The use of healthcare technology solutions in clinical settings is a time-tested conventional practice, and it’s becoming more commonplace in remote patient monitoring (RPM) as supporting technologies drive more innovation. With the broad range of care encompassed by the term “RPM,” there are a number of factors that can impact the overall effectiveness of monitoring patient vitals and other physiological parameters in remote, non-clinical situations.
When a patient transitions from a hospital to a remote or at-home setting they are essentially moving from a controlled environment to one that is highly variable. Three key factors contribute to this variability: 1) patient adherence, 2) patient activity, 3) ambient exposure.
1. Patient Adherence
One big challenge with RPM is whether the patient complies with instructions on using RPM technologies. Simply put, if the patient does comply it will be very difficult to capture relevant medical data from that patient. Unlike clinical settings where there are staff members who can ensure patient compliance, in most cases the patient is on their own while at home. To mitigate against non-compliance, RPM technologies should have a combination of ease-of-use and comfort.
Ease-of-use can be as simple and important as the font size in user manuals or product interfaces. Often overlooked, many products appear to be designed for twenty- and thirty-year olds with good vision. But RPM often applies to patients over 50, and many with poor eyesight.
Size and weight are also major considerations. Less mass in general is preferable, but small doesn’t always equate to comfort. Medical devices that are designed for ease-of-use as much as medical accuracy will have the best chance of compliance by the user.
Appearance is another factor, especially if a patient is expected to wear it while interacting with others or while at work. No one wants a visible device that draws unwanted attention and curiosity from others.
2. Patient Activity
With remote monitoring, a patient’s ability to move about can vary greatly. Some may spend most of their day in bed, while others are fit enough to go about their daily routine. Movement is one of the biggest contributors to poor data quality. Some parameters such as heart rate can be reliably captured even with movement, while others require patients to be still.
For example, to monitor for cardiac arrhythmia you need a stable ECG. However, ECG signals are highly susceptible to movement. A common device for cardiac RPM is an ECG patch or holter, which can continuously capture ECG signals throughout 24hour periods. In a patient who is active there will be many periods of poor data quality. This is not necessarily prohibitive, as long as the technology is able to interpret enough quality signals to make a proper diagnosis.
3. Ambient Exposure
Of the five most common human vitals (i.e. heart rate, respiratory rate, temperature, blood pressure, Sp02), temperature and Sp02 is most affected by ambient exposure. Temperature monitors can be affected by the sensor’s exposure to ambient temperature. Sp02 sensors can be affected by a strong light source such as outdoors in sunlight.
An effective approach to monitoring for infections is to have patients wear a continuous temperature monitor in order to capture trends over time. Instead of relying on patients to manually take temperature a couple of times per day, which can be unreliable, patients wear a continuous temperature monitor to automatically capture data 24 hours at-a-time. However, depending on the patient’s exposure to ambient temperatures, the reading can vary artificially.
To guard against this variability, using continuous temperature monitors that are considered an FDA ‘clinical’ thermometer, as opposed to an algorithm-calculated body temperature patch, can greatly increase the effectiveness. Furthermore, having a corresponding algorithm that filters out artificial variability then provides an effective method for continuously monitoring patient temperature remotely.
Similarly, a continuous Sp02 sensor will likely capture some level of poor data quality throughout the day, but also having an algorithm that filters the data can significantly improve quality.
Conclusion
With RPM, it’s not just about more data, but enough volume of high quality data to be able to significantly improve the quality of care. Most RPM technologies today can provide a much higher level of quality data over a continuous period compared to existing methods when used properly. The important thing is to understand the ambulatory situations that your patients will encounter, and match that with the appropriate technologies and protocols.
About Jiang Li
Jiang Li is the founder, and CEO of VivaLNK, a provider of connected healthcare solutions for in-hospital, ambulatory, and remote patient monitoring. The company’s portfolio includes wearable medical sensors and an IoHT platform designed to continuously monitor patient vitals and biometrics in realtime or for retrospective analysis.
Prior to joining VivaLNK, he was responsible for new product and technology development as the VP of engineering in Kovio and Thinfilm Electronics, leading printed electronics companies. Prior to that, he worked at AMD and the joint venture between AMD/Fujitsu, Spansion. As the VP of product engineering in Spansion, Jiang managed the major new product launches in Spansion. Jiang holds a Ph.D. degree from the University of Wisconsin-Madison and a bachelor’s degree from Zhejiang University in China.
