These are all examples of how IoT in healthcare allows us to collect granular patient data at frequencies previously unimaginable – not just when people are sick or in a hospital, but where people live and work. This data can be combined with behavioral, physiological, biochemical, genetic, genomic and epigenetic data and more. The volume and scope of the data will make it possible to develop powerful learning and adaptive diagnostic and therapeutic models. Over time, these algorithms will be able to detect new, previously hidden or unknown patterns and relationships between data, diagnoses, treatments and patient outcomes. The result will be next-generation expert systems that will eventually develop a level of autonomy in diagnosis and treatment. Soon, we’ll see them routinely assisting physicians and nurse practitioners, helping them provide high-quality care and achieve better patient outcomes at a lower cost.
