title: Extrication time prediction tool.
abstract: BACKGROUND
  Many patients will require extrication following a motor vehicle collision (MVC). Little information exists on the time taken for extrication or the factors which affect this time.
  
  
  OBJECTIVE
  To derive a tool to predict the time taken to extricate patients from MVCs.
  
  
  METHODS
  A prospective, observational derivation study was carried out in the West Midland Fire Service's metropolitan area. An expert group identified factors that may predict extrication time-the presence and absence of these factors was prospectively recorded at eligible extrications for the study period. A step-down multiple regression method was used to identify important contributing factors.
  
  
  RESULTS
  Factors that increased extrication times by a statistically significant extent were: a physical obstruction (10 min), patients medically trapped (10 min per patient) and any patient physically trapped (7 min). Factors that shortened extrication time were rapid access (-7 min) and the car being on its roof (-12 min). All these times were calculated from an arbitrary time (which assumes zero patients) of 8 min.
  
  
  CONCLUSIONS
  This paper describes the development of a tool to predict extrication time for a trapped patient. A number of factors were identified which significantly contributed to the overall extrication time.
authors.affiliation: The Emergency Department, Derriford Hospital Plymouth, UK.
authors.forename: Tim
authors.initials: T
authors.lastname: Nutbeam
authors.affiliation: Emergency Department, Shrewsbury and Telford Hospitals NHS Trust, Telford, UK.
authors.forename: Rob
authors.initials: R
authors.lastname: Fenwick
authors.affiliation: West Midlands Fire Service, Birmingham, UK.
authors.forename: Charles
authors.initials: C
authors.lastname: Hobson
authors.affiliation: Integrated Risk Management, West Midlands Fire Service, Birmingham, UK.
authors.forename: Vikki
authors.initials: V
authors.lastname: Holland
authors.affiliation: Keele University, Keele, UK.
authors.forename: Michael
authors.initials: M
authors.lastname: Palmer
mesh_terms: D000063:Accidents, Traffic; D004632:Emergency Medical Services; D006801:Humans; D011446:Prospective Studies; D012044:Regression Analysis; D013997:Time Factors; D006113:United Kingdom
keywords: Prehospital Care, Advanced Practitioner; Prehospital Care, Clinical Management; Prehospital Care, Despatch; Trauma, Research