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

Gabrielle H. Saunders, Jeppe H. Christensen, Johanna Gutenberg, Niels H. Pontoppidan, Andrew Smith, George Spanoudakis, Doris Eva Bamiou

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1057-1063
Number of pages7
JournalEar and hearing
Issue number5
StatePublished - Sep 23 2020


  • Big data
  • Hearing health care
  • Population health
  • Public health policy

ASJC Scopus subject areas

  • Otorhinolaryngology
  • Speech and Hearing


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