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

Abstract

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.

Fully Synthetic Longitudinal Real-World Data From Hearing Aid Wearers for Public Health Policy Modeling

“…Data collection in EVOTION follow a published protocol (Spanoudakis et al, 2017; Dritsakis et al, 2018), is ongoing, and spans 12 months from the day of recruitment to the end of study participation. The data-set presented here represents a synthesized data-sample from EVOTION.…”

“…This inadequate focus has been attributed to a lack of evidence supporting policies that actively promote hearing healthcare (Moyer, 2012; Barker et al, 2016). However, this specific issue is targeted in the EU-funded H2020 project EVOTION (www.h2020evotion.eu), which collects a large volume of heterogenous data from almost 1,000 hearing aid (HA) users with varying degrees of hearing loss to support the development of evidence-based policy making within the hearing healthcare field (Spanoudakis et al, 2017; Gutenberg et al, 2018). Data are being collected from five sources: (i) hearing aids, (ii) a smartphone app, (iii) a biosensor, (iv) audiology clinics, and (v) electronic health records.…”

Public health policy-making for hearing loss: stakeholders’ evaluation of a novel eHealth tool

“…The collaborative European Union-funded EVOTION project has built an integrated platform to support the formulation of PH policies related to HL prevention, diagnosis and rehabilitation with the use of big data [ 28 , 29 ]. EVOTION’s overarching ambition is to promote evidence-informed policy-making in hearing healthcare, in line with the increasing use of eHealth applications worldwide.…”

Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study

“…Its ultimate objective is to enable and support a more holistic management of HL at the population level. 21 To this end, the EVOTION project is developing public health policy decision models (PHPDMs) using a combination of factors potentially affecting the effectiveness of HL treatments and ways in which they can inform public health policy decisions. 22 PHPDMs define, analyse and address a wide range of public health issues with the aim to provide different stakeholders (eg, ministries, regulatory bodies, non-governmental organisations) with tools for HL-related policy formulation.…”