Prehospital emergency care · Patient safety

Crafting the
patient safety net.

How should ambulance systems allocate scarce capacity when several patients need help at the same time?

Research on ambulance allocation, waiting, system pressure and patient safety.

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Start with one callFollow one call. Change resources and compare two possible responses.

Preparing the experience…

Understand the research through the observatory

The observatory is a learning tool for the four studies: explore a question, compare synthetic scenarios, then examine the research and its limitations.

Interpretation boundaries

Study findings are empirical evidence. Response times here are synthetic calculations. Patient colours illustrate different sensitivity to waiting; they are not validated clinical predictions. Neither the simulation nor weather and traffic inputs establish a causal effect on patient outcomes.

Four studies. One question.

From dispatch decisions to clinical uncertainty and system delays. Three peer-reviewed articles and one preprint contribute different parts of the picture.

Emergency call
Dispatch assessment
Peer reviewed
Stewarding scarce response capacity
Dispatchers described stewardship of scarce response capacity through proportionate allocation, preserved availability and coordination. They also described moral strain and decisions that redistributed risk between patients and across time.
Question, findings and limitations
Research question
How dispatchers prioritise patients, govern the queue and preserve readiness when ambulance capacity is constrained.
Study population · Method
Inductive qualitative content analysis of semi-structured interviews with 13 purposively sampled emergency medical dispatchers in Sweden in May 2025.
Interpretation boundaries
The findings describe professional experience in one organisational context and should be transferred to other EMS systems with attention to local governance.
How is scarce response capacity shared?
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Dispatch & queue governance
BMJ Open · 2026Explore study 01
Resource allocation / waiting
Peer reviewed
Breathing emergencies and nonlinear risk
Age was the most important model feature; age over 60 was associated with higher modeled HRTS probability. Response-time relationships were nonlinear and varied with age and sex. Discrimination was modest (area under the ROC curve, AUC 0.66).
Question, findings and limitations
Research question
How response time, age and sex interact with high-risk time-sensitive triage among 132,395 breathing-problem missions.
Study population · Method
Retrospective observational analysis of 132,395 breathing-problem missions in Stockholm, 2017–2022. Multiple models and partial dependence (PD) and individual conditional expectation (ICE) plots explored nonlinear model relationships.
Interpretation boundaries
HRTS is RETTS red/orange triage, a higher-risk proxy rather than confirmed time-sensitive disease. Short response times can reflect prioritization of severe cases. These observational associations do not establish effects of waiting. The exploratory, single-region model is not validated for individual prediction or automated dispatch.
Why might the same wait matter differently?
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Patient vulnerability & waiting
BMC Medical Informatics and Decision Making · 2025Explore study 02
First EMS assessment
Preprint · not peer reviewed
Infectious presentations and concordance
The three information layers did not represent the same clinical construct; concordance changed depending on where in the care pathway infection and urgency were assessed.
Question, findings and limitations
Research question
How dispatch suspicion, on-scene phenotype and high-risk time-sensitive triage align in infectious presentations.
Study population · Method
Retrospective machine-learning study of 34,779 EMS assignments initially coded as Fever/Infection at dispatch in Region Stockholm, 2017–2022, after prespecified exclusions. It compared dispatch suspicion of infection, the first on-scene symptom phenotype and high-risk time-sensitive triage.
Interpretation boundaries
This preprint has not completed journal peer review. Observational associations do not establish causal effects or operational thresholds.
What is uncertain at the emergency call?
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Information across the care pathway
Research Square · 2026Explore study 03
System response-time distribution
Peer reviewed
Understanding EMS response times
Priority was the strongest overall feature, but workload, call reason, geography, precipitation, temperature and operational intervals interacted. Lower priorities had markedly long-tailed response-time distributions.
Question, findings and limitations
Research question
How priority, workload, geography, weather and operational intervals shape variability and tail delays.
Study population · Method
Retrospective analysis of 1,144,754 EMS missions in Stockholm, 2017–2022, integrating operational, geographic and weather variables with regression and machine-learning analyses.
Interpretation boundaries
Traffic data were unavailable and the study covered one region. Negative response times and times exceeding ten hours were excluded, limiting interpretation of atypical delays. Predictive performance does not establish readiness for real-time use.
What can the longest response times reveal?
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System capacity & response-time variation
BMC Medical Informatics and Decision Making · 2025Explore study 04

Doctoral thesis & publications

Policy brief Doctoral thesis · 2026 Peer-reviewed publications Research in progress

Peter Hill · Karolinska Institutet · DOI 10.69622/31262914

Research question and planned approach only. Unpublished results are not disclosed.

RESEARCH GUIDE

Ask EMS Allocation

Explore the research through questions.

This AI research guide uses the published research, thesis and explanatory material on this site. Answers should cite their sources and distinguish evidence status. It can make mistakes and is not clinical decision support. Questions are processed by Mistral AI; do not enter personal or patient information. Research integrity

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Get in touch

Peter Hill · peter.hill@ki.se

Karolinska Institutet profile LinkedIn

References & research resources

Bring the evidence into teaching, research and conversations about prehospital care. Reference files include the thesis, three journal articles and one preprint.

Policy brief · Research summary All references · RIS / EndNote All references · BibTeX Follow publications · RSS

Peer-reviewed publications

Doctoral thesis · 2026

Hill P. Adaptive emergency medical services allocation: crafting the patient safety net in prehospital emergency care. Stockholm: Karolinska Institutet; 2026. doi:10.69622/31262914

Preprint · not peer reviewed

Hill P, Jonsson D, Lederman J, Bolin P, Vicente V. Concordance Between Dispatch Suspicion, On‑Scene Phenotype, and Time Sensitive Triage in Prehospital Infectious Presentations: A Retrospective Machine‑Learning Study. Research Square. 2026. doi:10.21203/rs.3.rs-7651316/v1

Methodological limitations & research integrity

Exploration before deployment

The research is observational and explanatory. It does not provide patient-level advice or a validated real-time dispatch tool. Operational translation requires prospective evaluation, governance, human-factors design and safeguards.

Illustrative teaching model · no live data · not clinical decision support. Values are neither empirical findings nor patient-level predictions.