Related Experiment Video
Updated: Jun 4, 2026

Setup and Execution Of the Blindfolded Code Training Exercise
Published on: March 29, 2019
Trauma resuscitation errors and computer-assisted decision support
Mark Fitzgerald1, Peter Cameron, Colin Mackenzie
1Trauma Service, Alfred Hospital, Melbourne, Victoria, Australia. m.fitzgerald@alfred.org.au
Hypothesis:
This project tested the hypothesis that computer-aided decision support during the first 30 minutes of trauma resuscitation reduces management errors.
Design:
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.
Setting:
A level I adult trauma center.
Patients:
Severely injured adults.
Main Outcome Measures:
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 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.
Conclusions:
Computer-aided, real-time decision support resulted in improved protocol compliance and reduced errors and morbidity. Trial Registration clinicaltrials.gov Identifier: NCT00164034.
Related Concept Videos
Cardiopulmonary Resuscitation III: AED Use
Cardiopulmonary Resuscitation IV: Pharmacological Management
Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
Guidelines and Strategies for Safe Computer Charting
Maintain Confidentiality and Security:
