Prehospital delay interval for patients who use emergency medical services: the effect of heart-related medical conditions and demographic variables

Ann Emerg Med. 1993 Oct;22(10):1597-601. doi: 10.1016/s0196-0644(05)81267-3.


Study objective: To investigate the effect of heart-related medical conditions and demographic variables on patients' tendency to delay contacting emergency medical services for symptoms of acute myocardial infarction.

Type of participants: A sample of 2,947 patients with acute myocardial infarction but no cardiac arrest, transported by paramedics to the coronary care units of 19 hospitals in King County, Washington, between January 1988 and April 1991.

Measurements: Patient record abstracts contained information on medical history, age, gender, delay interval, and means of transportation.

Results: Multiple regression analyses showed that prehospital delay interval was significantly greater for individuals who were older and female and who had a history of angina, congestive heart failure, or diabetes.

Conclusion: It is important to investigate further how people interpret and evaluate their symptoms in light of other medical conditions. It is also critical to find out why women delay longer than men and why older individuals delay longer than younger people before they contact emergency medical services. Interventions need to be developed that are targeted at populations at risk for delaying use of emergency medical services for acute myocardial infarction symptoms. These interventions must legitimize the use of emergency medical services and encourage patients to act quickly when confronted with acute myocardial infarction symptoms.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Angina Pectoris / complications
  • Emergency Medical Services*
  • Female
  • Heart Failure / complications
  • Humans
  • Male
  • Middle Aged
  • Myocardial Infarction* / complications
  • Patient Acceptance of Health Care*
  • Regression Analysis
  • Sex Factors
  • Time Factors