St. Croix Hospice recently unveiled data showing how the company leveraged predictive analytics technology to improve quality outcomes.
In 2019 the Minnesota-headquartered hospice provider began utilizing a predictive analytics tool from Medalogix. The post-acute data analytics company develops machine learning solutions designed to identify patients in need of home health, hospice or palliative care services as early as possible in the course of their illnesses. Medalogix’s Muse platform is also designed to identify patients at high risk of hospitalization or clinical decline and assists in care coordination across the health continuum.
St. Croix Hospice and Medalogix recently released results of how predictive analytics technology utilization has impacted care delivery. The technology has aided in raising quality ratings among patients within the last seven days and led to improved care transitions through more responsive patient attention and interaction, the case study data found.
The most significant impacts have been patient and family satisfaction, according to Ashley Arnold, vice president of clinical services at St. Croix Hospice. The ability to more accurately predict and identify declines has also helped staffing resource allocation, Arnold indicated.
“Back in 2019 we were really looking at how we could enhance our presences, and how using end-of-life technology could help guide us to being at the right spot at the right moment for our patients,” Arnold told Hospice News. “What we found with this tool is that we could transition patients in need quicker, identify declines faster and get the appropriate team members there to be with them in a timely fashion, especially during those last and important days of care.”
Established in 2009, St. Croix Hospice cares for more than 4,400 patients daily across its 10-state service region. The hospice provider is a portfolio company of the private equity firm H.I.G. Capital.
Through the predictive analytics data, hospice patients at St. Croix received an average of roughly 10.3 visits in the last seven days of life between May and November 2023.
Quality ratings among these patients and their families reached 90% higher than national averages, the case study found. Additionally, 90% of families reported a willingness to recommend the hospice provider to others.
The case study analyzed results from Consumer Assessment of Healthcare Providers & Systems (CAHPS) surveys and the U.S. Centers for Medicare & Medicaid Services’ (CMS) quality measures such as the Hospice Quality Reporting Program (HQRP) and the Hospice Item Set (HIS).
Leveraging predictive analytics technology has helped address a challenging issue for many hospices – balancing clinical capacity with patient demand, according to Arnold. Not only have daily clinical visits in the last week of life improved, so too have bedside presence from other interdisciplinary team members such as social workers and chaplains, she stated.
“Identifying patients a little sooner with technology can allow those patients to have longer and more visits at the end of life,” Arnold said. “We’ve gotten a lot of positive feedback for it. That’s really one of the biggest challenges you face is just that unknown piece of technology and embracing what it can show. It doesn’t replace the care provided, it enhances what we can provide for our patients. From a staff perspective, the quality it adds is another tool in their toolbox to make sure patients that need us the most are identified at those moments. It builds upon our culture of high quality care.”
Predictive analytics technology can give hospice providers expanded visibility into patient conditions and overall experiences as they reach the most critical stages at the end of life, according to Amie Nangle, client success executive at Medalogix.
“[Having] these unique insights and focus on end-of-life care also helps St. Croix manage regulatory compliance,” Nangle told Hospice News in an email.
Hospices have increasingly used these systems to build their census and improve performance on quality measures, Nangle indicated.
Hospices can leverage predictive analytics to gain a clearer picture of their quality performance amid ongoing regulatory pressures. Hospices have increasingly honed data insights to enhance their ability to assess the quality and quantity of bedside care delivered during a patients’ final days.
This includes two key quality measures: Hospice Visits in the Last Days of Life (HVLDL) and the Hospice Care Index (HCI).
The benefits of predictive analytics tools can be two-fold for hospices in terms of both patient and staff satisfaction, with opportunities tied to retention as well, Nangle stated.
“Our findings showed improvement in HCI measures which drive quality, including increased nursing and social work visits and time spent in the home to support patients and their loved ones and caregivers in the last seven days of life,” Nangle said. “Even more importantly, it’s helping with staff satisfaction. Keeping and maintaining skilled nurses is always a challenge, leveraging Muse helps to prioritize a clinician’s daily schedule and support clinical decision making around each individualized patient’s care. We’ve also heard it allows them to put their focus back on why they are in this field to begin with – to care for their patients.”
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