As the EMR “space race” peaks, clinical and health leaders are coming to understand that digitising data does not, on its own, drive innovation or transformation.
Many are wondering what’s next. Looking ahead, the next wave in our journey towards digital transformation is Artificial Intelligence (AI).
Simply put, Artificial Intelligence is a collection of systems that sense, comprehend, act and learn.
The goal of AI in health is to drive greater “data dividends” than what we are getting from investments already made in EMRs and other systems. This dividend will be measured two ways: First, improved quality and efficiencies of systems that care for people when they are sick. Second, AI will enable a new style of “health systems” that empower consumers to better shape and manage their own health.
AI is not about creepy robots creating assembly-line healthcare. It is about systems that assist and support the wisdom and experience of well-trained clinicians in making better data-driven decisions and taking actions that best support the needs of those they serve. It does this by gathering and crunching massive amounts of data quickly and intelligently to identify patterns often overlooked or undiscovered in the traditional practice of care.
While still in the early stages, here are a few examples of AI in health.
AI to Improve Treatment Planning: Antonio Criminisi from Microsoft Research-Cambridge has developed an intelligent medical analysis system capable of improving radiation treatment planning for cancer patients.