The healthcare industry is quickly evolving, shaped by factors such as increasing global demand and significant advancements in imaging technology. Staying on top of these changes and securing the best tools and strategies to address them is critical to the success of any industry provider.
Electronic medical records (EMRs) have made it possible to provide clinicians with access to a patient's medical history, or a patient's truth, at the point of care. However, these electronic systems only tell part of the story – not the whole truth that is required to make informed choices. Today, medical images often become part of an organization's "dark data" – the information that remains inaccessible at the point of decision. But this critical data doesn't have to live in
Out of the ashes of the stock market crash of 2008 came a jobs program, the American Redevelopment and Reinvestment Act (ARRA) of 2009, designed to help put people back to work, including people in healthcare who were willing to comply with evolving national healthcare goals by manufacturing specific healthcare software or by meaningfully implementing such technology. The Feds set up private credentialing organizations for EMR vendors plus an incentive payment system (The EHR Incentive Program), and "meaningful use (MU)" was born. Despite hiccups and complaints about its administrative complexity and implementation costs, the MU program led to revolution in U.S. healthcare information technology, including two
By Nancy Koenig
and Murray A. Reicher
, MD FACR
Cognitive computing involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works. Instead of a software engineer devising an algorithm that remains static, cognitive systems can perform evolving tasks previously reserved for humans. The resulting opportunities are incredibly exciting.