| Literature DB >> 33121491 |
Giorgos Dritsakis1, Lyubov Trenkova2, Mariola Śliwińska-Kowalska3, Dario Brdarić4,5, Niels Henrik Pontoppidan6, Panagiotis Katrakazas7, Doris-Eva Bamiou8,9.
Abstract
BACKGROUND: Hearing loss (HL) affects 466 million people of all ages worldwide, with a rapidly increasing prevalence, and therefore requires appropriate public health policies. Multi-disciplinary approaches that make use of eHealth services can build the evidence to influence public policy. The European Union-funded project EVOTION developed a platform that is fed with real-time data from hearing aids, a smartphone, and additional clinical data and makes public health policy recommendations based on hypothetical public health policy-making models, a big data engine and decision support system. The present study aimed to evaluate this platform as a new tool to support policy-making for HL.Entities:
Keywords: EVOTION platform; SWOT; big data; hearing loss; policy-making; public health
Mesh:
Year: 2020 PMID: 33121491 PMCID: PMC7596974 DOI: 10.1186/s12961-020-00637-2
Source DB: PubMed Journal: Health Res Policy Syst ISSN: 1478-4505
Fig. 1Schematic representation of the EVOTION platform. Middle: the EVOTION Data Repository collecting data from various sources. Left: Hearing aid users transmitting data via smart hearing aids, smartphones and potentially via smartwatches if available using a Bluetooth connection. Bottom right: healthcare professional entering data from the clinic either directly through a dashboard of the platform or through existing clinical databases connected to the EVOTION Data Repository. Top right: policy-maker running queries on the EVOTION database through the dashboard in order to answer specific public health issues. Source: Pontoppidan 2019 [27]. Used with permission
Fig. 2Preliminary results from EVOTION dynamic data analysis. Average hearing aid usage over time (left) and how the sound level, sound diversity and signal quality, i.e. signal-to-noise ratio, describe the acoustic environment (right). Source: Christensen et al. [34]. Used with permission
Fig. 3Snapshots of the EVOTION dashboard. Top: creation of a policy using pre-defined Public Health Policy Decision-Making models. Middle: creation of a workflow within that policy specifying the statistical techniques to be used. Bottom: Creation of a data analytics task within the workflow by specifying the types of data from the EVOTION Data Repository to be used. Source: Basdekis et al. [37]. Used with permission
Fig. 4EVOTION evaluation results. Summary of common themes from all four workshops produced after identifying themes in the SWOT analysis of each of the workshops and then comparing themes from the four countries to each other