Optimizing a decision support system for damage-control resuscitation using mixed methods human factors analysis

Abstract

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.

Open versus percutaneous tube thoracostomy with and without thoracic lavage for traumatic hemothorax: a novel randomized controlled simulation trial

“…Simulation provides a means to control these challenging environments to best prepare for subsequent studies in the less structured, real-world environment. As an example, a recent study on optimizing a decision support system for damage-control resuscitation used precisely this strategy to iteratively improve a tool through simulation before deploying it for evaluation in a clinical setting 19. We hope that this study will similarly lay the groundwork for further research on HTX management in a clinical setting.…”

Surgical Science and the Evolution of Critical Care Medicine

“…Evolving end points that signal successful hemorrhagic shock resuscitation help inform the timing of planned reexploration for definitive surgical management and help avoid postsurvival complications such as multiple organ failure (67, 68). Developing approaches to more precisely guide timing include decision support tools to facilitate optimal resuscitation; in silico modeling to plan clinical trials, novel monitoring, and management strategies such as microcirculation dark field microscopy, and trigeminal nerve stimulation (69–72). Perhaps most importantly, each of these approaches is not solely applicable to surgical patients.…”

Clinical decision support versus a paper‐based protocol for massive transfusion: Impact on decision outcomes in a simulation study

“…Multiple CDS tools have been developed for transfusion decision-making with most applying only to nonemergent bleeding transfusion support. 10,[23][24][25] Schmulevich and colleagues developed a CDS for Damage Control Resuscitation, a management approach to major hemorrhage that encompasses MT and damage control surgery, using an iterative human factors focused development approach that involved evaluation in both simulated and clinical environments. 10 This tool, Blood Navigator (Arcos Medical, Texas, USA), utilizes a number of similar features to MTP Assistant, including blood transfusion tally and ratios, TEG interpretation, integrated protocol, and adjunct administration documentation, and operates via a portable tablet device.…”

“…10,[23][24][25] Schmulevich and colleagues developed a CDS for Damage Control Resuscitation, a management approach to major hemorrhage that encompasses MT and damage control surgery, using an iterative human factors focused development approach that involved evaluation in both simulated and clinical environments. 10 This tool, Blood Navigator (Arcos Medical, Texas, USA), utilizes a number of similar features to MTP Assistant, including blood transfusion tally and ratios, TEG interpretation, integrated protocol, and adjunct administration documentation, and operates via a portable tablet device. 10 In contrast to MTP Assistant, Blood Navigator does not retrieve patient laboratory results, requires manual entry of TEG results for interpretation, does not allow multiple simultaneous user input, and does not track blood products from blood bank to patient.…”

“…7 To support clinical teams managing similarly challenging and unpredictable scenarios, cognitive aids and computerized clinical decision support systems (CDS) have been developed to support consistent and evidence-based clinical decisionmaking in areas such as trauma and blood transfusions generally, but only one tool has previously been developed specifically for MT. [8][9][10] CDS may contain algorithms that generate generic as well as patient-specific recommendations by comparing patient results to a knowledge base. 11 In MT, a CDS could allow the latest laboratory results to be immediately compared to transfusion goals and provide targeted recommendations to guide subsequent transfusion and other time-critical interventions.…”