As artificial intelligence becomes increasingly integrated into tools used by senior care and living providers, its uses can be broadly placed into two categories: data analysis and automating routine work.

Some of the best new AI tools that LTC providers should be aware of include the newly expanded Microsoft 365 Copilot and the website scena.ai, according to a new brief guide on AI from LeadingAge. 

The latter was used to generate the opening video at LeadingAge’s conference. 

“At its core, generative AI is a subset of AI that focuses on creating content, whether its text images, music or entire virtual worlds,” a digital avatar told the crowd. “With the right application, generative AI can assist in aging services.” 

While many of these AI tools, and their applications, have been widely available for months, organizations like LeadingAge have been working to advance adoption of these tools, because the LTC industry often lags behind other sectors in onboarding new tech, many healthcare experts have noted. 

Coming into this year, staffing shortages remain an ongoing issue for LTC providers, so the more administrative tasks an organization can devote to AI, the more existing staff and caregivers can focus on resident care.

As for data analysis, AI’s predictive power, which can help predict and prevent falls, was seen as one of the most promising tech innovations in LTC, according to a recent podcast panel for McKnight’s Market Leaders including AHCA President Mark Parkinson.

Seniors themselves may be more open to AI being used in their healthcare systems, or at least accept its presence, a recent report found.

In addition to listing some AI tools and providing a broad overview, the recent LeadingAge post also listed several AI guides for organizations to review, including a report from NetHope and a recent research study published in JMIR Aging.

Although not meant to be used as a primary screening tool, the technology further evaluates skin lesions that doctors have already flagged as suspicious, the FDA noted in an agency news release.  

The handheld device uses AI-powered spectroscopy to assess the characteristics of lesions at both the cellular level and beneath the skin’s surface.

“We are entering the golden age of predictive and generative artificial intelligence in healthcare, and these capabilities are being paired with novel types of technology, like spectroscopy and genetic sequencing, to optimize disease detection and care,” DermaSensor Inc. co-founder and CEO Cody Simmons said in a company news release. “Equipping PCPs [primary care physicians], the most abundant clinicians in the country, to better evaluate the most common cancer in the country has been a major, long-standing unmet need in medicine.”

The device, also called DermaSensor, provides real-time results using an algorithm based on data culled from more than 4,000 malignant and benign lesions, according to the company.

“The device should be used in conjunction with the totality of clinically relevant information from the clinical assessment, including visual analysis of the lesion, by physicians who are not dermatologists,” the FDA said, adding that DermaSensor is for use in patients ages 40 and up.

Along with helping to spot melanoma, the most deadly form of skin cancer, the device can also assess moles for basal cell carcinoma and squamous cell carcinoma.

One in five Americans will have developed a form of skin cancer by the age of 70, according to the American Academy of Dermatology, which puts the cost of treatment in the United States at more than $8 billion. Most skin cancers are curable if detected early.

The FDA added that it is requiring additional validation testing in patients from representative demographic groups, including those who are at lower risk of skin cancer.

More information

The Skin Cancer Foundation has more on skin cancer.

SOURCE: US Food and Drug Administration, news release, Jan. 16, 2024; DermaSensor Inc., news release, Jan. 17, 2024

A high number of senior living and care residents have dementia on admission, or develop it during their stay, despite never receiving a formal diagnosis. 

When these “secret” dementia patients, however, have an emergency – say, a fall – and are hospitalized, they can catch the new care team unaware and struggling to make appropriate clinical decisions. 

To avoid this pitfall, new research is looking at electronic health records to flag individuals who might have dementia, possibly undiagnosed, so that when they arrive at a hospital, the care team is ready. 

The study authors used the example of a person who has had a fall and being unable to accurately describe his condition and medical history, or to communicate his own sound judgments about future care to a hospital team.

Up to 40% of older adults with mild or early-onset dementia do not have dementia diagnoses, one study shows. The new research, led by a team from Cedars–Sinai Medical Center in Los Angeles, noted that “early detection of dementia in the inpatient setting” is less than 50%. 

The research found similar numbers when using AI to analyze EHR records of study participants: Of the 64 patient records reviewed that had no dementia diagnosis, the AI found 33 shown signs of altered mental status or cognitive dysfunction. Overall, that involved approximately 10% of the EHR records reviewed, which included both people with confirmed dementia and those who showed no record of cognitive decline.

