​Long term care and technology are becoming more comfortable partners in the drive to improve the lives of seniors and to create new economic efficiencies.

 

But the form of this push for high-tech solutions is moving beyond just the latest advances in software for electronic health records (EHRs) and telemedicine to other specialized fields, like sensor technology.

It is here, experts say, that real promise is being shown in advancing from relatively basic sensors that track heart rates and oxygen flows to more precise and in-depth health monitoring for seniors living independently and in skilled nursing care or assisted living communities.

The goal of sensor technology is to allow clinicians an early peek at possible future chronic illnesses for those not yet under full-time care.

Then, later it can be an unobtrusive companion in a facility setting to detect falls; measure restlessness while sleeping; and keep nurses, doctors, and residents and their families informed with the latest cutting-edge data.

Sensors and tracking programs like imaging technology are by no means the norm in every skilled nursing care or assisted living community, but the hardware does represent another option for providers to consider.

Sensor technology developers say the up-front cost of buying their creations is well worth it, as the aim is to make quality of care better and cheaper in the long run. They point to new-generation hardware that allows not only for the increased safety of the elderly, but also the ability to collect data that will benefit individual seniors and the broader long term care community.

In seeking a closer look at these tools, it makes sense to start with the University of Missouri. This is where sensor research and development have a home base, considering that the school’s innovative multidisciplinary Center for Eldercare & Rehabilitation Technology and real-life seniors’ health research “laboratory” Tiger Place (named after the school’s mascot) are here.

Researchers working across the nursing, engineering, and computer fields at the university have come together to dig into the issue of how sensors and imaging hardware can be used to keep seniors living independently for longer durations than was previously possible. And, once in a facility-based setting, the hardware attached to software in EHRs can improve residents’ lives by tracking chronic conditions more ably.

Some examples of these projects—which have won grant awards from the Centers for Medicare & Medicaid Services (CMS), the National Institutes of Health, the National Science Foundation, and the Agency for Healthcare Research and Quality (AHRQ), among others—include subjects like Linguistic Summarization of Sensor Data for Early Illness Recognition in Eldercare, EAGER: An In-Home Health Alert System with Remote Care Coordination, and Technology to Automatically Detect Falls and Assess Fall Risk in Seniors Housing.

Current and past research at the university is attempting many different things, but the overarching goal is to set benchmarks for those studied at Tiger Place and elsewhere for gauging how sensors and imaging can shift the quality and cost dynamics, says Marilyn Rantz, curators’ professor emerita, nursing lead,
School of Nursing at the University of Missouri in Columbia.

“When Tiger opened [in 2004], we hoped that we would have infrastructure in place to test the development of sensor technology…to give us technological solutions to help people age in place,” Rantz says.

“So two years before Tiger opened, I went to the College of Engineering and said, ‘We need you to help us and come on this journey.’ I did a presentation and challenged them to build technology to help address the complicated problems of aging, because as a researcher I’ve seen the same problems essentially throughout the whole 40 years of my nursing career.”

Those “same problems” revolve around functional decline, incontinence, malnutrition, and cognition slippage.

“Many of us had been researchers who had attempted to define good solutions to those problems, but really over the long haul, we have not made much of an impact,” Rantz says.

But when the engineering department stepped forward, notably in the form of Marjorie Skubic, PhD, then things started to happen, she says. Skubic is Rantz’s longtime co-conspirator of sorts in seeking technological advances to aid seniors. She is the director of the eldercare center and a professor of electrical and computer engineering at the University of Missouri, Columbia.

Over the past decade plus, the two, along with others at the school and across the country, have advanced the case for sensors. In the initial days of their work, the team at Missouri developed methods for automating a new depth image sensor, since patented, which focuses on fall detection and fall-risk technology.

“We did an interesting grant that was funded by AHRQ where we looked at radar technology, and Marge had a hit at the same time on a National Science Foundation grant. So we combined our efforts and installed at Tiger a whole battery of different potential sensors to do the fall-risk assessment and measure it simultaneously while we were doing a clinical trial on measuring fall risk against standardized instruments that you typically used to measure fall risk,” Rantz says.

What the pair discovered is that vision-based sensors worked better than radar-based devices for the purposes of commercialization, and that is where they continued to put their efforts as new versions of their sensors were developed over the years. The vision sensor looks like a camera with its “eye” or lens, but does not take traditional pictures as it instead “searches for measurements on distances of moving objects in front of it,” Rantz says.

