035 Ensuring data adequacy in development of a major trauma clinical decision app. Issue 12 (21st November 2019) - Mather, Alexandra; Lowe, David; Thomson, Kevin; Whitelaw, Alan; Beaumont, Ben; Tulloch, James
Abstract : Background: Emergency medicine clinicians from the QEUH research team EMQUIRE are working alongside design agency, Daysix, and the Scottish Trauma Network to develop a pioneering clinical decision support app to be used in major trauma. The development of the major trauma app will support clinicians to achieve three key aims: Robust data collection Cognitive aids to support and prompt clinicians Provision of a reliable framework When creating a innovate, digital tool to be used in the medical setting, it is essential that it satisfies CE marking and MHRA regulations. Method and results: A variety of methods have been used to ensure the trauma app provides reliable, valid and adequate data; A systematic review of existing paper trauma proformas within Scotland was performed and data points recorded. A review of 10 major trauma cases and documentation from each region was then taken place. This information was used to establish a minimum data set TARN and STAG data standards were reviewed, and the app data fields reflect this Cognitive aids and prompts within the app have a strong evidence base – literature from the ATLS manual and case–based evidence The Delphi method was used to establish clear data fields for the trauma app. This involved expert clinicians from MTCs and MTUs within Scotland High fidelity trauma simulation was performed Conclusions: The comparison of current standards of paper documentation and data fields of the app has ensured granularity of data is increased. Clinicians have provided feedback throughout the design process which has led to further development and refinement. This expert input has ensured that the data fields within the app are adequate and valid. The overall result is an app that mirrors and supports the established clinical framework for trauma management and enables enhanced data visualisation of episodes of care.