title: Why and when citizens call for emergency help: an observational study of 211,193 medical emergency calls.
abstract: BACKGROUND
  A medical emergency call is citizens' access to pre-hospital emergency care and ambulance services. Emergency medical dispatchers are gatekeepers to provision of pre-hospital resources and possibly hospital admissions. We explored causes for access, emergency priority levels, and temporal variation within seasons, weekdays, and time of day for emergency calls to the emergency medical dispatch center in Copenhagen in a two-year study period (December 1(st), 2011 to November 30(th), 2013).
  
  
  METHODS
  Descriptive analysis was performed for causes for access and emergency priority levels. A Poisson regression model was used to calculate adjusted ratio estimates for the association between seasons, weekdays, and time of day overall and stratified by emergency priority levels.
  
  
  RESULTS
  We analyzed 211,193 emergency calls for temporal variation. Of those, 167,635 calls were eligible for analysis of causes and emergency priority level. "Unclear problem" was the most frequent category (19%). The five most common causes with known origin were categorized as "Wounds, fractures, minor injuries" (13%), "Chest pain/heart disease" (11%), "Accidents" (9%), "Intoxication, poisoning, drug overdose" (8%), and "Breathing difficulties" (7%). The highest emergency priority levels (Emergency priority level A and B) were assigned in 81% of calls. In the analysis of temporal variation, the total number of calls peaked at wintertime (26%), Saturdays (16%), and during daytime (39%).
  
  
  CONCLUSIONS
  The pattern of citizens' contact causes fell into four overall categories: unclear problems, medical problems, intoxication and accidents. The majority of calls were urgent. The magnitude of unclear problems represents a modifiable factor and highlights the potential for further improvement of supportive dispatch priority tools or educational interventions at dispatch centers. Temporal variation was identified within seasons, weekdays and time of day and reflects both system load and disease occurrence. Data on contact patterns could be utilized in a public health perspective, benchmarking of EMS systems, and ultimately development of best practice in the area of emergency medicine.
authors.affiliation: Emergency Medical Services Copenhagen, University of Copenhagen, Copenhagen, Denmark. thea.palsgaard.moeller@regionh.dk.
authors.forename: Thea Palsgaard
authors.initials: TP
authors.lastname: Møller
authors.affiliation: National Institute of Public health, University of Southern Denmark, Copenhagen, Denmark. ake@si-folkesundhed.dk.
authors.forename: Annette Kjær
authors.initials: AK
authors.lastname: Ersbøll
authors.affiliation: National Institute of Public health, University of Southern Denmark, Copenhagen, Denmark. jst@si-folkesundhed.dk.
authors.forename: Janne Schurmann
authors.initials: JS
authors.lastname: Tolstrup
authors.affiliation: Danish Institute for Medical Simulation, University of Copenhagen, Copenhagen, Denmark. doris.OEstergaard@regionh.dk.
authors.forename: Doris
authors.initials: D
authors.lastname: Østergaard
authors.affiliation: Emergency Medical Services Copenhagen, University of Copenhagen, Copenhagen, Denmark. soeren.viereck@regionh.dk.
authors.forename: Søren
authors.initials: S
authors.lastname: Viereck
authors.affiliation: International Academies of Emergency Dispatch, Salt Lake City, Utah, USA. Jerry.Overton@emergencydispatch.org.
authors.forename: Jerry
authors.initials: J
authors.lastname: Overton
authors.affiliation: Emergency Medical Services Copenhagen, University of Copenhagen, Copenhagen, Denmark. ff@heart.dk.
authors.forename: Fredrik
authors.initials: F
authors.lastname: Folke
authors.affiliation: Emergency Medical Services Copenhagen, University of Copenhagen, Copenhagen, Denmark. freddy.lippert@regionh.dk.
authors.forename: Freddy
authors.initials: F
authors.lastname: Lippert
mesh_terms: D000552:Ambulances / Q000706:statistics & numerical data*; D016208:Databases, Factual; D003718:Denmark; D004630:Emergencies; D004631:Emergency Medical Service Communication Systems / Q000706:statistics & numerical data*; D004632:Emergency Medical Services / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D016012:Poisson Distribution; D011786:Quality Control; D012189:Retrospective Studies; D012307:Risk Factors; D012621:Seasons; D013997:Time Factors; D019037:Urban Health Services / Q000458:organization & administration; D014505:Urban Population