Studies I–IV
The studies examine EMS as a safety net under uncertainty—spanning dispatcher reasoning, conditional risk patterns, concordance across system classifications, and system-level drivers of response-time variability.
Study I — Dispatcher work under scarcity
Question: How do dispatchers prioritise and coordinate allocation when calls compete for limited units?
Status: Preprint available
Study II — Breathing emergencies
Question: How do response time and patient factors interact in conditional risk patterns in breathing-problem missions?
Status: Published
Study III — Infection presentations
Question: What is the concordance between dispatch suspicion, on-scene phenotype (ESS), and high-risk triage (RETTS)?
Status: Preprint available
Study IV — Response-time variability
Question: Which operational and contextual factors jointly shape response-time distributions and tail delays?
Status: Published
Interpretation note: Where exploratory machine learning is used, interpretability tools are emphasised to understand heterogeneity and non-linear patterns. Model “performance” must not be read as evidence for deployable dispatch automation.
Adaptive EMS Allocation 