Designing Real‐time Decision Support for Trauma Resuscitations

Abstract

Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed. Results Among 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert–video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low. Conclusions An eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians.

Improving Team-Based Decision Making Using Data Analytics and Informatics: Protocol for a Collaborative Decision Support Design

“…We will observe each scenario until the team reaches a consensus about the diagnosis. Previous studies have observed 32 to 50 cases for reaching data saturation [43,45-47].…”

Using a Clinical Workflow Analysis to Enhance eHealth Implementation Planning: Tutorial and Case Study

“…Within health care settings, one of the most common reasons eHealth apps fail to effectively increase the health outcomes they are designed to aid and improve quality of care is incompatibility between the app and clinical workflow [ 1 - 7 ]—the series of tasks conducted to complete clinical care in what order and by whom. Incompatibilities often stem from a wait-and-see method of implementation common to many eHealth interventions whereby an intervention is introduced into a clinical setting and the clinical workflow either adjusts to accommodate or does not [ 8 , 9 ]. Frequently, a lack of integration with clinical workflow results in clinical staff creating work-arounds or adaptations that interfere with the core components of the intervention [ 2 - 4 , 10 ].…”

Optimizing Clinical Decision Support in the Electronic Health Record

“…Consider as well the potentially deleterious effect of the number of "clicks" that EPs working in an EHR-enabled environment face each shift [30]. Other work suggests that CDSSs are more effective if adapted based on human factor analysis [31]. While there has been significant backlash regarding the benefits of the EHR, we know that certain aspects of it are effective -these include well-designed assistive order sets and condition-specific decision support tools [18,32].…”