@article{6944,
  author = {Mark FitzGerald and Peter Cameron and Colin F. Mackenzie and Nathan Farrow and Pamela Scicluna and Robert Gocentas and Adam Bystrzycki and Geraldine Lee and Gerard O'Reilly and Nick Andrianopoulos and Linas Dziukas and Jamie Cooper and Andrew Silvers and Alfredo Mori and Angela Murray and Susan M. Smith and Yan Xiao and Dion Stub and Frank T. McDermott and Jeffrey Rosenfeld V},
  title = {Trauma resuscitation errors and computer-assisted decision support.},
  abstract = {<p><b>HYPOTHESIS: </b>This project tested the hypothesis that computer-aided decision support during the first 30 minutes of trauma resuscitation reduces management errors.</p><p><b>DESIGN: </b>Ours 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 initial resuscitation between January 24, 2006, and February 25, 2008.</p><p><b>SETTING: </b>A level I adult trauma center.</p><p><b>PATIENTS: </b>Severely injured adults.</p><p><b>MAIN OUTCOME MEASURES: </b>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.</p><p><b>RESULTS: </b>A total of 1171 patients were recruited into 3 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 = .004) and from the control group to the study group (2.30 to 2.13, P = .04). The difference in error rate per patient from the baseline control group to the concurrent control group was not statistically different (2.53 to 2.30, P = .21). A critical decision was required every 72 seconds, and error-free resuscitations were increased from 16.0% to 21.8% (P = .049) during the first 30 minutes of resuscitation. Morbidity from shock management (P = .03), blood use (P < .001), and aspiration pneumonia (P = .046) were decreased.</p><p><b>CONCLUSIONS: </b>Computer-aided, real-time decision support resulted in improved protocol compliance and reduced errors and morbidity. Trial Registration clinicaltrials.gov Identifier: NCT00164034.</p>},
  year = {2011},
  journal = {Arch Surg},
  volume = {146},
  pages = {218-25},
  month = {02/2011},
  issn = {1538-3644},
  doi = {10.1001/archsurg.2010.333},
  language = {eng},
}