title: How emergency departments might alert for prehospital heat-related excess mortality?
abstract: BACKGROUND
  A major issue raised by the public health consequences of a heat wave is the difficulty of detecting its direct consequences on patient outcome, particularly because of the delay in obtaining definitive mortality results. Since emergency department (ED) activity reflects the global increase of patients' health problems during this period, the profile of patients referred to EDs might be a basis to detect an excess mortality in the catchment area. Our objective was to develop a real-time surveillance model based on ED data to detect excessive heat-related mortality as early as possible.
  
  
  METHODS
  A day-to-day composite indicator was built using simple and easily obtainable variables related to patients referred to the ED during the 2003 heat-wave period. The design involved a derivation and validation study based on a real-time surveillance system of two EDs at Cochin Hospital and Hôtel-Dieu Hospital, Paris, France. The participants were 99,976 adult patients registered from 1 May to 30 September during 2001, 2002 and 2003. Among these participants, 3,297, 3,580 and 3,851 patients were referred to the EDs from 3 August to 19 August for 2001, 2002 and 2003, respectively. Variables retained for the indicator were selected using the receiver operating characteristic curve methodology and polynomial regression.
  
  
  RESULTS
  The indicator was composed of only three variables: the percentage of patients older than 70 years, the percentage of patients with body temperature above 39 degrees C, and the percentage of patients admitted to or who died in the ED. The curve of the indicator with time appropriately fitted the overall mortality that occurred in the region of interest.
  
  
  CONCLUSIONS
  A composite and simple index based on real-time surveillance was developed according to the profile of patients who visited the ED. It appeared suitable for determining the overall mortality in the corresponding region submitted to the 2003 heat wave. This index should help early warning of excessive mortality and monitoring the efficacy of public health interventions.
authors.affiliation: Paris Descartes University, Faculty of Medicine, Assistance Publique--Hôpitaux de Paris, Department of Emergency Medicine, Hôpital Cochin, Paris Cedex 14, France. yann-erick.claessens@cch.ap-hop-paris.fr
authors.forename: Yann-Erick
authors.initials: YE
authors.lastname: Claessens
authors.forename: Pierre
authors.initials: P
authors.lastname: Taupin
authors.forename: Gérald
authors.initials: G
authors.lastname: Kierzek
authors.forename: Jean-Louis
authors.initials: JL
authors.lastname: Pourriat
authors.forename: Michel
authors.initials: M
authors.lastname: Baud
authors.forename: Christine
authors.initials: C
authors.lastname: Ginsburg
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Jais
authors.forename: Eric
authors.initials: E
authors.lastname: Jougla
authors.forename: Bruno
authors.initials: B
authors.lastname: Riou
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Dhainaut
authors.forename: Paul
authors.initials: P
authors.lastname: Landais
mesh_terms: D000328:Adult; D000367:Age Factors; D001831:Body Temperature; D002980:Climate; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D017052:Hospital Mortality / Q000639:trends*; D006358:Hot Temperature / Q000009:adverse effects*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011159:Population Surveillance / Q000379:methods*; D011634:Public Health; D018570:Risk Assessment