Machine Learning for Patient Triaging

Machine Learning for Patient Triaging

Machine Learning for Triaging Patients with Low Back Pain Towards Personalized Care

The project aims to develop a clinical decision support system to assist hospital staff in triaging. Triaging describes the process in which a patient undergoes a brief examination upon admission to the hospital and is referred to the appropriate specialist on the basis of the results. The selection of the specialist and thus further treatment is based on best knowledge and thus varies from specialist to specialist. The concordance has only a kappa value of 0.67.

Aims and procedure

The project aims to determine which treatment is optimal for which patient. For this purpose, an extension of an existing clinical information system will be developed on the basis of the biopsychological information collected during triaging and the outcome of the treatment, which will provide a treatment recommendation.

The project focuses on patients with chronic low back pain. For this patient group a data set is available, which has been recorded by our project partner at the University Medical Center Groningen (UMCG) in the Netherlands and is constantly being expanded. The data includes diagnosis, triaging information as well as the answers of several follow-up surveys. Based on these follow-up surveys, the outcome of the treatment can be evaluated. Increased quality of life indicates successful or optimal treatment, while unchanged or decreased quality of life may indicate suboptimal treatment.

Cooperation / Funding

The research is done in close collaboration with the UMCG Groningen and the University Hospital Oldenburg which form the clinical expert team. The University of Oldenburg is mainly responsible for the data analysis and the development of the CDSS.

The project is funded by the research pool of the University of Oldenburg from 1/1/2020 to 31/12/2022.

(Changed: 20 Jun 2024)  | 
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