Addressing the top challenges health systems face with first-generation RPM solutions
Understand the top challenges systems face in addressing remote care needs and how next-generation tools advance patient care and increase clinical staff efficiency.
Addressing the top challenges associated with first-generation Remote Patient Monitoring
As the Remote Patient Monitoring (RPM) industry matures, it’s essential to reflect on the challenges hospitals have faced with their first-generation systems. Initially the solution to hospital-at-home care needs during COVID, healthcare providers have the opportunity to look at home-based services as a strategic lever for their transition to value-based care. Ensuring their RPM system can support their clinical teams and scale to meet growth needs is critical.
The earliest remote patient monitoring (RPM) platforms allowed health care systems to open the door to remote monitoring as a new model for health care, but they also had very distinct limitations. At its basic level, RPM services provide detailed, routine monitoring for a wide range of patient health metrics - from temperature and heart rate to respiratory rates, movement data, oxygen levels, and more.
The space has evolved quickly in the last few years, with the clear winners addressing the following shortcomings.
1. Providing a sea of data but only a pond of insights.
While first-generation RPM systems were adept at gathering biometric data, they fell short of managing it. To move the dial, health systems need a way to seamlessly analyze massive amounts of data in real time to ensure the data is actionable for clinicians and patients.
2. Straining existing clinical resources
In today’s strained health care climate – where staff is already stretched thin – many health care systems struggle to allocate the correct number of clinical staff to monitor their RPM platforms. Systems that draw on machine learning and a continuous improvement methodology require far less oversight from staff to run effectively.
3. Producing too many false alerts
Roughly 80% of the alerts issued by the earliest RPM systems did not result in a necessary change to patient care, causing undue strain on stretched clinical resources. Put another way, when clinicians followed up with a patient after one of their remote biometric readings was flagged, eight out of ten times, the care providers deemed the patient did not need a change in care.
Systems that can help cut down on false or insignificant alerts will win in the market. We need processes that evaluate patients’ status with an “intelligent triage” survey system. Internalized, AI-powered, smart patient screening tools that ask a patient with a high blood pressure reading if they’ve recently been physically active will help cut down on false alerts. These extra tools mean clinicians are better equipped to screen and identify patients who genuinely need a clinician outreach call or other care modification.
Health care systems using intelligent triage are seeing a 50% reduction in the number of RPM alerts that do not require a change in care. In turn, they’re netting cost and time savings because their systems are running much more efficiently.
4. Limited ability to scale
Systems looking to upgrade their RPM systems are looking for platforms designed with scalability. Hospitals should fully understand clinical operations needs when deploying a new system. The system should allow for growth and staff efficiency by improving clinician-to-patient ratios over time.
5. Lacking continuous improvement
Many early-generation RPM systems viewed their product installation as their final step; in reality, installation is just the beginning. Next-generation RPM companies meet with their clients frequently to review their data and outcomes related to intelligent triage, alerts, recommendations, and clinical insights. Next-generation RPM organizations are working with partner healthcare systems to ensure that their platforms and protocols are as efficient as they can be.
6. Reliance on active patient participation
Many of the earliest RPM systems relied on active patient participation. For example, patients needed to observe their blood pressure or pulse oximeter readings and then enter those values into a self-reported platform. Some others required daily electronic patient surveys. But these approaches can leave a window for human error in data observation and data entry. They also can lead to patient fatigue and – potentially – cause some patients to withdraw from RPM monitoring altogether.
Next-generation platforms, in contrast, do not require self-monitoring or data entry by patients, thereby eliminating the human error potential inherent in manual data collection.
Their patients can wear a non-intrusive biometric patch that automatically reads and submits their data up to 35 days at a time. Because these systems are more straightforward for participants to use, patients are more apt to remain on RPM platforms – and health care systems can feel more confident in the accuracy of the data they’re receiving.
7. Restricting patient monitoring to homegrown devices
Early-stage RPM companies focused heavily on delivering systems linked solely to the devices they produced, causing providers and patients to learn custom hardware that may not always be best-in-class. As new monitoring devices hit the market at record speed, providers need to be in a position to act quickly vs. hindered by the restrictions of their RPM vendor. Health systems should look for device-agnostic RPM solutions to ensure their monitoring services can easily leverage innovations in the device field.
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