“These types of algorithms provide an opportunity to accurately identify hospitalized older individuals for inclusion in quality improvement projects, clinical trials, pay-for-performance programs and other initiatives,” the study authors concluded.

To make sure clinicians are able to take advantage of the new information the AI can give them about patients, Cedars-Sinai also instituted a training program to make sure all care staff knew how to respond to possible dementia. 

Data sharing between points of care and different EHR systems is becoming increasingly important for healthcare providers, as health records are constantly updated from new data collection tools. 

Although the dementia research foretells a positive outcome for both patients and their caregivers, the flip side of that is the unintentionally morbid study on EHR discrepancies — also from California — that showed that care teams were filling medications and appointments for patients who already had died, the McKnight’s Tech Daily recently reported.

Healthcare software and long-term care providers are on the same page in using technology to shape care goals, according to some leading executives in both fields.

As senior living and care providers and associations have focused on the concept of value-based care, which ties finances and insurance coverage to residents’ quality of life, tech developers have moved in tandem to meet the twin goals of reducing costs and improving services.

Although many new innovations have helped achieve this aim, healthcare leaders have expressed the greatest enthusiasm for the future of artificial intelligence and predictive analytics.

“Early is critical with seniors,” said Allison Rainey, head of nursing and clinical informatics for MatrixCare, during a recent discussion for the McKnight’s Long-Term Care News Market Leaders podcast. “We can really impact outcomes if we identify changes early. Proactive tools are critical. But too, because time is so important, we can identify the plan of care that might be appropriate.”

The panel included Rainey; Mark Parkinson, president and CEO of the American Health Care Association/National Center for Assisted Living, and Bharat Monteiro, MatrixCare’s general manager for senior living. The experts discussed the need to coordinate on new software and tech tools so that they are both easier to use for providers, and tailored to their needs.

MatrixCare has been one of the leading companies developing interoperable tools for long-term care operators, so that resident and patient information can be shared along different points of care, such as hospitals and nursing homes. 

That can be a moving target, as the benefit of AI’s analytical and predictive capabilities also generates a mountain of data that must be contextualized, Rainey noted.

“Health journeys are very complicated,” she said. “What is meaningful and what is not? More interoperability means more patient data coming in. How do we include the social determinants of health in that? Now we have great AI tools to serve only [relevant] changes.”

Monteiro offered the example of increasingly robust falls prediction tools, for how tech is advancing to both improve resident and patient health and reduce costs. Falls can cost communities and facilities an average of $380,000 a year, and it is anticipated that residents will fall at least once during their stay in a residential care setting, Monteiro noted.

“AI can look at falls and data points and stratify patients into the highest risk [level] for falling. That’s the opening step,” Monteiro said. “If I can create smart care plans, then I’m able to provide proactive care for residents. If you reduce falls, you’re automatically keeping the patient in that area of resident longer, and the provider has better financial benefits because they’re not dealing with as many fall repercussions.”

Parkinson agreed and noted that, from a policy perspective, the key will be for providers to control hospitalization and re-hospitalization rates.

“If you can keep your hospitalization rates low, you will do really well in value based purchasing,” he said. “And I don’t think it would be possible to slaughter your re-hospitalization rate if you weren’t using EMRs [electronic medical records] or tools that EMRs provide.”

The panelists also noted that, for the time being, clinicians’ anxieties about new technology replacing them are unfounded and that care providers are stressing that human healthcare workers still must make the final decisions and analyze information from new software and predictive AI.

In fact, a recurring theme in high-level analyses of AI over the past year is that new tools can take over the more mundane, frustrating tasks that clinicians and caregivers have to do and can free up more time for them to work directly with residents and patients.

During our final session, we tried to help them pare back their goals, but they fell into the problem many companies are facing. They were struggling to prioritize and, against our advice, they felt that they needed to begin to address each item all at once. 

Senior living business leaders and companies are facing a very similar challenge in 2024, and should they fail to focus and prioritize addressing the greatest issues they face, they will soon find themselves asking how they didn’t make any headway in 2024 and what to do about it in 2025.

