Patient sex, racial and ethnic disparities in emergency department triage: A multi-site retrospective study.

OBJECTIVES: There is limited evidence on sex, racial, and ethnic disparities in Emergency Department (ED) triage across diverse settings. We evaluated differences in the assignment of Emergency Severity Index (ESI) by patient sex and race/ethnicity, accounting for age, clinical factors, and ED operating conditions. METHODS: We conducted a multi-site retrospective study of adult patients presenting to high-volume EDs from January 2019-February 2020. Patient-level data were obtained and analyzed from three EDs (academic, metropolitan community, and rural community) affiliated with a large health system in the Southeastern United States. For the study outcome, ESI levels were grouped into three categories: 1-2 (highest acuity), 3, and 4-5 (lowest acuity). Multinomial logistic regression was used to compare ESI categories by patient race/ethnicity and sex jointly (referent = White males), adjusted for patient age, insurance status, ED arrival mode, chief complaint category, comorbidity score, time of day, day of week, and average ED wait time. RESULTS: We identified 186,840 eligible ED visits with 56,417 from the academic ED, 69,698 from the metropolitan community ED, and 60,725 from the rural community ED. Patient cohorts between EDs varied by patient age, race/ethnicity, and insurance status. The majority of patients were assigned ESI 3 in the academic and metropolitan community EDs (61% and 62%, respectively) whereas 47% were assigned ESI 3 in the rural community ED. In adjusted analyses, White females were less likely to be assigned ESI 1-2 compared to White males although both groups were roughly comparable in the assignment of ESI 4-5. Non-White and Hispanic females were generally least likely to be assigned ESI 1-2 in all EDs. Interactions between ED wait time and race/ethnicity-sex were not statistically significant. CONCLUSIONS: This retrospective study of adult ED patients revealed sex and race/ethnicity-based differences in ESI assignment, after accounting for age, clinical factors, and ED operating conditions. These disparities persisted across three different large EDs, highlighting the need for ongoing research to address inequities in ED triage decision-making and associated patient-centered outcomes.

Identifying Patient Subpopulations with Significant Race-Sex Differences in Emergency Department Disposition Decisions.

Background/objectives: The race-sex differences in emergency department (ED) disposition decisions have been reported widely. Our objective is to identify demographic and clinical subgroups for which this difference is most pronounced, which will facilitate future targeted research on potential disparities and interventions. Methods: We performed a retrospective analysis of 93 987 White and African-American adults assigned an Emergency Severity Index of 3 at 3 large EDs from January 2019 to February 2020. Using random forests, we identified the Elixhauser comorbidity score, age, and insurance status as important variables to divide data into subpopulations. Logistic regression models were then fitted to test race-sex differences within each subpopulation while controlling for other patient characteristics and ED conditions. Results: In each subpopulation, African-American women were less likely to be admitted than White men with odds ratios as low as 0.304 (95% confidence interval (CI): [0.229, 0.404]). African-American men had smaller admission odds compared to White men in subpopulations of 41+ years of age or with very low/high Elixhauser scores, odds ratios being as low as 0.652 (CI: [0.590, 0.747]). White women were less likely to be admitted than White men in subpopulations of 18 to 40 or 41 to 64 years of age, with low Elixhauser scores, or with Self-Pay or Medicaid insurance status with odds ratios as low as 0.574 (CI: [0.421, 0.784]). Conclusions: While differences in likelihood of admission were lessened by younger age for African-American men, and by older age, higher Elixhauser score, and Medicare or Commercial insurance for White women, they persisted in all subgroups for African-American women. In general, patients of age 64 years or younger, with low comorbidity scores, or with Medicaid or no insurance appeared most prone to potential disparities in admissions.

Disparities in emergency department prioritization and rooming of patients with similar triage acuity score.

BACKGROUND: We identify patient demographic and emergency department (ED) characteristics associated with rooming prioritization decisions among ED patients who are assigned the same triage acuity score. METHODS: We performed a retrospective analysis of adult ED patients with similar triage acuity, as defined as an Emergency Severity Index (ESI) of 3, at a large academic medical center, during 2019. Violations of a first-come-first-served (FCFS) policy for rooming are identified and used to create weighted multiple logistic regression models and 1:M matched case-control conditional logistic regression models to determine how rooming prioritization is affected by individual patient age, sex, race, and ethnicity after adjusting for patient clinical and time-varying ED operational characteristics. RESULTS: A total of 15,781 ED encounters were analyzed, with 1612 (10.2%) ED encounters having a rooming prioritization in violation of a FCFS policy. Patient age and race were found to be significantly associated with being prioritized in violation of FCFS in both logistic regression models. The 1:M matched model showed a statistically significant relationship between violation of rooming prioritization with increasing age in years (adjusted odds ratio [aOR] 1.009, 95% confidence interval [CI] 1.005-1.013) and among African American patients compared to Caucasians (aOR 0.636, 95% CI 0.545-0.743). CONCLUSIONS: Among ED patients with a similar triage acuity (ESI 3), we identified patient age and patient race as characteristics that were associated with deviation from a FCFS prioritization in ED rooming decisions. These findings suggest that there may be patient demographic disparities in ED rooming decisions after adjusting for clinical and ED operational characteristics.

ReSTART: A Novel Framework for Resource-Based Triage in Mass-Casualty Events.

OBJECTIVE: Current guidelines for mass-casualty triage do not explicitly use information about resource availability. Even though this limitation has been widely recognized, how it should be addressed remains largely unexplored. The authors present a novel framework developed using operations research methods to account for resource limitations when determining priorities for transportation of critically injured patients. To illustrate how this framework can be used, they also develop two specific example methods, named ReSTART and Simple-ReSTART, both of which extend the widely adopted triage protocol Simple Triage and Rapid Treatment (START) by using a simple calculation to determine priorities based on the relative scarcity of transportation resources. METHODS: The framework is supported by three techniques from operations research: mathematical analysis, optimization, and discrete-event simulation. The authors? algorithms were developed using mathematical analysis and optimization and then extensively tested using 9,000 discrete-event simulations on three distributions of patient severity (representing low, random, and high acuity). For each incident, the expected number of survivors was calculated under START, ReSTART, and Simple-ReSTART. A web-based decision support tool was constructed to help providers make prioritization decisions in the aftermath of mass-casualty incidents based on ReSTART. RESULTS: In simulations, ReSTART resulted in significantly lower mortality than START regardless of which severity distribution was used (paired t test, p<.01). Mean decrease in critical mortality, the percentage of immediate and delayed patients who die, was 8.5% for low-acuity distribution (range ?2.2% to 21.1%), 9.3% for random distribution (range ?0.2% to 21.2%), and 9.1% for high-acuity distribution (range ?0.7% to 21.1%). Although the critical mortality improvement due to ReSTART was different for each of the three severity distributions, the variation was less than 1 percentage point, indicating that the ReSTART policy is relatively robust to different severity distributions. CONCLUSIONS: Taking resource limitations into account in mass-casualty situations, triage has the potential to increase the expected number of survivors. Further validation is required before field implementation; however, the framework proposed in here can serve as the foundation for future work in this area.