Towards Smarter and Connected Hearing Implant Care

Author: Filiep Vanpoucke, Cochlear Technology Centre, Mechelen, Belgium

Connectivity is transforming the hearing care model significantly. Wireless links turn hearing instruments and implants effectively into Internet of Medical Things (IoMT) devices, connecting the user 24/7 to their caregivers and peers. This opens unprecedented routes to higher value creation. Patients may benefit from better hearing outcomes and user experiences. Health care professionals may take better care decisions and access new capabilities such as remote monitoring. And providers and payers may benefit from higher efficiency.

Data – and turning these data into useful insights and tools – is at the heart of this digital transformation. AI has the potential to support HCPs – augmented intelligence – and to significantly empower non-expert users in taking on more responsibility. Bigger and richer connected data and machine learning (ML) will allow to make progress on hard problems such as managing outcome variability. Although the future is bright, major hurdles exist.

Establishing and maintaining trust among all parties is arguably the biggest one. To truly reap these benefits, users must be willing to share more data about how they use their device and how well they perform, such that these can serve as inputs to smart algorithms. Without a deeper, more precise understanding of their needs, only shallow group-level solutions can be offered. Also, clinicians need the assurance that ML-powered tools are trustworthy. Where risks exist, regulators must play a role in establishing credibility, e.g. by extending traditional design controls to include the data sets underlying machine learning. The role of manufacturers is evolving. In response to the rightful expectation – accelerated by the pandemic – to provide connected care solutions, they are building digital platforms where hearing data can be shared among selected stakeholders in the hearing journey.

This is happening in a rapidly evolving context, where governments are trying to keep up with the AI space updating ethical, privacy and medical device regulations and standards. Given this complexity, the first digital platforms will likely be relatively closed. However, given the need for true collaboration and deep partnerships among stakeholders, including the research community, an evolution is expected towards more open ecosystems. Standards can play an enabling role to accelerate our learnings.