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UID:HFESHCS_2025 International Symposium on Human Factors and Ergonomics i
 n Health Care_sess127_INDLEC170@linklings.com
SUMMARY:Usability Evaluation of OptiBrain, a Clinical Decision Support Sys
 tem for Traumatic Brain Injury
DESCRIPTION:Oral Presentations\n\nEmilie Grandgirard (Université de Lorrai
 ne, CHU Sainte-Justine); Sandrine Laliberté (Polytechnique Montréal, CHU S
 ainte-Justine); Marie-Jade Marcil (Polytechnique Montréal); Philippe Jouve
 t (CHU Sainte-Justine); Tomás Dorta (Université de Montréal); Guillaume Ém
 eriaud (CHU Sainte-Justine); and Philippe Doyon-Poulin (Polytechnique Mont
 réal)\n\nContext: Since their first implementation in the 1980s, Clinical 
 Decision Support Systems (CDSS) have significantly evolved, having a profo
 und impact on the healthcare field. These systems assist clinicians in mak
 ing complex decisions by compiling clinical data from different sources an
 d presenting an inference model to support clinical reasoning. Their use i
 s often associated with improved clinician performance and better clinical
  outcomes for patients. However, despite their potential in the medical se
 ctor, adoption of CDSS remains limited in practice due to intercompatibili
 ty issues, change in medical practices and poor usability. It is therefore
  essential to adopt a user-centered perspective in the design of CDSS and 
 evaluate its usability to integrate the CDSS more harmoniously into clinic
 ians' workflows. \nRecent work at CHU Sainte-Justine hospital (Montreal, Q
 C) developed OptiBrain, a CDDS to manage pediatric severe traumatic brain 
 injury. Using live data from the electronic health record and bedside moni
 tors, it computes the adherence to clinical guidelines of 14 indicators i.
 e., to what extent was the patient within the recommended range for each i
 ndicator, the patient's cerebral condition, and the cerebral autoregulatio
 n status including optimal cerebral perfusion pressure. A graphical user i
 nterface was designed for OptiBrain through iterative cycles involving cli
 nicians and human factors specialists. It consists of 5 main information a
 reas (see the full manuscript for detailed figures): main navigation bar, 
 system-based navigation bar, patient records, adherence to guidelines, and
  real-time data. Before OptiBrain can make its way to the patient’s bedsid
 e, it requires an usability evaluation with realistic patient data. This w
 ill ensure fixing usability problems found in tests before its deployment 
 and improve clinicians’ acceptance of OptiBrain within the intensive care 
 unit.\n\nObjective: In this work, we conducted an usability evaluation of 
 OptiBrain, using realistic patient data. The evaluation aimed to ensure th
 e proper implementation of a new system within the intensive care unit at 
 CHU Sainte-Justine, as no similar initiative has been undertaken thus far.
 \n\nMethodology: 8 participants took part in the study: 4 intensive care p
 hysicians with an average clinical experience of 17 years, and 4 fellows w
 ith an average clinical experience of 3 years. Only 2 participants had pri
 or exposure to OptiBrain.\nClinical case. We used a realistic case of a 13
  year old patient following a bike accident. The case was presented in two
  phases: phase 1 was the most acute phase as the patient has just been tak
 en in charge and experienced several intracranial pressure peaks; phase 2 
 was on the second day after the patient had a craniectomy surgery and was 
 more stable.\nMaterial. We implemented the OptiBrain mockup as an interact
 ive prototype using Figma and populated its data using realistic patient’s
  information. Test was conducted in-person with 6 participants and remotel
 y with 2 participants. In both cases participants interacted with the prot
 otype from a laptop. \nProcedure. Before the test, we briefed participants
  on OptiBrain and let them familiarize with the interface. Then we present
 ed the clinical case: phase 1, followed by phase 2. We asked participants 
 to verbalize their clinical evaluation of the patient’s condition using Op
 tiBrain. Participants’ verbalizations allowed us to analyze the clinicians
  cognitive processes. We analyzed the transcript using three main coding c
 ategories: clinical reasoning, usability interactions, and user suggestion
 s. The session lasted 1 hour.\n\nResults: Clinical reasoning. Clinicians f
 irst scanned the interface and reviewed key parameters like ICP and CPAP t
 o support their diagnoses. They employed non-analytical processes to expla
 in the shape of curves, while using analytical reasoning, or clinical scri
 pting, for case management strategies. They formed hypotheses based on the
 ir knowledge and experience, as seen when one clinician questioned the acc
 uracy of arterial pressures. OptiBrain facilitated the transition between 
 non-analytical and analytical approaches, allowing practitioners to genera
 te and refine hypotheses, while simultaneously investigating off-target pa
 rameters to better understand their origins.\nInteraction. Clinicians appr
 eciated the inclusion of key parameters like ICP, MAP, and ETCO2. They als
 o understood the neurological parameters presented and actively explored o
 ther systems, demonstrating engagement with the interface. However, there 
 were notable usability issues. Navigation difficulties were reported, espe
 cially in accessing key parameters and understanding how to change the tim
 e window of the data displayed. The adherence banner cluttered the interfa
 ce during the acute phase, as clinicians had to scroll down to see the par
 ameters of interest. Clinicians also reported some parameters were missing
  like EVD and SaO2. Additionally, the optimal CPP, a new concept for users
 , required further clarification to clinicians less familiar with neurolog
 ical diagnosis.\nSuggestions. The interviews allowed us to gather several 
 relevant suggestions from clinicians, particularly regarding the represent
 ation of data over time. Many found it challenging to understand the conne
 ction between hour-based navigation and the real-time data displayed at th
 e bottom of the screen. Additionally, clinicians emphasized the importance
  of having more information available on the graphs used to analyze real-t
 ime indicators and the need for clearer axis labeling. Significant work wi
 ll be needed to ensure a more efficient interaction between time managemen
 t and patient progress.Our results also revealed clinicians’ interest in r
 educing visual overload and rethinking the prioritization of certain infor
 mation. Most participants believed that real-time data should take precede
 nce over adherence percentages, particularly for binary indicators such as
  nutrition or sedation. It will be important to reassess this hierarchy to
  ensure a better analysis and quality of the indicators provided by the sy
 stem. \nLastly, clinicians reported their need for more transparency regar
 ding the algorithm developed. For example, while clinicians appreciated re
 ceiving the optimal CPP results, they were somewhat hesitant to use it bec
 ause they did not understand how the results were generated. Therefore, pr
 oviding clear explanations and allowing clinicians to interact with the in
 terface to review automated data will be necessary. This will contribute t
 o increased trust in the system.\nLimitations. It is important to note tha
 t during the tests, the system was not connected to the hospital's electro
 nic health record in real-time. Indeed, the scenarios were built using a p
 revious patient record, with some associated data missing. Furthermore, it
  was difficult for clinicians to provide a comprehensive and confident dia
 gnosis, as the OptiBrain interface was limited to the neurological system 
 and did not account for the interrelation with other physiological systems
 .\n\nOutcomes: Following the study's recommendations, a second phase of be
 dside testing will be necessary to ensure the relevance of the proposed in
 terface and the changes made accordingly. In parallel with this evaluation
 , the application was programmed and designed to be easily integrated into
  the existing systems at the CHU Sainte-Justine Hospital. These recommenda
 tions will be incorporated into the application to ensure better adoption 
 of the system within the intensive care unit.\n\nTrack: Digital Health (DH
 )\n\nSession Chairs: Myrtede Alfred (University of Toronto) and Michelle L
 ai (University of Toronto)
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