Predictors of pre-hospital delay among patients with acute myocardial infarction

Fadi M Khraim1, Mary G Carey

  • 1School of Nursing, The State University of New York at Buffalo, United States. fmkhraim@buffalo.edu

Insights

Pre-hospital delay in acute myocardial infarction (AMI) is influenced by multiple factors. Interventions should focus on reducing decision time and improving patient symptom recognition for better outcomes.

Area of Science:

  • Cardiology
  • Public Health
  • Health Services Research

Background:

  • Pre-hospital delay in acute myocardial infarction (AMI) significantly impacts patient outcomes.
  • Identifying predictors of this delay is crucial for developing effective interventions.

Purpose of the Study:

  • To systematically review and synthesize current literature on the predictors of pre-hospital delay in patients experiencing AMI.
  • To inform the development of targeted interventions to reduce patient and healthcare system delays.

Main Methods:

  • A comprehensive literature search was conducted across Medline, CINHAL, and Psych Info databases.
  • Keywords related to health beliefs, help-seeking behavior, psychosocial factors, and delay were combined with AMI for articles published between 1995 and 2008.
  • Twenty-six relevant research articles were identified and analyzed.

Main Results:

  • Pre-hospital delay in AMI varied, with median delays ranging from 1.5 to 15.2 hours.
  • Six categories of predictors were identified: socio-demographic, symptom onset context, cognitive, affective/psychological, behavioral, and clinical factors.
  • Shorter delays were observed when family/coworkers facilitated healthcare decisions and when symptoms were severe and continuous.

Conclusions:

  • Intervention programs are needed to reduce pre-hospital delay in high-risk AMI patients.
  • Future research and interventions should prioritize decision time over combined decision and transportation time.
  • Patient education should emphasize symptom awareness, recognition, and prompt action; studies should include data from non-survivors to mitigate bias.
Abstract

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