• Cyrus Elahi, Charis A Spears, Sarah Williams, Timothy W Dunn, Josephine N Najjuma, Catherine A Staton, Nickenig Vissoci João Ricardo JR Duke Global Health Institute, Durham, North Carolina, USA; Division of Emergency Medicine, Department of Surgery, Duke University School , Anthony Fuller, David Kitya, and Michael M Haglund.
• Duke Global Health Institute, Durham, North Carolina, USA.
• World Neurosurg. 2020 Jul 1; 139: 495-504.

BackgroundTraumatic brain injury (TBI) prognostic models are potential solutions to severe human and technical shortages. Although numerous TBI prognostic models have been developed, none are widely used in clinical practice, largely because of a lack of feasibility research to inform implementation. We previously developed a prognostic model and Web-based application for in-hospital TBI care in low-resource settings. In this study, we tested the feasibility, acceptability, and usability of the application with potential end-users.MethodsWe performed our feasibility assessment with providers involved in TBI care at both a regional and national referral hospital in Uganda. We collected qualitative and quantitative data on decision support needs, application ease of use, and implementation design.ResultsWe completed 25 questionnaires on potential uses of the app and 11 semistructured feasibility interviews. Top-cited uses were informing the decision to operate, informing the decision to send the patient to intensive care, and counseling patients and relatives. Participants affirmed the potential of the application to support difficult triage situations, particularly in the setting of limited access to diagnostics and interventions, but were hesitant to use this technology with end-of-life decisions. Although all participants were satisfied with the application and agreed that it was easy to use, several expressed a need for this technology to be accessible by smartphone and offline.ConclusionsWe elucidated several potential uses for our app and important contextual factors that will support future implementation. This investigation helps address an unmet need to determine the feasibility of TBI clinical decision support systems in low-resource settings.Copyright © 2020 Elsevier Inc. All rights reserved.

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