Disabling hearing loss, according to the World Health Organization, affects 466 million people in the world and is predicted to rise to 900 million by 2050, unless action is taken. It is estimated that age-related and other hearing loss is the 4th most prevalent condition and 3rd leading cause of years lived with disability (YLD) in 2016.
Hearing loss is a huge problem in the world, expected to become more prevalent as life expectancy rises. Various health conditions compete for public funding, studies of treatment versus non-treatment in terms of cost, and personal health consequences (emerging from recent longitudinal studies), are gaining attention.
Our Focus
EVOTION is about enabling seamless collection of big data from all actors and related to treatment of hearing loss to inform, support, and develop hearing health care policies. This will be achieved by developing a multi-stakeholder demonstrator platform that combines and analyses heterogeneous big data from clinical repositories and from patients’ everyday hearing aid use and clinical treatment. The subsequent big data analytics is expected to produce ecologically valid evidence for the formulation and validation of public health policies.
In EVOTION, a large proportion of the Big Data is provided by the patients’ self-management of their hearing aids, which offers different perspectives and insights from the same data:
For the patients, the self-management data means that their hearing aid settings can be personalized without having to formulate their needs verbally.
For hearing health care professionals, the same data allows them to characterize the patients with respect to different sound environments and how patients compensate for and cope within them. These insights will allow professionals to optimise the benefit of hearing loss treatments.
For the public health policy makers, self-management data contributes to policy decision formulation, and economic analysis such as cost-effectiveness and cost-benefit analysis in which quality of care and use of clinical resources are key inputs.
What we do
EVOTION has successfully initiated the largest ever research study of hearing problems with concurrent collection of dynamic data as part of the standard clinical pathway and with patients.
During its first 18 months period EVOTION has collected requirements, designed the architecture, reviewed security, implemented the platform components according to the architecture specifications and developed a novel specification language for the formulation of public health policy decision models (PHPDMs). The platform components enable the platform to:
collect data from developed EVOTION hearing aids, wearable biosensor, and the EVOTION app (which serves as the collector)
collect the retrospective and current patient data from the existing clinical repositories
perform big data analytics, and
perform decision support simulation.
In parallel to the implementation of the platform, EVOTION has developed a unified protocol for managing over 1200 patients across the clinical sites in Greece, the UK and Denmark.
The platform is illustrated in Figure 1: EVOTION platform. The status of the EVOTION platform is that all three connections are enabled between patients, clinicians, and policy makers while the platform is powered. The joint work has so far enabled the planned use of the EVOTION platform for the clinical validation and the formulation and modelling of public health policies with the EVOTION data.
Our Impact
The EVOTION platform allows all actors to interact with data based on their specific needs, questions and from their own professional perspective. The EVOTION platform is being developed to support health care professionals and health policy makers in identifying, simulating, prioritizing, and monitoring the effectiveness of current and proposed/potential hearing loss interventions.
By means of its design and its implementation, EVOTION brings patients, health care professionals, and public health policy makers closer together in a single platform, where each collected data point will contribute information for analysis at the personal level, clinical level, and the public policy making level. Other medical fields with medical devices, e.g., prostheses, insulin pumps, visual implants, etc. share these characteristics and are likely to benefit from the overall approach, technology and findings of the EVOTION project.
