New Eastwood Healthcare and Rehabilitation Center is a 97-bed facility in Easton, Penn. This facility is dedicated to the post-hospitalization care of individuals recovering from joint replacement, cardiac, pulmonary, neurological, and other acute medical conditions.
Reducing rehospitalizations a priority
Although New Eastwood is located just across the street from the hospital, that doesn’t make readmits any less disruptive for residents. Reducing rehospitalizations is better for resident outcomes and cuts costs too.
Yet managing residents is challenging work. The clinical team has little time to pore over all the resident charts to try and identify trends and stem hospital readmit rates. Tired of taking a reactive approach, trying to set up emergency appointments, or looking back to see what happened, New Eastwood researched an affordable technological solution. New Eastwood elected to use SAIVA’s machine learning solution for proactive care to significantly improve outcomes in Post Acute Care at the start of 2021.
Surfacing the relevant data for improved care
Using machine learning and predictive AI, the SAIVA platform scours New Eastwood’s electronic health records (EHR) for indicators that a resident may be at risk. The artificial intelligence solution detects subtle changes in condition that can quickly lead to a serious decline in patient condition. Team members are sent an email identifying the residents most likely to be readmitted to hospital in ranked order helping prioritize care needs and real-time interventions.
Although the technology was met with initial skepticism, SAIVA’s daily reports quickly became an essential part of the workflow at New Eastwood.
“The daily report goes every morning to our supervisors and administrative team as well as our physicians, nurse practitioners, and other direct care people,” said Director of Nursing Karen Sandt. “Every morning at 9 a.m. we use the report in our clinical morning review to get a holistic view of the residents’ conditions and staffing notes.
“It helps us to prioritize as we already have a clear view of patients that have had a change in condition or should be watched for one. This lets the interdisciplinary team at this morning meeting make proactive decisions.”
New Eastwood nursing shift supervisors also use the emailed report as their rounding report. In the morning, when Sandt is preparing for the clinical meeting and catching up on what has happened overnight, she can quickly review the notes supervisors have made directly on the SAIVA resident at-risk ranking sheets.
With SAIVA’s support, New Eastwood today has one of the lowest rehospitalization rates among its peer group.
A positive tool for professionalism and time savings
The AI-powered solution also prioritizes treatments and identifies which tests or treatments a patient with a long-term health condition needs or might benefit from most. Sandt and other nursing supervisors save time previously spent researching and reading the residents’ EMR charts about next steps.
“With the SAIVA machine learning platform doing such a nice job of putting all the relevant information together for us, we can be more proactive,” Sandt said. “The reports put together a whole picture of the patient, so we can get them services sooner.”
The thorough report, with its focused attention to the data that matters, also supports communication across teams, with covering physicians, nurse practitioners, and with resident families.
“The SAIVA report has really helped change the way our staff approach their jobs,” Sandt said. Instead of telling each other what they know, or relying on statements such as “this patient doesn’t look good,” staff can rely on comprehensive data insights to make decisions.
SAIVA’s solution has quickly become an important tool improving quality care and resident outcomes. It’s changed the ways of thinking at New Eastwood. Everyone from residents to staff has benefited.
- Reduced the 30-day readmit rate by 39.7% in six months.
- Improves decision making to drive proactive resident care.
- Provides a comprehensive view of the patient that promotes greater communication internally and externally.