An attitude survey and assessment of the feasibility, acceptability, and usability of a traumatic brain injury decision support tool in Uganda
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Date
2020Author
Elahi, Cyrus
Spears, Charis A.
Williams, Sarah
Dunn, Timothy
Najjuma, Josephine N.
Staton, Catherine A.
Vissoci, João Ricardo Nickenig
Fuller, Anthony
Kitya, David
Haglund, Michael M.
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Background
Traumatic 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 due to 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.
Methods
We 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.
Results We completed 25 questionnaires on potential uses of the app and 11 semi-structured 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 application’s potential 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. While all participants were satisfied with the application and agreed it is easy to use, several expressed a need for this technology to be accessible by smartphone and offline.
Conclusions
We 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.
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- Research articles [63]