[Computer-assisted decision-making for trauma patients]

Abstract

Background: In the management of trauma patients in the resuscitation room many time-pressured and critical decisions must continuously be made in complex situations. Even experienced teams frequently make errors in this context. Computer-assisted decision-making systems can predict critical situations based on patient data continuously acquired online. Based on the calculated predictions these systems can suggest the next steps in managing the patient. This review summarizes the current literature on computer-assisted decision-making in the management of trauma patients.

Objective: A literature review summarizing existing concepts and applications of computer-assisted decision-making support for the management of trauma patients.

Methods: Narrative review article based on an analysis of literature in the German and English languages from the last 10 years.

Results: There exist numerous computer-assisted decision-making systems in the field of trauma care. Several studies could show that computer-assisted decision-making can improve the outcome in the preclinical setting, the resuscitation room and in the intensive care unit. For further validation and implementation of these systems, information technological barriers have to be overcome, existing systems need to be adapted to current data protection regulations and large multicenter studies are necessary.

Conclusion: Computer-assisted decision-making can help to improve the management of trauma patients; however, before a ubiquitous implementation a number of technological and legislative barriers have to be overcome.

Keywords: Algorithm; Decision making; Digitalization; Machine learning; Trauma.