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.
Original language | English |
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Title of host publication | Artificial Intelligent XXXIV. SGAI 2017. Lecture Notes in Computer Science |
Editors | M Bramer, M Petridis |
Publisher | Springer Cham |
Pages | 193-206 |
Number of pages | 14 |
Volume | 10630 |
ISBN (Electronic) | 978-3-319-71078-5 |
ISBN (Print) | 978-3-319-71077-8 |
DOIs | |
Publication status | Published (in print/issue) - 21 Nov 2017 |
Event | AI-2017: The Thirty-seventh SGAI International Conference - Cambridge, England Duration: 1 Sept 2017 → … |
Conference
Conference | AI-2017: The Thirty-seventh SGAI International Conference |
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Period | 1/09/17 → … |
Keywords
- Health Policy
- Data Analytics
- Big Data
- Prescribing
- Prevalence
- Deprivation
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Dive into the research topics of 'Towards the Integration of Prescription Analytics into Health Policy and General Practice'. Together they form a unique fingerprint.Profiles
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Michaela Black
- School of Computing, Eng & Intel. Sys - Professor of Artificial Intelligence
- Faculty Of Computing, Eng. & Built Env. - Full Professor
Person: Academic
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Debbie Rankin
- School of Computing, Eng & Intel. Sys - Senior Lecturer in Computer Science
- Faculty Of Computing, Eng. & Built Env. - Senior Lecturer
Person: Academic