Issue link: https://beckershealthcare.uberflip.com/i/1169964
86 Executive Briefing engagement strategy will be most useful when learning about each patient's unique behavior and reacting to it in a way that reaches the patient at the best possible times, in the best possible manner. When the platform itself is learning about the patients' motivations, it becomes much easier to promote self-healing. Here's a good example of how AI and machine learning can activate and motivate a patient to stay engaged with her care plan. Sarah, a patient living with diabetes, is an early riser who likes to go for a run before having breakfast. After her run, she has a healthy meal and a cup of coffee. She tends to catch up on texts and social media before heading to work. Her provider's patient engagement platform — equipped with AI and machine learning — has learned that this is when she is most likely to respond to notifications, reminders and other care instructions related to her health. In fact, when she was engaged at 2 p.m., her engagement rate was just 30 percent. When the AI told the system to try engaging her at 6 a.m., her interaction and engagement soared to 90 percent. The platform will curate individualized information for Sarah and push it to her when it knows Sarah is available and more willing to engage. This "learning" is critical as it promotes Sarah's self-management of her health at her convenience. When we make care more easily accessible (and manageable), we make positive outcomes attainable. But what about patients who aren't as motivated to engage? How can AI and machine learning capabilities help keep them motivated? One way to accomplish this is to enable the AI and machine learning to learn about these patients' behaviors and send different types of reminders at different times of day to keep the appointments and other instructions top of mind. Instead of designating a staff member to deliver reminder after reminder, AI and machine learning will determine when and how to best engage the patient. This not only keeps the patient active in his or her health, it helps organizations save administrative time (and money) that can be better spent on other tasks. Population health with AI and machine learning At Allscripts, we see these emerging technologies as positive and empowering. From a population health perspective, AI and machine learning are now helping change the face of patient engagement. On a daily basis, we see the results FollowMyHealth®, built on the Microsoft Azure cloud platform, clients are achieving with AI and machine learning and the results are energizing. Patients want to be engaged, and it is our job to enable this deep engagement. Across the healthcare industry, it is time to set our sights on driving smarter healthcare and changing what's possible for every patient, every day. n From a population health perspective, AI and machine learning are now helping change the face of patient engagement. To learn more, visit allscripts.com. Allscripts is a global leader in healthcare technology that connects communities for smarter care. Built on an open platform, its EHR, financial management, p o p - ulation health and precision medicine solutions drive innovation in workflows, care delivery and patient behavior. Microsoft is the leading platform and productivity company for the mobile-first, cloud-first world, and its mission is to empower every person and every organization on the planet to achieve more. We believe in what people make possible. https://www.microsoft.com/en-us/