Objective: Patient delay prior to seeking treatment during an acute myocardial infarction is a significant problem. Treatment strategies to reestablish blood flow to the damaged myocardium (such as thrombolytic therapy or percutaneous transluminal coronary angioplasty) can be successful if patients arrive in the emergency department shortly after the onset of symptoms. However, various studies have documented median patient delay times that ranged between 2 to 4 hours. The purpose of this study was to identify variables that were influential in a culturally diverse population and to identify if women and African Americans were at risk for longer delays.
Design: This was a descriptive correlational study. A purposive sampling plan was used in order to ensure adequate numbers of women and African Americans.
Population, Sample, Setting Years: Data were collected at three institutions in a large Midwestern urban community. These included a suburban medical center, an inner-city county hospital, and an inner-city University medical center.
Concept or Variables Studied: The variables of interest included demographic characteristics (gender, race/ethnicity, age), contextual variables (environment, bystander influence), cognitive variables (symptom expectations, match with actual symptom pattern, risk perceptions), and time of delay during acute myocardial infarction.
Methods: Patients who were hospitalized with an acute myocardial infarction were invited to participate after they were pain-free and hemodynamically stable. Eligibility criteria included: able to speak and understand English and oriented to person, place and time. The participation rate was 88%. Reasons for refusals included fatigue, being too busy, and lack of interest. The sample included 100 women and 135 men. The women ranged in age from 35-89 (M=63.5, SD 13.7) and 39% of the women were currently married. Sixty percent of the women were non-Hispanic White and 35% were African American. The men ranged in age from 31-86 (M=59, SD=12) and 62% were currently married. The men were predominately non-Hispanic White (60%), 23% were African American, 10% Hispanic. Seventy three percent of both men and women had at least a high school education. Women were significantly older than men and less likely to be married.
Findings: The median delay time did not differ by gender (women=2.0 hours, men=2.5 hours). The median delay for African Americans (3.25 hours) was significantly longer than for non-Hispanic Whites (2.0 hours; t=2.2, p < .05). The variables contributing to delay differed both by gender and by race. For African American men, older age and the inconsistency between expected and experienced symptoms were associated with longer delay (R2=.61, p < .01). For African American women only older age was associated with a longer delay (R2=.32, p < .05). For non-Hispanic White women calling a health care provider before seeking treatment and attempting to self-treat were associated with longer delay (R2=.27, p < .01). For non-Hispanic White men the inconsistency between expected and experienced symptoms, a lower intensity of reported pain, and calling a provider were associated with longer delay (R2=.29, p < .05)
Conclusions: Women do not delay longer than men during acute myocardial infarction; however, African Americans experience significantly longer delays prior to seeking treatment than non-Hispanic Whites. The reasons why individuals delay vary by gender and race. The inconsistency between expected and experienced symptoms is an important variable for men, but not for women. Attempting to self-treat or contacting a provider are strategies that increase the time interval prior to reaching the emergency department and should be avoided. A group that may be particularly vulnerable to increased delay time is older African Americans.
Implications: In order to develop a successful intervention to reduce patient delay prior to seeking treatment for acute myocardial infarction it is important to understand the reasons for delay. Individualized interventions that target the groups at risk and their reasons for delay may be essential in order to successfully impact delay behavior.
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