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

被引：0

作者：

Cleland, Brian ^{[1
]}

Wallace, Jonathan ^{[1
]}

Bond, Raymond ^{[1
]}

Black, Michaela ^{[1
]}

Mulvenna, Maurice ^{[1
]}

Rankin, Deborah ^{[1
]}

Tanney, Austin ^{[2
]}

机构：

[1] Ulster Univ, Coleraine, Londonderry, North Ireland

[2] Analyt Engines, Belfast, Antrim, North Ireland

来源：

ARTIFICIAL INTELLIGENCE XXXIV, AI 2017 | 2017年 / 10630卷

关键词：

Health policy; Data analytics; Big data; Prescribing; Prevalence; Deprivation; BIG DATA; PUBLIC-HEALTH; SOCIAL MEDIA; SURVEILLANCE;

D O I：

10.1007/978-3-319-71078-5_18

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 potential 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 deprivation 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, identifying correlations between the three main variables, and highlighting anomalies in the data. The findings are discussed and implications and opportunities for further research are described.

引用

页码：193 / 206

页数：14

共 31 条

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