Guest post by Steve Tolle, chief strategy officer, Merge Healthcare, an IBM Company.
The volume of health-related data available to physicians and other healthcare providers from disparate sources is staggering and continues to grow. In fact, a 2014 University of Iowa, Carver College of Medicine report projects that the availability of medical data will double every 73 days by 2020. Such data overload can make it difficult for clinicians to keep up with best practices and innovations.
Perhaps because imaging is so pervasive in healthcare, the medical imaging field has turned to data analytics and cognitive computing to help clinicians use large volumes of data in a meaningful way. These decision-support tools help them manage data to improve patient care and deliver value to referring physicians and payers.
At RSNA15, the crowds packed presentations on data analytics and cognitive computing and flocked to vendor exhibits featuring these decision-support tools — indicators of their expanding role in healthcare. In years past, exhibit space was primarily devoted to showcasing new imaging modalities.
Interest in analytics is growing rapidly as the U.S. health system transitions from volume- to value-based payment models — models that challenge physicians involved in medical imaging to demonstrate value. Physicians are under pressure to deliver educated, accurate, useful and efficient interpretations even as imaging studies become increasingly large in size and complex in scope. And these physicians are expected to communicate this information quickly and in a user-friendly manner. As a result, clinicians are turning to analytics-based solutions to boost efficiency and enhance the quality of their service to help them deliver the value demanded by payers, referring physicians and patients.