A feasibility assessment of a traumatic brain injury predictive modelling tool at Kilimanjaro Christian Medical Center and Duke University Hospital.

Traumatic brain injury (TBI) is the most common cause of death and disability globally. TBI, which disproportionately affects low middle-income countries (LMIC), uses significant amounts of health system resources in costly care and management. Innovative solutions are required to address this high burden of TBI. One possible solution is prognostic models which enhance diagnostic ability of physicians, thereby helping to tailor treatments more effectively. This study aims to evaluate the feasibility of a TBI prognostic model developed in Tanzania for use by Kilimanjaro Christian Medical Center (KCMC) healthcare providers and Duke-affiliated healthcare providers using human centered design methodology. Duke participants were included to gain insight from a different context with more established practices to inform the TBI tool implementation strategy at KCMC. To evaluate the feasibility of integrating the TBI tool into potential workflows, co-design interviews were conducted with emergency physicians and nursing staff at KCMC and Duke. Qualitatively, the TBI tool was assessed using human centered design (HCD) techniques. Our research design methods were created using the Consolidated Framework for Implementation Research which considers overarching characteristics of successful implementation to contribute to theory development and verification of implementation strategies across multiple contexts. Our knowledge translation method was guided using the knowledge-to-action framework. Of the 21 participants interviewed, 12 were associated with Duke Hospital, and 9 from Kilimanjaro Christian Medical Centre. Emerging from the data were 6 themes that impacted the implementation of the TBI tool: access, barriers, facilitators, use of the TBI tool, outer setting, and inner setting. To our knowledge, this is the first study to investigate the pre-implementation of a sub-Saharan Africa (SSA) data- based TBI prediction tool using human centered design methodology. Findings of this study will aid in determining under what conditions a TBI prognostic model intervention will work at KCMC.