ArticleBMC medical informatics and decision making2025
Enhancing prehospital decision-making: exploring user needs and design considerations for clinical decision support systems.
Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Artificial Intelligence in Prehospital Tele-Emergency Medicine: A Survey of Acceptance and Attitudes.Healthcare (Basel, Switzerland) · 2026Article
- Associations Among Emotional Intelligence, Job Stress, and Clinical Decision-Making in Prehospital Emergency Staff: A Cross-Sectional Study.Health science reports · 2026Article
- Improving Clinical Decision-Making in Treating Airway Diseases With an Expert System Built Upon the Free AI Tool Google NotebookLM.JMIR medical informatics · 2026Article
- Evaluating the real-world utility of four physiological scores for prehospital interventions in resource-limited EMS systems: a population-based study of 15,720 cases.BMC health services research · 2026Article
- Promise and Caution: Mapping Opportunities for AI Decision Support in Emergency Medical Services.Proceedings. IEEE International Conference on Healthcare Informatics · 2026Article
- Performance Indicators in Emergency Medical Services: A Scoping Review of Dashboard Applications in the Context of Crisis Management.Archives of academic emergency medicine · 2026Review
- A Needle in a Haystack: Looking for Gaps in Treatment and Education in Emergency Medicine-Editorial.Healthcare (Basel, Switzerland) · 2025Article
- Artificial Intelligence (AI) and Emergency Medicine: Balancing Opportunities and Challenges.JMIR medical informatics · 2025Review
- Emergency Primary Care Personnel's Perspectives Toward AI-Based Decision Support Tools: A Qualitative Study in Norway.Journal of primary care & community healthArticle
- Article
- The user experiences of AI-based clinical decision support systems and implications for usage over time: A scoping review.Digital healthReview
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5 authors.
Funding
Abstract
backgroundIn prehospital emergency care, providers face significant challenges in making informed decisions due to factors such as limited cognitive support, high-stress environments, and lack of experience with certain patient conditions. Effective Clinical Decision Support Systems (CDSS) have great potential to alleviate these challenges. However, such systems have not yet been widely adopted in real-world practice and have been found to cause workflow disruptions and usability issues. Therefore, it is critical to investigate how to design CDSS that meet the needs of prehospital providers while accounting for the unique characteristics of prehospital workflows.
methodsWe conducted semi-structured interviews with 20 prehospital providers recruited from four Emergency Medical Services (EMS) agencies in an urban area in the northeastern U.S. The interviews focused on the decision-making challenges faced by prehospital providers, their technological needs for decision support, and key considerations for the design and implementation of a CDSS that can seamlessly integrate into prehospital care workflows. The data were analyzed using content analysis to identify common themes.
resultsOur qualitative study identified several challenges in prehospital decision-making, including limited access to diagnostic tools, insufficient experience with certain critical patient conditions, and a lack of cognitive support. Participants highlighted several desired features to make CDSS more effective in the dynamic, hands-busy, and cognitively demanding prehospital context, such as automatic prompts for possible patient conditions and treatment options, alerts for critical patient safety events, AI-powered medication identification, and easy retrieval of protocols using hands-free methods (e.g., voice commands). Key considerations for successful CDSS adoption included balancing the frequency and urgency of alerts to reduce alarm fatigue and workflow disruptions, facilitating real-time data collection and documentation to enable decision generation, and ensuring trust and accountability while preventing over-reliance when using CDSS.
conclusionThis study provides empirical insights into the challenges and user needs in prehospital decision-making and offers practical and system design implications for addressing these issues.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.