Predicting patients that require care at a trauma center: Analysis of injuries and other factors

• Published in: Injury Vol. 46; no. 4; pp. 558 - 563
• Main Authors: Schoell, Samantha L, Doud, Andrea N, Weaver, Ashley A, Barnard, Ryan T, Meredith, J. Wayne, Stitzel, Joel D, Martin, R. Shayn
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01-04-2015
• Subjects: Abbreviated Injury Scale; Accidents, Traffic - statistics & numerical data; Advanced automatic crash notification (AACN); Decision Support Techniques; Emergency Medical Services - organization & administration; Humans; Motor vehicle crash; Orthopedics; Patient Transfer - organization & administration; Time Factors; Transfer; Trauma Centers - organization & administration; Trauma Severity Indices; Triage; Triage - methods; Wounds and Injuries - diagnosis; Wounds and Injuries - therapy; Advanced automatic crash notification (AACN); Motor vehicle crash; Transfer; Triage
• ISSN: 0020-1383; 1879-0267
• DOI: 10.1016/j.injury.2014.11.036

Abstract Introduction The detection of occult or unpredictable injuries in motor vehicle crashes (MVCs) is crucial in correctly triaging patients and thus reducing fatalities. The purpose of the study was to develop a metric that indicates the likelihood that an injury sustained in a MVC would require management at a Level I/II trauma centre (TC) versus a non-trauma centre (non-TC). Methods Transfer Scores (TSs) were computed for 240 injuries that comprise the top 95% most frequently occurring injuries in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) with an Abbreviated Injury Scale (AIS) severity of 2 or greater. A TS for each injury was computed using the proportions of patients involved in a MVC from the National Inpatient Sample (NIS) that were transferred to a TC or managed at a non-TC. Similarly, a TSMAIS that excludes patients with higher severity co-injuries was calculated using the proportion of patients with a maximum AIS (MAIS) equal to the AIS severity of a given injury. Results The results indicated for injuries of a given AIS severity, body region, and injury type, there were large variations in the TSMAIS . Overall results demonstrated higher TSMAIS values when injuries were internal, haemorrhagic, intracranial or of moderate severity (AIS 3–5). Specifically, injuries to the head possessed a TSMAIS that ranged from 0.000 to 0.889, with head injuries of AIS 3–5 severities being the most likely to be transferred. Discussion and conclusions The analysis indicated that the TSMAIS is not solely correlated with AIS severity and therefore it captures other important aspects of injury such as predictability and trauma system capabilities. The TS and TSMAIS can be useful in advanced automatic crash notification (AACN) research for the detection of highly unpredictable injuries in MVCs that require direct transport to a TC.