Improving Retention and Reducing Readmissions: How AI is Transforming Long-Term Care

Nurse viewing Caspar AI dashboard
Remote Patient Monitoring

Skilled nursing facilities face a constant challenge in ensuring the safety and well-being of bed-bound residents. Falls from unsupervised bed exits, pressure injuries, and undetected health issues are major concerns for patients, their families and the care facilities. These incidents can lead to:

  • Higher hospital readmissions and ER visits, resulting in lower census and occupancy rates.
  • Lower total satisfaction score from patients and families.
  • Lower Total Quality Scores for facilities, resulting in higher insurance rates and drops in new resident admissions.
  • Reduced ability to provide quality care outcomes.

Traditionally, monitoring these risks has relied on visual checks and patient communication, but this isn’t always the most efficient – or the most effective – way to provide the best care. Let’s take a look at the patient Jane Doe as an example. 

The Case of Jane Doe

Jane Doe suffers from dementia and has been bed-bound for several years. As a result of her illness, she’s not very communicative, which makes it difficult for Jane’s daughter to know how she’s doing or if she’s in any discomfort. It also presents a challenge for her care team, which had to rely only on manual visual monitoring with no input in the form of verbal feedback.

The Caspar AI Solution

Caspar AI offers a unique solution in the form of an automated patient monitoring system. Caspar AI’s system doesn’t require wearables or cameras. Instead, it uses strategically placed sensors to gather data on over 20 health and wellness markers that are key for prevention and early intervention. Data is then analyzed by powerful AI algorithms, which generate AI-driven Care Plan Reports.

A Game Changer for Care Teams

AI-driven Care Plan Reports provide valuable, actionable insights that can be easily interpreted by caregivers, who can then use their own judgment to decide on the best course of care. In Jane’s case, the reports provide:

  • Proactive Care Planning for Increased Retention: The reports revealed trends in her restlessness and pressure scores, while real-time alerts signaled whenever she attempted to get out of bed without assistance, allowing caregivers to proactively intercede to reduce the risk of her falling.
  • Early Detection for Avoiding Hospital Readmissions: The system’s ability to analyze longitudinal data can pick up on subtle changes in Jane’s individual biometrics, vitals and behavior that might otherwise be missed. In Jane’s case for example, the reports identified a spike in her heart rate at a specific time each day, potentially indicating a medication reaction.*
  • Enhanced Quality of Life for Higher Satisfaction Scores: Jane’s care team is now better equipped to monitor her health and well-being, leading to better quality of life.

Peace of Mind for Families

Thanks to Caspar AI, Jane’s care team is now better equipped to support her health and improve her quality of life. This provides peace of mind for Jane’s daughter, who can rest assured knowing her mom is receiving the best possible care and therefore feels comfortable leaving her mom in the facility. As a result, the nursing facility is able to improve retention, build a stronger census, and increase total satisfaction score.

*Actual patient data identified by Caspar’s system.

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