Academic Emergency Medicine · 2022 · 13 citations · 21 references
Health ProfessionsEmergency Medical ServicesEmergency MedicineEmergencyPatient SafetyPrehospital Emergency CareEmergency TriagePatient PrioritizationPriority DeterminationAge-specific TriageEmergency Case PrioritizationPatient Demographic VariablesPatient TriagePrioritizationSeverity Index MeasurementTriage Acuity ScoringTriage Prioritization
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.
21
Comorbidity Measures for Use with Administrative Data
Anne Elixhauser, Claudia Steiner, D.R. Harris et al. · Medical Care · 1998 · 9.9K citations
Education, Health Services Administration, Health Assessment +16
Matching to Remove Bias in Observational Studies
Donald B. Rubin · Biometrics · 1973 · 728 citations