Abstract
Introduction: The efficient utilization of resources is a crucial aspect of healthcare, particularly in both Level I and Level II American College of Surgeons (ACS)-verified trauma centers. The effect of resource allocation on emergency department length of stay (ED-LOS) of trauma patients has remained under-investigated. As ED crowding has become more prevalent, especially at quaternary care centers, an evaluation of the potential disparities in ED-LOS between Level I and Level II trauma centers is warranted. We hypothesized a longer ED-LOS at Level I centers compared to Level II centers. Methods: We queried the 2017–2021 Trauma Quality Improvement Process (TQIP) database for trauma patients ≥18 years of age presenting to either a Level-I or -II center. The TQIP defines ED-LOS as the time from arrival until the time an ED disposition (admission or discharge) order is written. We excluded transferred patients and those with missing data regarding ACS trauma center verification level. We performed bivariate analyses, as well as subgroup analyses based on location of disposition. Results: Of 2,225,067 trauma patients, 59.3% (1,318,497) received treatment at Level I centers. No significant differences were found in Injury Severity Scores between patients admitted to the operating room or non-intensive care unit (ICU) locations, or discharged home from Level-I and -II centers (all P < 0.05). The ED-LOS for trauma patients was longer at Level-I centers for all patient categories: overall (198 vs 145 minutes [min], P < 0.001), discharged home (286 vs 160 min, P < 0.001), non-ICU admissions (234 vs 164 min, P < 0.001), and those requiring surgery (126 vs 101 min, P < 0.001). Conclusion: Even when treating patients with similar injury severity, trauma patients at Level I trauma centers had longer ED-LOS compared to Level II centers, irrespective of the patients’ final disposition (surgery, non-ICU admission, or discharge). To optimize resource utilization and alleviate ED saturation, further research must delve into the underlying causes of these discrepancies to identify best practices and solutions.
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