This can prove challenging, as these companies aim to meet immediate financial targets and operational goals while they also need to lay the groundwork for sustainable growth, innovation and quality improvement in the long term. To cut through the noise, leaders must strategically focus and prioritize the right challenge by determining its urgency over its relative standing in the hype cycle.

So, let me help with that. Here are the four challenges and their implications that leaders and companies could face that must be addressed if they are to not only survive 2024 but thrive.

1. Today’s trendiest AI isn’t everyone’s best tool

Senior living businesses have arrived at a crossroads in 2024. Integrating artificial intelligence into general business practices has become an imperative and an untenable obstacle course.

Many companies are moving forward with the misguided hope that the benefits will outweigh the upfront costs, and that can be true. AI can personalize care, customize resident plans, provide predictive analytics and tell you what your budget could be next year.

Companies, however, will need to make smart choices, as not all AI models are built and, more importantly, trained, equally. Choosing the wrong model means a potential for a closed-loop input system where the model does not consider outside needs of potential future customers other than what it was trained on.

To make the most of AI, businesses should prioritize models that have transparency and ones that can help them fix their fragmented data. Siloed records, notes, charts and schedules in multiple platforms that lack interoperability means there will be limited value in the analytics from a model only able to pull from one source of data. The integration challenges are real, but the potential is transformative.

2. The demographic cliff

It’s not news to you that senior living businesses are facing the stark reality of the increasing number of potential residents and a lack of talent to care for them. As baby boomers continue to age and look to move into active-adult or various other tiered classes of caregiving, not only are the communities lacking or nonexistent, but so are the caregivers. Flexible working options and higher pay elsewhere are fueling resignations.

To address those challenges, businesses need to consider new development routes for staff and properties. Considerations for creativity in how administrative roles are staffed and developed through training and upskilling local community members is one way to start.

Long term, the labor shortage may mean rethinking on-demand workers over full-time hires. Also, there is the potential for modular construction, and investors looking to be recession-resilient could mean new forms of capital that could allow for the right-sizing of the units and technologic improvements needed.

3. Transparency versus personalization versus privacy

Senior living companies have leaned heavily on personalization to drive engagement. Data collection can provide unique offerings, especially with the advent of wearables, which can help customize meal plans, activities, amenities and medicine, but consumers and clients have begun to demand more privacy and protection of their data.

Businesses must become more transparent about where they collect data, where outside data are being used and what is done with them. If done successfully, the transparency can bolster engagement and increase communication between the residents and the communities, another potential data perk.

Equally important will be open communication on issues such as sustainability, social responsibility and employee well-being. Today’s residents and families expect more transparency. Companies that honestly address their practices and shortcomings will build trust. 

4. Inflexibility in your future direction

Operators facing these pressures often suffer from a lack of agility and flexibility in their planning. Anticipating future challenges in healthcare and demographics is crucial yet challenging, especially with limited resources, as those challenges constantly move.

Even with prioritized challenges to address, however, leaders must be open to being nimble enough to adapt their hardened three- to five-year plans while also realizing that type of planning needs to shift to become 10- to 15-year planning. This change will allow them to be ready for shifts in behaviors, to grow as digital health evolves, residents’ preferences morph and staffing dynamics shift.

Allowing for re-perception of the challenges and trends that are faced throughout the year will allow companies to be proactive instead of responsive. Most companies lack this flexibility, which ultimately means they stay the course when they need to pivot and, in doing so, become obsolete to the whims of their clients and residents.

In 2024, these challenges and trends are not just obstacles but also catalysts for innovation and improvement. For business leaders, particularly in the senior living industry, addressing these challenges head-on is not just about survival but also about thriving in an ever-changing landscape. By doing so, you can ensure sustained growth, improved service quality and enhanced operational efficiency, ultimately leading to long-term success and a positive impact on your communities.

Mark Bryan is the senior foresight manager at the Future Today Institute, an advisory firm specializing in strategic foresight aimed at driving corporate strategies that lead to long-term success and resilience. The institute partners with leaders of Fortune 500 companies, world governments and other major organizations to help them pivot, adapt and thrive in the face of disruptive change.

The opinions expressed in each McKnight’s Senior Living guest column are those of the author and are not necessarily those of McKnight’s Senior Living.

