CMIO says analytics, artificial intelligence, Big Data and machine learning are becoming IT requirements
In a changing competitive landscape where skilled nursing facilities, home health, assisted living and long-term care organizations are looking for ways to differentiate themselves, drive better care, and reduce the number of adverse events within their patient populations, healthcare analytics has a big role to play. But one expert said that analytics is only one piece of a much larger puzzle that is required to get the post-acute care field in order.
“Analytics is an old-fashioned term for what folks are doing today,” said Terry Sullivan, MD, chief medical information officer at Onpointe, a post-acute care provider organization. “There is analytics, there is artificial intelligence, there is Big Data, and there is machine learning. They all come together in cognitive machines and cognitive clinical capabilities. It’s the summation of those four things.”
Sullivan said that if a post-acute care provider organization does not have analytics, is not measuring something, and is not using an electronic health record, it should “close the door and leave town.”
“The world is moving faster than that,” he said. “In using analytics and artificial intelligence and these other pieces, they are demonstrating where they are at, which is crucial for them to be 21st century players in a competitive marketplace.”
These technologies – analytics, AI, Big Data and machine learning – enable providers to optimize the patient journey so they and their partners are capable of taking on financial risk, Sullivan explained.
“At the end of the day, if you are not capable of taking risk and performing in an optimum way, then you are not going to be very competitive,” he said. “The technology is part of it. One part is you align with the right financial partners, so you are in either a risk situation, a bundle situation, you are aligned with somebody so you are not in a fee-for-service model. Then you have to have an operational model that connects to the people above you who are referring to you and below you who you are referring to. And you have to have an IT capability that allows you to optimize the patient journey.”
Healthcare organizations require all of those things to perform, because without high-quality information an organization cannot really participate in the continuum of care and will not be competitive, Sullivan added.
“At a minimum the information would involve an EHR that has connections to the referring group above you and to the group below you who you are referring to,” he said.
One of the four components of Sullivan’s technology requirements, artificial intelligence, can help post-acute care organizations drive market differentiation and care quality, he said.
“Today, patient care is driven by usual and customary practice; things like length of stay, place of stay, are driven by historical practice – on average, people stay a certain amount of time at a certain location,” he explained. “With artificial intelligence and machine learning, then onto cognitive machines, you for the first time are becoming truly patient-centered not facility-centered. In the old days, I keep patients two or three weeks. In the new paradigm, I keep the patient there only until they can safely move to the next level of care because cognitive machines allow me to know more information about the patient that allows me to make that decision when they can safely move to the lower level and less expensive level of care.”
Sullivan will discuss his experience using these technologies at the HIMSS and Healthcare IT News Big Data & Healthcare Analytics Forum, May 15-16, 2017, in San Francisco, during a session entitled “Post-Acute Care: When Productions Move Outside the Hospital.”