Visiting Black Patients: Racial Disparities in Security Standby Requests

J Natl Med Assoc. 2018 Feb;110(1):37-43. doi: 10.1016/j.jnma.2017.10.009. Epub 2017 Nov 26.

Abstract

Background: Structural inequalities exist within healthcare. Racial disparities in hospital security standby requests (SSRs) have not been previously explored. We speculated hospital SSRs varied based upon race with black patients and their visitors negatively impacted.

Methods: An 8-year retrospective study of hospital security dispatch information was performed. Data were analyzed to determine demographic information, and service location patterns for SSRs involving patients and their visitors. The race of the patient's visitors was imputed using the patient's race. The observed and expected (using hospital census data) number of patients impacted by SSRs was compared. Descriptive statistics were computed. Categorical data were analyzed using chi-square or Fisher exact test statistic. A p < 0.05 was statistically significant.

Results: The majority of the 1023 SSRs occurred for visitors of patients who were white (N = 642; 63%), female (56%), or < 21 years old (50.7%). However, SSRs differed significantly based upon the patient's race. Although Black patients represent 12% of the hospital population, they and their visitors were more than twice as likely (p < 0.0001) to have a SSR generated (N = 275; 27%) when compared to the visitors of both White and other (i.e., race unknown) patients (N = 106; 10%) combined (p < 0.0001).

Conclusion: This study adds to the medical errors and healthcare disparities literature by being the first to describe racial disparities in SSRs for Black patients and their visitors. It also introduces the concept of "security intervention errors in healthcare environments." New metrics and continuous quality improvement initiatives are needed to understand and eliminate racial/ethnic based disparities in SSRs.

Keywords: Health and healthcare disparities and inequities; Medical errors; Racial disparities and inequities; Security intervention errors in healthcare environments.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Continental Population Groups*
  • Delivery of Health Care / standards*
  • Female
  • Follow-Up Studies
  • Health Care Surveys
  • Health Services Accessibility / statistics & numerical data*
  • Healthcare Disparities / ethnology*
  • Humans
  • Male
  • Middle Aged
  • Quality of Health Care*
  • Retrospective Studies
  • Socioeconomic Factors
  • Time Factors
  • United States
  • Young Adult