Predicting Changes in Quality of Life for Patients in Vocational Rehabilitation

Citation

Haraldsson S, Brynjolfsdottir RD, Gudnason V, Tomasson K & Siggeirsdottir K (2018) Predicting Changes in Quality of Life for Patients in Vocational Rehabilitation. In: EAIS 2018 proceedings. Evolving and Adaptive Intelligent Systems, Rhodes, Greece, 25.05.2018-27.05.2018. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/EAIS.2018.8397182

Abstract
Adaptive systems will become increasingly important for health care in coming years as costs and workload grow. The need for efficient rehabilitation will expand which will be fulfilled by information technologies. This paper presents a novel implementation and application of a dynamic prediction software in vocational rehabilitation. The software is made adaptable with a Genetic Improvement of software methodology and utilised to predict fluctuations in patient’s perceived quality of life. Results of accuracy, recall and precision were better than 90% for the classification of the shifts and the mean absolute error in predictions of the quantity of the shifts was low. The findings of the present study support that it is possible to predict fluctuations in quality of life on average based on the status six months prior. Professionals could therefore intervene accordingly and increase the possibility of successful rehabilitation. The significant long term effect on health care from applying the prediction tool might be reduced cost and overall improved quality of life.

Keywords
Computational Intelligence; Vocational Rehabilitation; Icelandic Quality of Life; Prediction Models

People

Dr Saemundur Haraldsson

Lecturer, Computing Science