMS AND OBJECTIVES: This review aims to synthesise published evidence on health economics and implementation determinants of prehospital triage tools for acute suspected ischaemic stroke patients.
METHOD: 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-simulation, COREQ, CONSORT, SQUIRE, and GRAMMS. Included were empirical studies of EMS-operated prehospital triage innovations for acute suspected stroke patients. The main outcome measures were health economic outcomes (e.g., ICER) and system-level implementation determinants (CFIR constructs).
RESULTS: From 6491 screened studies, thirty-one were included: thirteen studies included health economic outcomes and eighteen reported implementation determinants. Prehospital triage tools assessed were: MSU (n = 14), telemedicine (n = 13), clinimetrics (n = 1), prehospital MRI (n = 1), biomarkers (n = 1), and an AI-based microwave tool (n = 1). Most studies (68%) were of high reporting quality. Positive results regarding cost-effectiveness were reported (n = 11), including cost-savings (n = 1), as well as implementation determinants (n = 11). However, evidence on sustained implementation was limited. Barriers included innovation design, complexity, workflow compatibility, work and IT infrastructure, and costs.
CONCLUSION: Included studies suggest most prehospital stroke triage tools are cost-effective, but implementation remains largely context-dependent. 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.
AIMS AND OBJECTIVES: This review aims to synthesise published evidence on health economics and implementation determinants of prehospital triage tools for acute suspected ischaemic stroke patients.
METHOD: 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-simulation, COREQ, CONSORT, SQUIRE, and GRAMMS. Included were empirical studies of EMS-operated prehospital triage innovations for acute suspected stroke patients. The main outcome measures were health economic outcomes (e.g., ICER) and system-level implementation determinants (CFIR constructs).
RESULTS: From 6491 screened studies, thirty-one were included: thirteen studies included health economic outcomes and eighteen reported implementation determinants. Prehospital triage tools assessed were: MSU (n = 14), telemedicine (n = 13), clinimetrics (n = 1), prehospital MRI (n = 1), biomarkers (n = 1), and an AI-based microwave tool (n = 1). Most studies (68%) were of high reporting quality. Positive results regarding cost-effectiveness were reported (n = 11), including cost-savings (n = 1), as well as implementation determinants (n = 11). However, evidence on sustained implementation was limited. Barriers included innovation design, complexity, workflow compatibility, work and IT infrastructure, and costs.
CONCLUSION: Included studies suggest most prehospital stroke triage tools are cost-effective, but implementation remains largely context-dependent. 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.