title: Pre-hospital delay in patients with acute coronary syndrome: factors associated with patient decision time and home-to-hospital delay.
abstract: BACKGROUND
  Pre-hospital delays in patients experiencing acute coronary syndromes (ACS) remain unacceptably long.
  
  
  OBJECTIVE
  To examine simultaneously a wide range of clinical, sociodemographic and situational factors associated with total pre-hospital delay and its two components.
  
  
  METHODS
  Pre-hospital delay data were collected from 228 patients with ACS using patient's medical notes and semi-structured interviews. Total pre-hospital delay (symptom onset to hospital admission) was divided into 2 components: decision time (symptom onset to call for medical help), and home-to-hospital delay (call for help to hospital admission).
  
  
  RESULTS
  Shorter total pre-hospital delays and decision times were associated with ST segment myocardial infarction (STEMI), recognizing symptoms as cardiac in origin, being married, symptom onset outside the home and the presence of a bystander. Shorter home-to-hospital delays were more likely among younger patients, those experiencing an STEMI, and patients reporting a greater number of symptoms. Initial contact with emergency medical services was related to shorter total delays and decision times.
  
  
  CONCLUSIONS
  Different factors were associated with shorter times in the 2 component phases. Greater understanding of the factors impacting on the component phases may help target interventions more effectively and reduce pre-hospital delays.
authors.affiliation: Department of Epidemiology & Public Health, University College London, London, UK. l.porras@ucl.ac.uk
authors.forename: Linda
authors.initials: L
authors.lastname: Perkins-Porras
authors.forename: Daisy L
authors.initials: DL
authors.lastname: Whitehead
authors.forename: Philip C
authors.initials: PC
authors.lastname: Strike
authors.forename: Andrew
authors.initials: A
authors.lastname: Steptoe
mesh_terms: D054058:Acute Coronary Syndrome / Q000453:epidemiology* / Q000523:psychology* / Q000628:therapy; D000368:Aged; D002755:Choice Behavior; D003657:Decision Making; D004632:Emergency Medical Services / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D017533:Marital Status / Q000706:statistics & numerical data; D008875:Middle Aged; D015999:Multivariate Analysis; D009203:Myocardial Infarction / Q000453:epidemiology / Q000523:psychology / Q000628:therapy; D011237:Predictive Value of Tests; D012307:Risk Factors; D012959:Socioeconomic Factors; D013997:Time Factors; D014187:Transportation of Patients / Q000706:statistics & numerical data*