Affiliations: Instituto de Telecomunicações, and Department of Informatics, University of Beira Interior, Covilhã, Portugal | Faculty of Health Sciences, University of Beira Interior, Covilhã, Portugal
Note: [] Corresponding author. Nuno Pombo, Instituto de Telecomunicações, and Department of Informatics, University of Beira Interior, Covilhã, Portugal. E-mail: [email protected]
Abstract: Millions of people around the world suffer from pain, acute or chronic and this raises the importance of its screening, assessment and treatment. Pain, is highly subjective and the use of clinical decision support systems (CDSSs) can play an important part in improving the accuracy of pain assessment, and lead to better clinical practices. This review examines CDSSs, in relation to computer technologies and was conducted with the following electronic databases: CiteSeerx, IEEE Xplore, ISI Web of Knowledge, Mendeley, Microsoft Academic Search, PubMed, Science Accelerator, Science.gov, ScienceDirect, SpringerLink, and The Cochrane Library. The studies referenced were compiled with several criteria in mind. Firstly, that they constituted a decision support system. Secondly, that study data included pain values or results based on the detection of pain. Thirdly, that they were published in English, between 1992 and 2011, and finally that they focused on patients with acute or chronic pain. In total, thirty-nine studies highlighted the following topics: rule based algorithms, artificial neural networks, rough and fuzzy sets, statistical learning algorithms, terminologies, questionnaires and scores. The median accuracy ranged from 53% to 87.5%. The lack of integration with mobile devices, the limited use of web-based interfaces and the scarcity of systems that allow for data to be inserted by patients were all limitations that were detected.
Keywords: Clinical decision support system, pain measurement, medical informatics, machine learning
