​Staff, administrators, and medical professionals in senior care communities are acutely aware of the increased frequency of urinary tract infections (UTIs) among older adults and how often they are misdiagnosed as signs of dementia.

While these two diagnoses are separate, they are inextricably linked based on overlapping symptoms. One of the most significant and obvious overlapping symptoms is a sudden increase in confusion. This often presents as delirium and explains why many jump to a diagnosis of dementia before testing for a UTI. Other overlapping symptoms include increased agitation, withdrawal, and difficulty concentrating. Yet diagnosis can be further challenging because the typical physical symptoms of a UTI, such as a burning sensation during urination, may not be present in older adults.

Another often overlooked challenge when it comes to proper diagnosis is staff not having enough time with a resident to rule out other health factors. Of course, the faster a UTI is ruled out, the more expedient treatment can be, enabling a resident to resume their regular routine. Conversely, the longer a misdiagnosis lingers, the more detrimental it is for the resident. This includes unnecessary treatments while the underlying infection worsens, longer hospital stays with rising health care costs, and overprescribing antibiotics, along with anxiety.

A helpful way to help differentiate between a UTI and dementia is to understand that dementia, with few exceptions, is often a progressive condition signified by a gradual decline. However, if staff don’t have the ability to spend enough time with residents, progressive declines are harder to spot.

The Role of Technology in Supporting Senior Care Administrators

The common UTI and dementia misdiagnosis is where innovations in technology, specifically artificial intelligence (AI), help provide insight to augment medical expertise. Technology is now enabling care professionals to spot subtle changes in behavior that may signal a longer-term issue such as a UTI well before a test is necessary.

Sensors that combine AI and body-heat-sensing technology can understand subtle movements in a room or a hallway without requiring the use of cameras or other devices that compromise privacy. The sensors can help staff recognize an increase in frequency when it comes to a resident’s bathroom habits. This can signal a UTI. Similarly, they can also be alerted to wandering incidents, which can signal cognitive decline.

The associated data from the sensors provides a benchmark for an individual room. Based on these early indicators, outliers can be more easily detected and often before an infection gets too far along.

Since the data is anonymized, it can contribute to greater industry learnings. Imagine being able to pool data from a larger population of older adults, or across a national care community. Data analysis based on vast amounts of anonymized behavior data can have many benefits.

It can lead to more proactive health planning. It can also help administrators plan for future needs of residents as well as their facilities. Also, the data can shape how they recruit and staff communities.

From a technological point of view, the insights can be used to support the training of data models to analyze actions such as sleep, activities, and social engagement. These additional dimensions of insight provide even more benchmarks across a wider population to better understand the aging process and immediate changes that may need attention.

Taking this even further, the combination of individual and empirical data to better identify the correlations between symptoms will improve diagnostic accuracy.

On a more immediate level, this insight can also help close gaps, especially when it comes to noticing subtle changes in residents that often aren’t detected until much later. This insight helps schedulers know where to allocate staff based on the resident needs as opposed to scheduled physical check-ins.

Weaving Technology into the Senior Care Community

For most senior care administrators, this type of benchmark data is critical. Yet many are concerned that the burden of gathering data and analyzing it adds more to their already overextended schedule. The good news is that the emergence of new technologies for senior care and longevity and making serious inroads in addressing these issues. A closer look at The Gerentechnologist’s Age Tech Market Map provides great insight into the current state of all the emerging technologies being developed specifically to support senior care communities.

As the population ages, with one in six adults being over the age of 60 by the year 2030, there will be increased challenges for the entire industry. Innovations in technology, especially AI, are making significant strides in helping administrators plan more efficiently and respond more proactively to changes.
 
Honghao Deng is a computational designer and entrepreneur, and the CEO and co-founder of Butlr. In his previous role, he was a researcher at City Science Group, MIT Media Lab. He earned a Master of Design Technology with Distinction at Harvard University.