July 19, 2019
Widespread organizational change is never easy, but healthcare has historically struggled with change, garnering a reputation as a slow adopter of technology in an era of digital transformation. The concept of “change management” has spurred countless books, philosophies, and consulting agreements, yet the topic can still be difficult, especially for healthcare organizations trying to chart the course for the future. Healthcare systems face unique challenges – first, their core business has two, sometimes opposing, goals: to provide excellent patient care and to be profitable. Any effort to cut costs or improve margins must also enhance, or at the very least not detract from, patient care. Second, healthcare organizations have a very complex structure. With a variety of facilities, a hierarchy of staff with independent contractors and employees, numerous acquisitions and legacy systems, multiple contracts and payers, it can be difficult to create alignment. On top of all of this, add in the common questions like “will a robot take my job?” and it’s a wonder that any new technology initiatives survive in a hospital environment.
Healthcare looks quite different than it did just a few short years ago. The COVID-19 crisis has created a distinct “before” and “after” for the world, and especially for healthcare.
Artificial intelligence (AI) is revolutionizing healthcare data analytics and changing the way we predict, learn and act based on insights gained through AI-powered data models.