All told, the lessons learned at Tiger Place are that one can increase the length of stay in seniors housing by 2.5 years by adding sensor technology, along with nurse care coordination, and improve lives in the facility setting.

“It’s stunning. You can actually do this and measure this,” Rantz says. And it is not terribly expensive and will get cheaper as time moves on, she adds. “With nurse care coordination it is $300 to $350 a month to pay for sensors and the cost of storage for the data.”

Tiger Place researchers are also working on other applications of technology for facilities. For instance, Rantz says, as part of a project funded by a CMS grant, her team is running a demonstration in 16 skilled nursing care centers. Staff in the centers are learning to use secure communication technology in addition to EHRs. Secure communication with other providers speeds up and improves the accuracy of the work of advanced practice nurses who are providing care to residents with more acute illnesses.

“For many of [the nursing centers], the only part of the health record that is electronic is billing and for MDS in the nursing home setting. And assisted living is even further behind,” Rantz says. But her team has encouraged the centers to start using secure communication methods and portals to capture EHR
information to straighten out medication records when a person goes back and forth to the hospital. “And they’re getting up to speed,” she says.

The research team also is working on assisted living applications. It is installing sensors so that automated alerts from the data become part of the normal workflow to inform staff decision making. With the sensors helping them, staff can detect increasing fall risk and health changes two to three or more weeks before the resident falls or has a serious change in health that requires hospital care.

“These are new ideas for clinical staff. At first they react with a healthy dose of skepticism, but after awhile they come to rely on [general] fall-risk alerts, health alerts, and real-time alerts of falls detected by the sensors,” Rantz says.

From the engineering side, it has been important to make the technology as invisible as possible to the user, Skubic says. Her research team began by using simple motion sensors, coupled with a basic sensor (about an inch wide and several inches long, flexible, and about one-quarter inch thick) that was positioned on top of a mattress under the person’s upper torso, which was not ideal as far as keeping the sensor hidden. The sensor detected energy changes from the person and transmitted it as a wave form that could be analyzed.

In the case of Skubic’s work of caring for the elderly, the first such sensors deployed on tops of beds and allowed researchers to gauge whether bed restlessness, qualitative heart rates, and respiration rates were low, normal, or high. But the system in use today has evolved and improved with a much better bed-sensor device that is now placed below the mattress, making it less obtrusive. “Some residents had complained,” Skubic says.

These newer sensors also do much more than their predecessors, giving quantitative measurements of pulse rates, respiration, and restlessness.

“These are actual heart and respiration rates, and through the data you can see clear ballistocardiogram signals of people as they sleep without the sensor having any contact on the body,” she says. The term ballistic refers to the mechanical effect of the blood flowing through the body. It is similar to the well-known electrocardiogram that most people are familiar with, which measures the electrical activity in the heart.

The Missouri researchers also have been using depth cameras, or depth sensors. These produce a depth image wherein each pixel of the image is measured for its distance to the nearest object.

“We use that depth sensor to track people. And what we get is a three-dimensional silhouette of people moving around” protecting privacy as the image is not overly detailed, Skubic says. “From that we can compute walking speed, gait parameters, walking time, stride time, stride length, and sway, which sometimes represents balance issues.”

These walking measurements and movement data are invaluable in determining if fall risk is on the rise for patients. “Of course we would like to eliminate falls,” she says. “So if you know somebody is at increasing risk of falling, then if you can get them some kind of intervention, and usually as this has something to do with balance issues, then you can prevent the fall. We also do automated, immediate fall detection using these same depth sensors, so that people don’t end up lying on the floor for a long period of time.”

There are other ways these and related sensors can give nurses and other clinicians very early warnings to potential health problems. An example Skubic gives is that sensors indicate when somebody may have a urinary tract infection (UTI). This can be detected through analysis of the sensor data and imaging because some of the many signs of UTI complications, even before they become a full-blown infection, are related to gait and bed restlessness, as well as more frequent use of the bathroom.

“By monitoring with these motion sensors, it is pretty easy to detect changes in behavior,” she says. “We have caught congestive heart failure because of sleeping patterns, as another example. It is all about breaking the cycle of rehospitalization, which is where these conditions, if not caught, will likely lead.”

