基于大数据分析的听力障碍管理公共卫生政策:Genesis的进化

G. Spanoudakis, P. Katrakazas, D. Koutsouris, D. Kikidis, A. Bibas, N. H. Pontoppidan
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引用次数: 17

摘要

听力损失的整体管理需要适当的公共卫生政策,以预防、早期诊断、长期治疗和康复听力损失;认知能力下降的检测和预防;防止噪音;和HL患者的社会经济包容性。然而,目前形成此类政策的证据基础有限。整体HL管理政策需要分析异构数据,包括助听器(HA)使用情况、噪音发作、听力学、生理、认知、临床和药物、个人、行为、生活方式、职业和环境数据。为了利用这些数据形成全面的HL管理政策,EVOTION,一个新的欧洲研究和创新项目,旨在开发一个集成平台,支持:(a)分析相关数据集,以便利用各种形式的大数据分析确定其中的因果关系和其他影响;(b)根据(a)的结果和制定相关的公共卫生政策,重点选择与HL整体管理有关的有效干预措施;以及(c)以可持续的方式规范和监测这些政策。在本文中,我们描述了进化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Public Health Policy for Management of Hearing Impairments Based on Big Data Analytics: EVOTION at Genesis
The holistic management of hearing loss (HL) requires appropriate public health policies for HL prevention, early diagnosis, long-term treatment and rehabilitation; detection and prevention of cognitive decline; protection from noise; and socioeconomic inclusion of HL patients. However, currently the evidential basis for forming such policies is limited. Holistic HL management policies require the analysis of heterogeneous data, including Hearing Aid (HA) usage, noise episodes, audiological, physiological, cognitive, clinical and medication, personal, behavioural, life style, occupational and environmental data. To utilise these data in forming holistic HL management policies, EVOTION, a new European research and innovation project, aims to develop an integrated platform supporting: (a) the analysis of related datasets to enable the identification of causal and other effects amongst them using various forms of big data analytics, (b) policy decision making focusing on the selection of effective interventions related to the holistic management of HL, based on the outcomes of (a) and the formulation of related public health policies, and (c) the specification and monitoring of such policies in a sustainable manner. In this paper, we describe the EVOTION approach.
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