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

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.

[1]  Frank E. Musiek,et al.  Plasticity, Auditory Training, and Auditory Processing Disorders , 2002 .

[2]  D. Bates,et al.  Big data in health care: using analytics to identify and manage high-risk and high-cost patients. , 2014, Health affairs.

[3]  T YOKOYAMA [Studies on occupational deafness. 1. Subjective symptoms concerning auditory apparatus and various fatigue]. , 1962, Nihon Jibiinkoka Gakkai kaiho.

[4]  Heather Fortnum,et al.  Why do people fitted with hearing aids not wear them? , 2013, International journal of audiology.

[5]  T. Murdoch,et al.  The inevitable application of big data to health care. , 2013, JAMA.

[6]  William B. March,et al.  MLPACK: a scalable C++ machine learning library , 2012, J. Mach. Learn. Res..

[7]  Stig Arlinger,et al.  Negative consequences of uncorrected hearing loss—a review , 2003, International journal of audiology.

[8]  John A. Albertini,et al.  Deafness and Hearing Loss , 2010 .

[9]  Jerker Rönnberg,et al.  Gated Auditory Speech Perception in Elderly Hearing Aid Users and Elderly Normal-Hearing Individuals: Effects of Hearing Impairment and Cognitive Capacity , 2014, Trends in hearing.

[10]  J. Popay,et al.  Systematically reviewing qualitative and quantitative evidence to inform management and policy-making in the health field , 2005, Journal of health services research & policy.

[11]  Athanasios V. Vasilakos,et al.  Big data analytics: a survey , 2015, Journal of Big Data.

[12]  David Kirk,et al.  NVIDIA cuda software and gpu parallel computing architecture , 2007, ISMM '07.

[13]  Karen Golden-Biddle,et al.  Towards systematic reviews that inform health care management and policy-making , 2005, Journal of health services research & policy.

[14]  A. Beekman,et al.  Increased risk of mortality associated with social isolation in older men: only when feeling lonely? Results from the Amsterdam Study of the Elderly (AMSTEL) , 2011, Psychological Medicine.

[15]  Jignesh M. Patel,et al.  Storm@twitter , 2014, SIGMOD Conference.

[16]  W. Kaplan,et al.  priority Medicines for Europe and the World: 2013 update , 2013 .

[17]  Dan J Stein,et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2015, The Lancet.

[18]  Zoltán Prekopcsák,et al.  Radoop: Analyzing Big Data with RapidMiner and Hadoop , 2011 .

[19]  Alan D. Lopez,et al.  The Global Burden of Disease Study , 2003 .

[20]  T E WESTON,et al.  PRESBYACUSIS. A CLINICAL STUDY. , 1964, The Journal of laryngology and otology.

[21]  Sergei Kochkin,et al.  MarkeTrak VIII: The Key Influencing Factors in Hearing Aid Purchase Intent , 2012 .

[22]  S. Schneeweiss Learning from big health care data. , 2014, The New England journal of medicine.

[23]  R. Brownson,et al.  Understanding evidence-based public health policy. , 2009, American journal of public health.

[24]  Susan M Resnick,et al.  Hearing loss and incident dementia. , 2011, Archives of neurology.

[25]  Tom White,et al.  Hadoop: The Definitive Guide , 2009 .