Presentation
DH12 - OptiBrain: Interface Design to Support Clinical Decisions and Patient Management of Pediatric Traumatic Brain Injury
SessionPoster Session 2
DescriptionContext. Severe Traumatic Brain Injury is one of the leading causes of death and disability in children. Managing this condition is complex and requires a multimodal approach, along with close monitoring to prevent complications, secondary injuries, or fatalities. For nearly two decades, clinical guidelines have been developed to support healthcare providers. However, these guidelines are often underutilized, especially in pediatric care. The unique nature of a child's developing brain complicates the application of these recommendations, as children exhibit varying pathological responses and neurological symptoms that differ from adults. This variability makes it challenging to apply standard guidelines, which are typically based on averages, and limits clinicians' ability to predict the trajectory of a pediatric patient's condition accurately.
Beyond the complexities of pediatric Severe Traumatic Brain Injury management, Intensive Care Units (ICU) present a high-pressure, fast-paced, and multidisciplinary environment. Managing complex cases in this setting requires the synthesis of large volumes of data, while clinicians are subject to stress and fatigue, increasing the risk of medical errors. To address these challenges, hospitals could benefit from well-designed Clinical Decision Support Systems (CDSS) to enhance clinical decision-making and promote adherence to medical guidelines. However, CDSS implementations in healthcare remain scarce, and many of the systems currently available are hampered by poor usability and suboptimal user experiences. These issues contribute to increased human error, higher workloads, and concerns over patient safety, ultimately limiting the adoption of such systems in clinical practice.
OptiBrain is a CDDS developed at CHU Sainte-Justine hospital (Montreal, QC) to improve the management of pediatric severe traumatic brain injury. Using live data from the electronic health record and bedside monitors, it computes the adherence to clinical guidelines of 14 indicators i.e., to what extent was the patient within the recommended range for each indicator, the patient's cerebral condition, and the cerebral autoregulation status including optimal cerebral perfusion pressure. For OptiBrain to make its way to the bedside, it needs a visualization interface to support the clinician's decision making.
Objective. This work developed a graphical user interface for OptiBrain, a CDSS to study the neurological system.
Method. The development process adhered to the User-Centered Design approach throughout the exploration, analysis, and generation phases. In the exploration and analysis stages, we conducted ten semi-structured interviews with healthcare professionals: seven doctors, two nurses, and one fellow. Additionally, we observed clinical staff over three days in the ICU, shadowing a nurse, a head nurse, and a doctor. These observations and interviews helped us understand end-users' needs, their working environment, and the critical indicators required for the OptiBrain system to monitor brain injury. This information guided the design process during the generation phase. We designed the OptiBrain interface over the course of ten collaborative design sessions. The sessions involved a neurologist, an ICU clinician and two human factors specialists. We iteratively refined the mockup, making necessary adjustments based on feedback. The iterative nature of User-Centered Design approach meant that we occasionally revisited previous phases to ensure the solution aligned with user needs.
Results. From the interviews, we identified 20 user requirements related to the ICU environment e.g., simplify access to CT scan, and 6 main indicators for brain injury. We created 2 user personas (ICU clinician and ICU nurse) with their task analysis to manage brain injury. The final interface design consisted of five key sections (see the full manuscript for detailed figures): the main navigation bar, a system-based navigation bar, patient records, adherence to guidelines, and real-time data. The main goal of the interface is to summarize clinical data and provide an overview of the patient’s trajectory, enhancing the clinician’s situational awareness of the neurological state and associated risk factors. Ultimately, this solution is expected to improve decision-making, reduce human error, and enhance patient safety.
Outcomes. This project successfully achieved its objectives and contributed to advancing knowledge in the field of Clinical Decision Support Systems by delivering a first-of-its-kind user interface tailored to the management of Severe Traumatic Brain Injury. Furthermore, the design criteria and recommendations formulated during this process will serve as valuable resources for future CDSS development. As no standardized communication methods currently exist, this work could have broader implications, influencing sectors such as defense and aviation, where rapid decision-making is crucial, and the cost of human error is high.
Beyond the complexities of pediatric Severe Traumatic Brain Injury management, Intensive Care Units (ICU) present a high-pressure, fast-paced, and multidisciplinary environment. Managing complex cases in this setting requires the synthesis of large volumes of data, while clinicians are subject to stress and fatigue, increasing the risk of medical errors. To address these challenges, hospitals could benefit from well-designed Clinical Decision Support Systems (CDSS) to enhance clinical decision-making and promote adherence to medical guidelines. However, CDSS implementations in healthcare remain scarce, and many of the systems currently available are hampered by poor usability and suboptimal user experiences. These issues contribute to increased human error, higher workloads, and concerns over patient safety, ultimately limiting the adoption of such systems in clinical practice.
OptiBrain is a CDDS developed at CHU Sainte-Justine hospital (Montreal, QC) to improve the management of pediatric severe traumatic brain injury. Using live data from the electronic health record and bedside monitors, it computes the adherence to clinical guidelines of 14 indicators i.e., to what extent was the patient within the recommended range for each indicator, the patient's cerebral condition, and the cerebral autoregulation status including optimal cerebral perfusion pressure. For OptiBrain to make its way to the bedside, it needs a visualization interface to support the clinician's decision making.
Objective. This work developed a graphical user interface for OptiBrain, a CDSS to study the neurological system.
Method. The development process adhered to the User-Centered Design approach throughout the exploration, analysis, and generation phases. In the exploration and analysis stages, we conducted ten semi-structured interviews with healthcare professionals: seven doctors, two nurses, and one fellow. Additionally, we observed clinical staff over three days in the ICU, shadowing a nurse, a head nurse, and a doctor. These observations and interviews helped us understand end-users' needs, their working environment, and the critical indicators required for the OptiBrain system to monitor brain injury. This information guided the design process during the generation phase. We designed the OptiBrain interface over the course of ten collaborative design sessions. The sessions involved a neurologist, an ICU clinician and two human factors specialists. We iteratively refined the mockup, making necessary adjustments based on feedback. The iterative nature of User-Centered Design approach meant that we occasionally revisited previous phases to ensure the solution aligned with user needs.
Results. From the interviews, we identified 20 user requirements related to the ICU environment e.g., simplify access to CT scan, and 6 main indicators for brain injury. We created 2 user personas (ICU clinician and ICU nurse) with their task analysis to manage brain injury. The final interface design consisted of five key sections (see the full manuscript for detailed figures): the main navigation bar, a system-based navigation bar, patient records, adherence to guidelines, and real-time data. The main goal of the interface is to summarize clinical data and provide an overview of the patient’s trajectory, enhancing the clinician’s situational awareness of the neurological state and associated risk factors. Ultimately, this solution is expected to improve decision-making, reduce human error, and enhance patient safety.
Outcomes. This project successfully achieved its objectives and contributed to advancing knowledge in the field of Clinical Decision Support Systems by delivering a first-of-its-kind user interface tailored to the management of Severe Traumatic Brain Injury. Furthermore, the design criteria and recommendations formulated during this process will serve as valuable resources for future CDSS development. As no standardized communication methods currently exist, this work could have broader implications, influencing sectors such as defense and aviation, where rapid decision-making is crucial, and the cost of human error is high.
Event Type
Poster Presentation
TimeTuesday, April 14:45pm - 6:15pm EDT
LocationFrontenac Foyer