Trauma Quality Improvement: Reducing Triage Errors by Automating the Level Assignment Process.

BACKGROUND

Trauma patients are triaged by the severity of their injury or need for intervention while en route to the trauma center according to trauma activation protocols that are institution specific. Significant research has been aimed at improving these protocols in order to optimize patient outcomes while striving for efficiency in care. However, it is known that patients are often undertriaged or overtriaged because protocol adherence remains imperfect. The goal of this quality improvement (QI) project was to improve this adherence, and thereby reduce the triage error. It was conducted as part of the formal undergraduate medical education curriculum at this institution.

STUDY DESIGN

A QI team was assembled and baseline data were collected, then 2 Plan-Do-Study-Act (PDSA) cycles were implemented sequentially. During the first cycle, a novel web tool was developed and implemented in order to automate the level assignment process (it takes EMS-provided data and automatically determines the level); the tool was based on the existing trauma activation protocol. The second PDSA cycle focused on improving triage accuracy in isolated, less than 10% total body surface area burns, which we identified to be a point of common error. Traumas were reviewed and tabulated at the end of each PDSA cycle, and triage accuracy was followed with a run chart.

SETTING

This study was performed at Vanderbilt University Medical Center and Medical School, which has a large level 1 trauma center covering over 75,000 square miles, and which sees urban, suburban, and rural trauma.

PARTICIPANTS

The baseline assessment period and each PDSA cycle lasted 2 weeks. During this time, all activated, adult, direct traumas were reviewed. There were 180 patients during the baseline period, 189 after the first test of change, and 150 after the second test of change. All were included in analysis.

RESULTS

Of 180 patients, 30 were inappropriately triaged during baseline analysis (3 undertriaged and 27 overtriaged) versus 16 of 189 (3 undertriaged and 13 overtriaged) following implementation of the web tool (p = 0.017 for combined errors). Overtriage dropped further from baseline to 10/150 after the second test of change (p = 0.005). The total number of triaged patients dropped from 92.3/week to 75.5/week after the second test of change. There was no statistically significant change in the undertriage rate.

CONCLUSION

The combination of web tool implementation and protocol refinement decreased the combined triage error rate by over 50% (from 16.7%-7.9%). We developed and tested a web tool that improved triage accuracy, and provided a sustainable method to enact future quality improvement. This web tool and QI framework would be easily expandable to other hospitals.