One of the biggest challenges that the senior living industry has faced over the past few years has been attracting and retaining staff. Thus, it is important to use technology to optimize staff efficiency and avoid staff burnout, especially as we consider the incoming demographic changes with members of the Baby Boom generation start aging into senior living communities. The time is now for analytics to become a core resource for operators to help their residents and staff thrive.
Analytics will evolve from their current state, where they commonly are limited to simple utilization reports, to become far more advanced, allowing operators to make better decisions on how to best ensure the success of their most valuable resource, their staff members. This evolution can be broken down into four phases: descriptive — basic, descriptive — advanced, predictive and, finally, prescriptive.
We’re largely in the descriptive — basic phase within senior living. This reporting is invaluable in creating operational decisions, but there is so much more that can be done as the systems in senior living increase in complexity.
As an example, let’s look at emergency call analytics. Those analytics have been around for decades and provide useful roll-ups, such as the number of alarms answered by a caregiver. This is a great starting point to grow from, but we can now focus on developing analytics that help operators determine how to staff optimally, such as understanding how many alarms a caregiver is expected to respond to on a particular floor.
Our goal here is to optimize staffing so that the number of alarms a caregiver must respond to within a building is consistent, regardless of the number of residents. Even though those are descriptive insights, we can use these analytics to help ensure that residents have an equal experience throughout the community and that caregivers can avoid burnout.
With this foundation, we can grow even further into predictive and prescriptive insights. Using advances in data science and the detailed data now collected, we can create robust predictions in communities, such as how many alarms will be triggered. The next step would be to use those predictions to create recommendations for operators.
For example, we can predict that there will be significantly more alarms on Monday after a long holiday. After that, we’ll move into prescriptive analytics where we will suggest the number of caregivers per floor to ensure a target time to respond to alarms.
The advanced version of descriptive analytics already is available in the market, with predictive and prescriptive coming soon. Beyond that, prescriptive analytics will be paired with generative artificial intelligence, providing operators with the ability to ask questions about their data. Most insights will answer most of the questions an operator has, but the last few are unique to each community.
The power of rich data capture combined with advanced algorithms will be combined to address those questions. Through those analytical advancements, communities will provide a better level of care for their residents and a better work environment for their staff members.
Kunaal Goel is vice president of analytics and insights at Sentrics.
The opinions expressed in each McKnight’s Senior Living marketplace column are those of the author and are not necessarily those of McKnight’s Senior Living.
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