The commercial offshoot of the work being done at the University of Missouri is in the control of George Chronis, PhD, chief executive officer and co-founder of Foresite Healthcare in St. Louis, Mo., which started operations in 2013. The company markets products on an exclusive basis from the work done at the university for, among other things, the early detection of strokes and fall prevention, Chronis says.

Foresite has two products for two different platforms. One, called Foresight Patientcare, is for acute care, and another, Foresite Eldercare, is for assisted living, skilled nursing, and memory care centers, as well as independent living, Chronis says.

The Eldercare platform consists of the actual sensors, the computer software to turn the data collected by the devices into actionable medical information for a patient, and the services that connect the technology to medical staff. The goal of the product is to increase both resident safety and the length of stay for patients at their current level of care.

“So if you are in independent living you stay there. If you are in assisted living, you stay there as long as possible,” he says.

The way the technology works is by having the system of sensors installed, which range from motion sensors to bed sensors to imaging sensors and through these devices collect data over long periods of time. This in turn, Chronis says, allows the system to create algorithms via artificial intelligence (AI).

AI allows for the analysis of the data that can compare changes over time so that caregivers can look for patterns in patients’ medical conditions and behaviors.

“When such matches between the changes of data are found, then the system will issue an illness alert to the health care professionals,” Chronis says. This allows the nurse or doctor to go into the system and look at what these changes are and potentially discover how they have affected the health of other residents in the past. These benchmarks can lead to better care coordination via shareable EHRs as issues arise and are documented.

The combination of having data from sensors for use on the clinical side is where patients can benefit with better and smarter care, and where providers can save money from getting to a problem before it blossoms into something much more serious.

“The effect we have seen from this technology in length-of-stay statistics is that the stays have more than doubled, almost tripled. We have seen studies by our clients that have shown length of stay moving from 1.8 years to over four years,” Chronis says.

Like any technology, the sensors have an up-front cost. “But you don’t have to wait too long to see the [return on investment],” he says. “Say you are in independent living and have to have a home nurse: a costly service, present five hours a day for assistance at $20 an hour, which is the typical rate. It is much more efficient and cost-effective [to have] a system like this that can send data and monitor remotely for $200 a month. If it turns out a nurse is needed, they can take it from there.”

Another player in the commercialized sensor space is Right at Home, which provides in-home monitoring services, according to Mike Flair, vice president of franchise business solutions. He says the company offers two different remote care systems through its partnership with Philips: Well-Being Monitoring service and Routine Check-In service.

“The Well-Being Monitoring consists of small sensors placed in key areas of the home based on a client’s normal activity. When changes in pattern are examined, Right at Home will contact the client for a well-being check,” he says.

The Routine Check-In service also schedules virtual, face-to-face visits with clients on a provided tablet in order to engage in light social interaction as well as note mental awareness and hygiene. “At the moment, we have more clients participating in the Well-Being services,” Flair says.

For seniors not yet in need of skilled nursing or other supervised living, the sensors allow for individuals to live independently in their homes, yet still keep their family members and care providers aware of their health.

As for privacy concerns or the devices disrupting normal life, Flair notes that feedback from users and their families has been “very positive,” since the technology works for such an important purpose.

Bringing technology to bear in health care and, more specifically, in long term care, is something that Gregory Alexander, PhD, a nursing school professor at the University of Missouri, Columbia, has been examining for years. His work has delved into many different aspects of the issues of why technology in long term care has lagged, with the obvious reasons being tight profit margins, along with a lack of executive leadership and a workforce to manage sophisticated systems.

“I don’t think it is just money. For example, there are differences in for-profit and not-for-profit [long term care providers],” Alexander says. “The not-for-profits tend to have greater sophistication of IT than for-profit, but we don’t necessarily know why.”

It is also not as easy to say there is better technology in more urban skilled nursing care centers or assisted living communities vs. their rural counterparts, with some rural operators quite ahead of the pack on bringing technology into their daily operations. It just depends on whether the leadership of a center or chain makes technology upgrades a priority or has experience in tech-related work.

But there are monetary and market-based incentives, like referrals from acute-care hospitals, to avoid rehospitalizations and other medical problems, Alexander says. Citing an initiative in Missouri to improve quality, he says communication and tracking of patients is at the center of the effort, be they with sensors and EHRs or solely EHRs and sharing the documents of care.

“The overall goal is to reduce avoidable readmissions. Both hospitals and nursing homes are being held accountable for readmission rates,” he says. “If we can eliminate them, it helps both sides of the equation.”