Have a column idea? See our submission guidelines here.

Many have fancifully wished for a mirror that could look beyond the surface and deep into one’s heart. 

One new tech company has taken this concept literally and created a “smart mirror” device that can accurately assess vital signs such as blood pressure and even risk of heart disease. 

The MagicMirror, developed by NuraLogix, currently is being marketed to senior living and care operators and others, the company announced this week. 

“Gathering health data in this method without requiring tedious multiple manual inputs provides ease of use, especially for those with mobility issues and elderly populations,” the company said in a statement.

The mirror, which was showcased at this week’s Consumer Electronics Show in Las Vegas, works by analyzing facial blood flow. In addition to analyzing a variety of heart conditions, including risk of disease or stroke, the mirror also can make an assessment about a user’s stress or mental health condition. 

Since artificial intelligence capabilities have blossomed over the past year, developers have tried to train AI tools to interpret a large body of data, and images, to make useful health predictions.

Many older adults who have heart conditions are not currently using tools to appropriately monitor their symptoms, so any tool that could make it easier to do so could help prevent health emergencies. 

Although the NuraLogix mirror appears to be connected to a proprietary screen device, other developers have introduced AI-aided diagnostics that can be used via smartphones. 

One AI app, Together, interprets selfies to record blood pressure and heart rate, the McKnight’s Tech Daily reported over the summer. 

Collectively, those innovative tools underscore the value of AI to skeptical seniors. Because of these innovations, more older adults not only are accepting but also expressing enthusiasm for incorporating AI into their healthcare routines, a recent report showed. 

One of the most debilitating symptoms of Parkinson’s sufferers is the loss of control of their gait while walking. 

Two technological breakthroughs could help people living with Parkinson’s disease regain this control: Music-based software that helps stabilize the pace of walking, and a wearable robotic exoskeleton that would stabilize a user’s muscle movements. 

The findings come from two separate studies out of Boston University’s Center for Neurorehabilitation, but they are not mutually exclusive. Senior living and care providers in the United States may be able to look into multiple options for the hundreds of thousands of long-term care residents in whom Parkinson’s has been diagnosed. 

While the music software program is based on a clinically validated technique — rhythmic auditory stimulation — the concept of providing an audio cue to stimulate movement is not necessarily new. The study participants did get shoe sensors to help provide better diagnostic data. 

The relatively more innovative wearable robotic exosuit, developed by ReWalk, involves a banded series of cables, motors and sensors that go around a users’ thigh and waist. The device, which augments muscle with mechanical force, was specifically tested to help with the freezing of gait, one of the most common and concerning Parkinson’s symptoms. 

Although the study involved just one participant – a 73-year-old male with Parkinson’s – the freezing of gait was “instantaneously eliminated,” according to the researchers, and the tool’s impressive results were demonstrated in a video showing him walking smoothly down a hallway with the device’s assist, compared with stopping and stumbling when it was off.

Several innovations have come out in recent years designed to alleviate various Parkinson’s symptoms or monitor the disease. A wearable wrist device designed to treat hand tremors was released by biomedical company Cala last year. 

In addition, although the ReWalk system already is commercially available, other researchers are looking into tools that involve wearable robotics for rehabbing people who have had a stroke, the McKnight’s Tech Daily recently reported.

Over the past few years, robotics developers have found conclusively that those high-tech companions are a welcome addition to senior living communities. 

Now, developers are further augmenting their robot pals with new tricks and personality. 

One of the companies at the forefront of introducing robots to long-term care settings, Intuition Robotics, is releasing its third iteration of ElliQ, which was conceived as a way to address older adults’ feelings of loneliness and isolation. 

One of the major innovations of the new model is a lighter, smaller design that is easier for older adults to handle, the company said. Even the earlier iterations of ElliQ were small, table or desktop-mounted devices that somewhat resemble the Pixar lamp. 

While they continue to fine-tune the robot’s capabilities, Intuition also is learning new insights about how interaction with ElliQ differs between demographics, Intuition Vice President of Strategy Assaf Gad told the McKnight’s Tech Daily on Friday. 

“The majority of ElliQ users are women,” Gad said. “And while everyone engages with ElliQ, rural users use it as a communication tool for family members, while in more urban areas, we’re seeing it used more for health and medication reminders.”

