City Research Online

Application of Big Data to Support Evidence-Based Public Health Policy Decision-Making for Hearing.

Saunders, G. H., Christensen, J. H., Gutenberg, J., Pontoppidan, N. H., Smith, A., Spanoudakis, G. ORCID: 0000-0002-0037-2600 and Bamiou, D-E. (2020). Application of Big Data to Support Evidence-Based Public Health Policy Decision-Making for Hearing.. Ear and Hearing, doi: 10.1097/AUD.0000000000000850

Abstract

Ideally, public health policies are formulated from scientific data; however, policy-specific data are often unavailable. Big data can generate ecologically-valid, high-quality scientific evidence, and therefore has the potential to change how public health policies are formulated. Here, we discuss the use of big data for developing evidence-based hearing health policies, using data collected and analyzed with a research prototype of a data repository known as EVOTION (EVidence-based management of hearing impairments: public health pOlicy-making based on fusing big data analytics and simulaTION), to illustrate our points. Data in the repository consist of audiometric clinical data, prospective real-world data collected from hearing aids and an app, and responses to questionnaires collected for research purposes. To date, we have used the platform and a synthetic dataset to model the estimated risk of noise-induced hearing loss and have shown novel evidence of ways in which external factors influence hearing aid usage patterns. We contend that this research prototype data repository illustrates the value of using big data for policy-making by providing high-quality evidence that could be used to formulate and evaluate the impact of hearing health care policies.

Publication Type: Article
Additional Information: Copyright © 2020 The Authors. Ear & Hearing is published on behalf of the American Auditory Society, by Wolters Kluwer Health, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is prop-erly cited. The work cannot be changed in any way or used commercially without permission from the journal.
Publisher Keywords: Big data, Hearing health care, Population health, Public health policy
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Date Deposited: 17 Feb 2020 14:26
URI: https://openaccess.city.ac.uk/id/eprint/23613
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