Prevalence and Predictors of Delay in Seeking Emergency Care in Patients Who Call 9-1-1 for Chest Pain

J Emerg Med. 2019 Nov;57(5):603-610. doi: 10.1016/j.jemermed.2019.07.012. Epub 2019 Oct 12.

Abstract

Background: Delay in seeking medical treatment for suspected acute coronary syndrome can lead to negative patient outcomes.

Objective: Our aim was to evaluate the prevalence and predictors of delay in seeking care in high-risk chest pain patients with or without acute coronary syndrome (ACS).

Methods: This was a secondary analysis of an observational cohort study of patients transported by Emergency Medical Services for a chief complaint of chest pain. Important demographic and clinical characteristics were extracted from electronic health records. Two independent reviewers adjudicated the presence of ACS. Logistic regression was used to model the predictors of delay in seeking care.

Results: The final sample included 743 patients (99% non-Hispanic). Overall, 24% presented > 12 h from onset of symptoms. Among those with ACS (n = 115), 14% presented > 12 h after onset of symptoms. Race, smoking, diabetes, and related symptoms were associated with delayed seeking behavior. In multivariate analysis, non-Caucasian race (black or others) was the only independent predictor of > 12 h delay in seeking care (odds ratio 1.4; 95% confidence interval 1.0-1.9).

Conclusions: One in four patients with chest pain, including 14% of those with ACS, wait more than 12 h before seeking care. Compared to non-blacks, black patients are 40% more likely to delay seeking care > 12 h.

Keywords: acute coronary syndrome; chest pain; delay; emergency care.

Publication types

  • Observational Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Chest Pain / psychology*
  • Chest Pain / therapy
  • Cohort Studies
  • Delayed Diagnosis
  • Emergency Medical Services / methods
  • Emergency Service, Hospital / organization & administration
  • Emergency Service, Hospital / statistics & numerical data
  • Female
  • Help-Seeking Behavior*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Prevalence*
  • Prospective Studies
  • Time Factors