In this Voices interview, VP of Clinical Management, Ryan Krout, PharmD, sits down with Hospice News to talk about the future of predictive analytics in hospice care, and the steps providers can take to get the most out of this evolving technology. He breaks down the different use cases for predictive analytics and the key areas where AI-powered tools are impacting care. He also offers a look at what’s to come for Enclara and its clients as they explore new ways to deliver value in the hospice pharmacy environment.
Hospice News: We talked previously about your extensive experience in hospice pharmacy — what excites you most in the industry today?
Ryan Krout: The explosion of artificial intelligence (AI) has started to affect nearly every industry in some way or another. While AI has been a very popular marketing term, what we’re actually beginning to see are some valuable predictive analytics tools making their way into the hospice world, particularly when it comes to disease progression.
There are many reasons to have a better handle on how and when patient needs are likely to evolve so providers can be more proactive in their care strategies. Proactive care reduces stress on staff and improves the experience of care, but end of life is an entirely different set of challenges.
In 2016, CMS introduced the service intensity add-on, or SIA, which incentivizes visits during a patient’s final week. The problem is that we can’t always predict when death will occur. We can usually tell when it is imminent, but by then, we’re talking about days, not weeks. Marshaling the resources to increase service intensity overnight can be difficult, especially for smaller organizations, so predictive analytics can help care teams plan better and make more efficient use of their resources.
Where do you see Enclara adding value with predictive analytics?
For Enclara, predicting disease progression presents several opportunities to help our hospice partners improve quality while managing expenses. When evaluating any predictive analytic tool, Enclara always ensures that a clinical expert makes the final determination when predictive data are involved to help mitigate bias and verify the accuracy of information.
