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Public Health Policy for Management of Hearing Impairments Based on Big Data Analytics: EVOTION at Genesis

机译:基于大数据分析的听力障碍管理公共卫生政策:创世纪的EVOTION

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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.
机译:听力损失(HL)的整体管理需要适当的公共卫生政策以预防HL,及早诊断,长期治疗和康复;检测和预防认知能力下降;防止噪音;和HL患者的社会经济包容性。但是,目前形成这种政策的证据基础是有限的。整体HL管理政策要求分析各种数据,包括助听器(HA)的使用,噪声发作,听力学,生理学,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整体的HL管理政策,EVOTION是一项新的欧洲研究与创新项目,旨在开发一个集成平台,以支持:(a)相关数据集的分析,从而能够使用各种方法识别其中的因果关系及其他影响大数据分析的形式,(b)基于(a)的结果和相关公共卫生政策的制定,以及(c)规范的结果,着重于选择与HL整体管理有关的有效干预措施的政策决策并以可持续的方式监测此类政策。在本文中,我们描述了EVOTION方法。

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