Background: The care of trauma patients in combat operations is handwritten on a five-page flow sheet. The process requires the manual scanning and uploading of paper documents to bridge the gap between electronic and paper record management. There is an urgent operational need for an information technology solution that will enable medics to better capture patient treatment information, which will improve long-term health care without impacting short-term care responsibilities.
Methods: We conducted a process improvement project to evaluate the ability of T6 Health Systems Mobile Application to improve combat casualty care data collection at a deployed trauma hospital. We performed a head-to-head comparison of the completeness and accuracy of data capture of electronic versus handwritten records to determine noninferiority.
Results: During the 90-day pilot, there were 131 trauma evaluations of which 53 casualty resuscitations (40.5%) were also documented in the electronic application. We compared completeness and accuracy of admit, prehospital, primary survey, secondary survey, interventions, and trends data. We found an overall 13% increase in data capture at 96% accuracy compared with the written record, suggesting that the electronic record was superior. Completion of electronic documentation compared with paper by section was statistically significantly higher for admitting data, 119.7% (p < 0.0001); prehospital, 116.2% (p = 0.0039); primary, 109.6% (p < 0.001); and secondary, 125.5% (p < 0.001). We also had the medical evacuation teams document prehospital and en route care and then synchronize the record in the trauma bay, allowing the trauma teams there to continue documenting on the same casualty record, likely contributing to superiority because teams did not have to redocument based on an oral report.
Conclusion: Our pilot program in the deployed environment demonstrated a mobile technology that actually enhanced the completeness and accuracy of paper trauma documentation that has the capability of providing patient-specific decision support and real-time data analysis.
Level of evidence: Care Management, level IV.