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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationArtificial Intelligent XXXIV. SGAI 2017. Lecture Notes in Computer Science
EditorsM Bramer, M Petridis
PublisherSpringer Cham
Pages193-206
Number of pages14
Volume10630
ISBN (Electronic)978-3-319-71078-5
ISBN (Print)978-3-319-71077-8
DOIs
Publication statusPublished (in print/issue) - 21 Nov 2017
EventAI-2017: The Thirty-seventh SGAI International Conference - Cambridge, England
Duration: 1 Sept 2017 → …

Conference

ConferenceAI-2017: The Thirty-seventh SGAI International Conference
Period1/09/17 → …

Keywords

  • Health Policy
  • Data Analytics
  • Big Data
  • Prescribing
  • Prevalence
  • Deprivation

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