Research outputs and publications
Peer-reviewed articles, doctoral thesis, manuscripts, and selected outputs on adaptive EMS allocation, prehospital patient safety, dispatch prioritisation, triage, response-time variability, and system governance.
Doctoral thesis
The doctoral thesis integrates the four supporting studies into a systems-oriented account of EMS allocation as part of the prehospital patient safety net.
Adaptive emergency medical services allocation: crafting the patient safety net in prehospital emergency care
Hill, P. Adaptive emergency medical services allocation: crafting the patient safety net in prehospital emergency care. Doctoral thesis. Karolinska Institutet, Department of Clinical Science and Education, Södersjukhuset. Stockholm, 2026.
DOI: 10.69622/31262914
ISBN: 978-91-8141-015-0
Contribution: Frames EMS allocation as a safety-net problem under uncertainty, integrating dispatch stewardship, patient vulnerability, response-time variability, triage concordance, and governance of scarce response capacity.
Published articles
Three supporting studies are published as peer-reviewed journal articles. Together they examine dispatch work, breathing-problem missions, and response-time variability.
Stewarding scarce response capacity: an inductive qualitative interview study of emergency medical dispatchers prioritising ambulance resources
Hill P, Lederman J, Jonsson D, Bolin P, Vicente V. BMJ Open. 2026. doi: 10.1136/bmjopen-2026-118269.
Contribution: Examines emergency medical dispatchers’ experiences of prioritising patients and stewarding ambulance resources when system capacity is constrained. The study frames dispatch under scarcity as active stewardship of a safety-critical dispatch queue.
Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study
Hill P, Jonsson D, Lederman J, Bolin P, Vicente V. BMC Medical Informatics and Decision Making. 2025;25:205.
Contribution: Explores how response time, age, and sex interact with high-risk time-sensitive conditions among patients initially reported with breathing problems.
Understanding EMS response times: a machine learning-based analysis
Hill P, Lederman J, Jonsson D, Bolin P, Vicente V. BMC Medical Informatics and Decision Making. 2025;25:143.
Contribution: Examines multifactorial determinants of EMS response-time variability using register-based data and machine learning methods.
Study III
Study III maps concordance between dispatch suspicion, on-scene phenotype, and time-sensitive triage in prehospital infectious presentations.
Concordance between dispatch suspicion, on-scene phenotype, and time-sensitive triage
Full title: Concordance Between Dispatch Suspicion, On-Scene Phenotype, and Time Sensitive Triage in Prehospital Infectious Presentations: A Retrospective Machine-Learning Study.
Contribution: Maps how dispatch suspicion, early on-scene phenotype, and high-risk triage align in infectious EMS presentations.
Preprint DOI: 10.21203/rs.3.rs-7651316/v1
Conservative publication status
Publication status is listed conservatively. Peer-reviewed articles are separated from manuscripts and preprints. Operational claims, deployment readiness, and causal interpretation are avoided unless supported by study design and prospective evaluation.
The research uses qualitative evidence and observational EMS data to support system understanding, not patient-level advice or validated real-time dispatch automation.
