Sovrinti Case Study

A Perfect Day

Maintaining independence for older adults is a crucial goal in long-term care. Early detection of health concerns plays a vital role in achieving this objective. This case study shows an example of a day where all factors were normal allowing for complete peace of mind knowing that when your loved one says “I’m fine” that they really are.

Background:

The Sovrinti system was installed in a long-term study home for an active couple with independent feedback on status.

Results:

The Sovrinti Daily Risk Level for November 7, 2024, was 0.0. This indicates that all monitored behaviors, including meal patterns, sleep duration, sleep times, mobility, and blood pressure, were perfectly aligned with the individual’s norms, with every subcategory in the green.

Typically, one or more factors fall outside the normal range, which raises the risk level. For example, later in the week, the Daily Risk Levels for November 8 and November 11 were still very low at 0.5.

It's important to note that a Daily Risk Level of 3 or higher triggers an automated alert to caregivers, ensuring timely action when necessary.


Key Insights

These observed subfactors and total score provide confidence that the care recipient is having a good physiological day prompting the opportunity to encourage with good news instead of only dealing with issues and concerns.


Further Research:

Opportunities to track mood and emotional states associated with the various factors is in discussion with this type of low risk level leading to a quantified definition of physiological baseline.

The figure provides an overview of the individual's activity over a week, using color indicators to represent risk levels. The data shows that the individual experienced "perfect" days, with all metrics aligned within the normal range.

Figure 1: The figure provides an overview of the individual's activity over a week, using color indicators to represent risk levels. The data shows that the individual experienced "perfect" days, with all metrics aligned within the normal range