8 JUNE 2024IN MY OPINIONHOW AI IS HELPING HOSPICE CARECharlotte Mather, RN, BSN, MBA, FACHE, RWJF-ENFCharlotte is the Vice President of Nursing ­ Hospice at AccentCare. She has completed both her BSN and MBA from Oakland University in Rochester, Michigan, as well as an Executive Certificate in Negotiation from Notre Dame. She is a Fellow of the American College of Healthcare Executives and a Robert Wood Johnson Foundation Executive Nurse Fellow. Charlotte was awarded the Nightingale Award for Nursing from Oakland University in the Distinguished Alumni category. She holds membership in Beta Gamma Sigma, the exclusive business honor society which recognizes academic excellence in business studies.Artificial intelligence (AI) and machine learning are helping detect diseases faster, culling vital information for treatment plans and aiding clinicians. But how can it help hospice care? At AccentCare, we provide home health, hospice and personal care services to thousands of patients, nationwide. As Vice President of Nursing for Hospice at the organization, I know the decision to choose hospice care is not an easy one for patients and families. Hospice is also a difficult profession both emotionally and physically for our clinicians and hospice teams. It's my job to look for ways to make the hospice experience smoother for patients, families and our team. Implementing this unique AI program for our clinicians to utilize has helped in the care of hospice patients. This revolutionary AI program is called Muse. It was developed by a company called Medalogix, based in Nashville, TN. This tool helps us utilize technology to act like an extra set of eyes for our clinicians. I like to think of it as having an experienced nurse standing alongside our clinicians, giving patients and families timelier, more responsive care when they need it the most, at the patient's end-of-life journey. How does it work? Well, it's very data driven. Muse looks at all the patient's vitals, medications, physical assessments and clinician notes and then scrubs it through the predictive analytics software. This tool looks at hundreds of points within the electronic medical record (EMR), in fact, it pulls from over nine hundred data points. From this information, Muse is able to rate the patient's condition on a non-critical or urgent scale. They are placed in 1 of 8 care categories based on what MUSE learns from the data. When a patient is placed in the highest category "critical," the patient's likelihood of dying in the next 7-12 days is greater than 90%. As the intelligence platform categorizes and emphasizes those patients who would most benefit from Charlotte MatherBy Charlotte Mather, MBA, RN, FACHE, Vice President of Nursing, AccentCare
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