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Optimizing a decision support system for damage-control resuscitation using mixed methods human factors analysis
Daniela Schmulevich1, Pamela Z Cacchione, Sara Holland
1From the Division of Traumatology, Surgical Critical Care & Emergency Surgery (D.S., K.Q., J.W.C.), Penn Acute Research Collaboration (PARC) (D.S., B.S.A., J.W.C.), Perelman School of Medicine at the University of Pennsylvania; Department of Nursing (P.Z.C., S.H., A.H.), Penn Presbyterian Medical Center, Penn Medicine; University of Pennsylvania School of Nursing Philadelphia (P.Z.C.); Leonard Davis Institute of Health Economics (P.Z.C., J.W.C.), University of Pennsylvania, Philadelphia, Pennsylvania; Arcos, Inc. (C.M.), Missouri City, Texas; Department of Emergency Medicine (B.S.A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Surgery (J.W.C.), Uniformed Services University of the Health Sciences, Bethesda, Maryland.
Background:
Damage-control resuscitation (DCR) improves trauma survival; however, consistent adherence to DCR principles through multiple phases of care has proven challenging. Clinical decision support may improve adherence to DCR principles. In this study, we designed and evaluated a DCR decision support system using an iterative development and human factors testing approach.
Methods:
The phases of analysis included initial needs assessment and prototype design (Phase 0), testing in a multidimensional simulation (Phase 1), and testing during initial clinical use (Phase 2). Phase 1 and Phase 2 included hands-on use of the decision support system in the trauma bay, operating room, and intensive care unit. Participants included trauma surgeons, trauma fellows, anesthesia providers, and trauma bay and intensive care unit nurses who provided both qualitative and quantitative feedback on the initial prototype and all subsequent iterations.
Results:
In Phase 0, 14 (87.5%) of 16 participants noted that they would use the decisions support system in a clinical setting. Twenty-four trauma team members then participated in simulated resuscitations with decision support where 178 (78.1%) of 228 of tasks were passed and 27 (11.8%) were passed with difficulty. Twenty-three (95.8%) completed a postsimulation survey. Following iterative improvements in system design, Phase 2 evaluation included 21 trauma team members during multiple real-world trauma resuscitations. Of these, 15 (71.4%) completed a formal postresuscitation survey. Device-level feedback on a Likert scale (range, 0-4) confirmed overall ease of use (median score, 4; interquartile range, 4-4) and indicated the system integrated well into their workflow (median score, 3; interquartile range, 2-4). Final refinements were then completed in preparation for a pilot clinical study using the decision support system.
Conclusions:
An iterative development and human factors testing approach resulted in a clinically useable DCR decision support system. Further analysis will determine its applicability in military and civilian trauma care.
Level Of Evidence:
Therapeutic/Care Management, Level V.
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