Skip to main content

Research Repository

Advanced Search

Data mining medical information: should artificial neural networks be used to analyse trauma audit data?

Chesney, Thomas; Penny, Kay I; Oakley, Peter; Davies, Simon; Chesney, David; Maffulli, Nicola; Templeton, John

Authors

Thomas Chesney

Kay I Penny

Peter Oakley

Simon Davies

David Chesney

Nicola Maffulli

John Templeton



Abstract

Trauma audit is intended to develop effective care for injured patients through process and outcome analysis, and dissemination of results. The system records injury details such as the patient’s sex and age, the mechanism of the injury, various measures of the severity of the injury, initial management and subsequent management interventions, and the outcome of the treatment including whether the patient lived or died. Ten years’ worth of trauma audit data from one hospital are modelled as an Artificial Neural Network (ANN) in order to compare the results with a more traditional logistic regression analysis. The output was set to be the probability that a patient will die. The ANN models and the logistic regression model achieve roughly the same predictive accuracy, although the ANNs are more difficult to interpret than the logistic regression model, and neither logistic regression nor the ANNs are particularly good at predicting death. For these reasons, ANNs are not seen as an appropriate tool to analyse trauma audit data. Results do suggest, however, the usefulness of using both traditional and non-traditional analysis techniques together and of including as many factors in the analysis as possible.

Citation

Chesney, T., Penny, K. I., Oakley, P., Davies, S., Chesney, D., Maffulli, N., & Templeton, J. (2006). Data mining medical information: should artificial neural networks be used to analyse trauma audit data?. International Journal of Healthcare Information Systems and Informatics, 1, 51-64. https://doi.org/10.4018/jhisi.2006040104

Journal Article Type Article
Publication Date Apr 1, 2006
Deposit Date Apr 4, 2008
Print ISSN 1555-3396
Electronic ISSN 1555-340X
Publisher IGI Global
Peer Reviewed Peer Reviewed
Volume 1
Pages 51-64
DOI https://doi.org/10.4018/jhisi.2006040104
Keywords trauma audit; logistic regression analysis; patient outcomes; artificial neural network
Public URL http://researchrepository.napier.ac.uk/id/eprint/1575
Publisher URL http://dx.doi.org/10.4018/jhisi.2006040104