Issue link: https://beckershealthcare.uberflip.com/i/1169964
85 Executive Briefing Sponsored by: Driving better patient engagement outcomes with AI & machine learning N ow more than ever, patients are willing to incorporate emerging technologies in all aspects of their lives — including using AI and machine learning to assist them in managing health outcomes. In sharp contrast to patients' overall comfort level with AI being used in their care, recent data suggests only 35 percent of patients say they feel valued by their physician's office. Furthermore, only 50 percent of patients said their physicians are readily available, with one-fifth of patients either disagreeing or strongly disagreeing that their physicians are easily accessible. We can do better to reach this key population, providing better access to care and quality engagement. Enter AI and machine learning. These capabilities offer healthcare providers the opportunity to more deeply engage patients and ensure they feel heard and valued by their care team. Additionally, success with value-based care models means providers need to drive wellness and behavior change. AI and machine learning can help fill gaps in care in an efficient way to improve patient outcomes and overall satisfaction without adding to a physician's workload. Reaching patients where they are — at the right time — will enhance overall health outcomes while helping boost satisfaction. Using AI and machine learning will greatly help achieve these goals. You can see more data around patients and AI here 1 AI and machine learning Before we dive deeper into how these technological capabilities will help patients stay more meaningfully engaged in their health journeys, "Machine Learning Vs. Artificial Intelligence: How Are They Different?" 2 breaks down what each of these capabilities can offer your organization's patient engagement strategy. Here's a quick look at each capability: AI is the output of computer programs created to not only perform certain tasks, but to also adapt to different situations. These programs are algorithmic and "intelligent," which enable them to react similarly to humans, but perhaps more acutely. Machine learning is a part of AI but goes a bit further into the concept of "learning." It is based on the idea that it is more beneficial to teach machines (programs) to learn and process data, rather than teach them to react to every possible situation that might arise. These programs are algorithmic and "intelligent," which enable them to react similarly to humans, but perhaps more acutely. Enabling patient engagement platforms to more effectively use AI/machine learning will strengthen patient engagement strategies by ensuring patients are contacted and engaged based on the behaviors already in motion. Patient behavior, after all, is a major factor in driving successful care plans Adopting AI and machine learning for improved patient engagement strategies Patients are more likely to stay engaged with their health and wellness if the mode of engagement is convenient. To date, major strides have been taken to help activate and motivate patients. For instance, patients can message with their providers and receive important care plan updates from their smartphone or other mobile device. Incorporating AI or machine learning into your patient 1 https://patientengagementhit.com/news/patients-ready-to-embrace-ai-patient-engagement-technologies 2 https://www.forbes.com/sites/forbestechcouncil/2018/07/11/machine-learning-vs-artificial-intelligence-how-are- they-different/#5d8cd2973521