Gad cautioned that those trends are not definitive but said the company does have enough data to provide a meaningful snapshot of where the assistive robots market is at.

In addition to the updated design, ElliQ 3.0 also has new artificial intelligence capabilities that allow for more advanced conversation, Gad said. The robot now also can connect users for Bingo games and other synchronized events, the company said.

“We want to help older adults have a more meaningful conversation [with ElliQ],” Gad explained. “This allows us to learn more about their needs. And that empowers older adults to stay more independent.”

One way ElliQ could achieve this goal is by collaborating with older adults on cooking recipes, Gad noted. The new version of the robot can remember and draw on past conversations to help build recipes for a gluten-free or diabetic diet, or it can use that context to advise on how someone can combine ingredients that are in the refrigerator. 

While ElliQ’s conversational abilities are becoming more intelligent, the company has remained steadfast in the contention that the device is not a replacement for human interaction, but rather a tool to help foster it. 

“We try to bring trust and empathy to the table,” Gad said, “but it’s always a combination of the human and robotic touch.”

In the valley of the blind, the AI-ed man may be king: New research suggests that machine learning and artificial intelligence tools could be used to provide early detection for visual impairment in older adults.

The advanced pattern-detection capabilities of AI are allowing for new insights into how diseases form and can identify the onset of conditions at ever-more granular levels.

One recent study was able to analyze deposits in the eye at the molecular level and begin establishing how such disease-causing deposits first begin forming. 

Approximately two-thirds of nursing home residents may have some form of age-related macular degeneration, or AMD, with 23% of those seniors being fully blind, data show.

The ability to catch visual decline relatively early on is important for older adults and their caregivers, because the more advanced AMD becomes, the more costly and complicated treatment options grow, one story notes. 

Poor eyesight contributes to some of the biggest long-term care concerns, such as lower quality of life and falling risks, studies show.

In addition, AMD and visual impairment could be linked to higher risk for dementia, the McKnight’s Clinical Daily reported last year.

Due to the highly specialized nature of the research, the immediate application of the study can be difficult to see. The focus was on lesser-studied “subretinal drusenoid deposits,” or SDDs, a category of tissue whose link to blindness has only recently been established, the researchers said.

Nevertheless, the machine learning tool, combined with mass spectrometry, was able to evaluate the build-up of SDDs in extremely thin retinal samples, one story explained. 

The analysis not only can be used to identify visual impairment at an earlier stage than before; it provided new insights into how SDDs are actually formed, the researchers said.

“These examples demonstrate that automation in this manner can be utilized not only for confirmation and exhaustive assessment,” the study authors noted, “but also for generation of new hypotheses and guidance for targeted downstream analysis.”

New tools such as passive sensors and artificial intelligence are growing rapidly within senior living and care. 

Although various studies show mixed responses from older adults toward accepting those technologies, at least one company is offering training and question-and-answer sessions to help ease residents’ concerns. 

“Seniors have a lot of questions [about our technology],” said David Ly, CEO of Iveda, whose AI-enabled monitoring system, IvedaCare, helps prevent falls. “They ask: What is it going to do? Is it going to be listening to me? Watching me? We have to show them: Traditional alarm systems in our house are similar.” 

Ly, who has visited some assisted living communities personally to discuss Iveda’s technology, said it was important to explain to residents what AI is and what information it is sharing.

Iveda is one of several emerging companies now trying to carve out a niche within both independent living and assisted living living; although most AI-enabled sensors work on similar principles, experts have told the McKnight’s Tech Daily that much room to grow remains within the industry. 

Iveda hopes its educational outreach increases buy-in to its tech; the company also has made inroads with care for older veterans. Iveda was awarded a contract to add its fall detection and telehealth software in VA facilities, the company announced last summer.

Although Ly, like many others, characterized AI as a powerful data collection tool rather than some mysterious entity, he acknowledged that popular perceptions have been shaped negatively by film and TV portrayals of robots or AI gone rogue.

“We use all kinds of analogies for AI,” Ly told the McKnight’s Tech Daily on Wednesday. “At the end of the day it’s just one tool to help us achieve [health outcomes]. Hopefully, it will only become more accurate, and more compassionate.”