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Towards the Integration of Prescription Analytics into Health Policy and General Practice

Cleland, Brian, Wallace, Jonathan, Bond, Raymond, Black, Michaela, Mulvenna, Maurice, Rankin, Debbie and Tanney, Austin (2017) Towards the Integration of Prescription Analytics into Health Policy and General Practice. In: AI-2017: The Thirty-seventh SGAI International Conference, Cambridge, England. BCS. 14 pp. [Conference contribution]

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Abstract

The phenomenon of big data and data analytics is impacting many sectors, including healthcare. Practical examples of the application of big data to health policy and health service delivery remain scarce, however. In this paper, which summarises findings from an ongoing research project, we explore the po- tential for applying data analytics and anomaly detection to open data in order to support improved policy design and to enable better clinical decisions in primary care. The policy context of mental health in Northern Ireland is described, and its importance as a public health issue is explained. Based on previous work, it is proposed that depression prevalence is a mediating factor between economic dep- rivation and antidepressant prescribing. This hypothesis is tested by analysing a variety of open datasets. The methodology is described, including datasets used, the data processing pipeline, and analysis tools. The results are presented, iden- tifying correlations between the three main variables, and identifying anomalies in the data. The findings are discussed and implications and opportunities for further research are described.

Item Type:Conference contribution (Paper)
Keywords:Health Policy, Data Analytics, Big Data, Prescribing, Prevalence, Deprivation
Faculties and Schools:Faculty of Computing & Engineering
Ulster Business School
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Faculty of Computing & Engineering > School of Computing and Mathematics
Ulster Business School > Department of Management and Leadership
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
Computer Science Research Institute > Information and Communication Engineering
ID Code:38636
Deposited By: Mr Brian Cleland
Deposited On:14 Sep 2017 11:03
Last Modified:14 Dec 2018 23:23

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