Development of A Clinical Decision Support System for Trauma Emergency Care: Identifying Main Features and Usability Test (Preprint)

Abstract

Computerized clinical decision support system is a solution to promote ATLS protocol for traumatic injuries. To study its design based on user requirements and usability, a Kano questionnaire research to survey perspectives of physicians was undergone.

This study aims to elicit user requirements for a CDSS treating traumatic patients in a hospital setting and it’s usability by evaluating the features of TFA.

We applied Kano mode research studying user requirements to further provide theoretical support for the development of the system. A 5-level questionnaire was designed based on the perspectives of Kano. The features of TFA were evaluated by pairs of questions: first a functional question and subsequently a dysfunctional question. The questionnaire along with system introduction and instructions were sent to the physicians in ED from five different hospitals that work as regional trauma centers and have ability to treat severe trauma patients.

A total of 63 physicians in ED responded the questionnaire completely and were concluded into the study including 16 physicians qualified with ATLS certificate and 47 having not passed the ATLS training. A total of 16 features were rated and classified using the Kano evaluation table. Five features are classified as indifferent (5/16, 31.3%), with five being one-dimensional (5/16, 31.3%), four being attractive (4/16, 25%) and two being must-be (2/16,12.5%). Both physicians with and without ATLS experience were indifferent to most of the evaluated features (11/16, 68.8%). A difference in user requirements between physicians with ATLS qualification and those without the qualification regarding 3,4,8,13,14 features.

The study provides recommendations to developers on the user requirements that need to be addressed when developing a CDSS for advanced trauma life support care in-hospital. Two features of must-be attributes must be incorporated in the TFA. In addition, four features (attractive attributes) would result in higher user satisfaction. Among those five one-dimensional features, ISS and knowledge database display high score in both positive and negative values that indicates developers to especially prioritize the features to be implemented when developing the CDSS.