Computer-aided decision support for trauma reception and resuscitation

Background: This project spanning six years tested the hypothesis that computer-aided decision support during the first 30 minutes of trauma resuscitation reduces management errors. Methods: This was a prospective, open, randomized controlled, interventional study that evaluated the effect of real time, computer prompted, evidence-based decision and action algorithms on error occurrence during the initial resuscitation of severely injured adults. The primary outcome variable was the ‘error rate per patient treated’ as demonstrated by deviation from trauma care algorithms. Computer assisted video audit was used to assess adherence to the algorithms. Results: A total of 1171 patients were recruited into three groups – 300 into a Baseline Control Group, 436 into a concurrent Control Group and 435 into the Study Group. There was a reduction in error rate per patient from the Baseline Control Group to the Study Group (2.53 to 2.13, p=0.004) and between the Control Group to the Study Group (2.30 to 2.13, p=0.042). The difference in error rate per patient between the Baseline Control Group and the concurrent Control Group was not statistically different (2.53 to 2.30, p=0.210). A critical decision was required every 72 seconds and error free resuscitations were increased from 16% to 21.8% (p=0.049) during the first 30 minutes of resuscitation. Morbidity from shock management (p< 0.025), blood use (p< 0.0001) and aspiration pneumonia (p=0.046) were decreased. Conclusions: This was the first study to demonstrate that computer-aided, real time decision support used by experienced trauma teams resulted in improved protocol compliance and reduced errors and morbidity. Clinical Trials Identifier:NCT00164034.