When RPM meets RPA

As medical technology continues to develop, it is becoming possible to collect increasing amounts of remotely generated patient data. This has the potential to greatly improve patient outcomes, but it also poses a challenge to efficiency by potentially requiring more resources to monitor and react to the incoming remote care data.

Is there a way to win both worlds? Better outcomes without increasing, or even decreasing operational costs?

The staff hours needed to monitor the incoming data can present a significant barrier to wide rollout of Remote Patient Monitoring (RPM). With most healthcare staff already overburdened, giving this task to an existing care team may not be feasible. Hiring additional staff members to do the monitoring is not cost effective and may be difficult due to labor shortages in many markets. At the same time, the vast majority of RPM tasks are repetitive and follow predefined guidelines, only rarely is there a need for providers to intervene, and thus, Robotic Process Automation (RPA) can help remove the barriers by automating the simple, repeatable tasks that would otherwise take up much of a healthcare worker’s time.

RPM is traditionally used for integrating tasks between systems. In remote care, we can think about 3 different systems that have to interact – EMR, the patient, and their connected devices. Data must flow from the connected devices into the patient app and from there into the EMR, with existing RPM solutions requiring additional resources to monitor the engagement and the data before it is entered into the EMR, and to determine whether or not an intervention is needed. Imagine if we could automate the majority of these tasks, similarly to how it is done in other settings like in call centers and many other similar operations? This could increase the capacity of a care team, leading to lower costs. With a well-designed RPA system, RPM can be made much more widely available in the future, leading to lower healthcare costs along with better patient outcomes.

How is remote patient monitoring used?

Some version of remote patient monitoring has long been a part of patient care in most fields of medicine. One example is a patient whose blood pressure is high at a clinic visit. The physician may ask the patient to measure their BP twice a day and record the values manually, then bring the written record to their next visit. While this is a manual process, it is RPM. In this version, RPM is also asynchronous, meaning that the data is viewed at a later date rather than as it is being generated.

In a synchronous version of this example, a system might send an alert to a nurse if a patient records a high BP reading. The nurse would call the patient for monitoring. The nurse might ask about symptoms, have the patient take another BP reading while resting, and ask whether the patient has been taking their hypertension meds. If the new reading is high and the patient reports not taking their meds, the nurse could tag the high reading as being due to noncompliance with meds and set a reminder to follow up with the patient. If the new reading is normal, the nurse might conclude that all is well and no further intervention is needed.

Using RPA, a process like this could be automated. The system could send reminders to the patient twice per day, reminding them to measure their BP and upload the data. If a high reading is detected, it would automatically send a survey about symptoms and medication use and could direct the patient to rest for a few minutes and take another reading, and if normal – could let the patient know there is no reason for concern. Most of the menial tasks performed by the nurse could easily be performed through RPA. The system would alert the nurse of the need for patient intervention only when necessary. This saves the cost of the nurse’s time, helping to make remote care more cost-effective and therefore more accessible.

How can we implement robotic process automation in healthcare?

The challenge is to broaden the use of RPA to cover the monitoring of a broader range of patient data, and to interact on a more regular basis with patients. Remote care platforms that are designed for maximum flexibility in which clinical teams can customize treatment plans and care protocols for their patients will be able to reap the greatest benefits of RPA.

An example of how RPA works within a remote patient monitoring platform:

  • The care team creates a flow chart, mimicking its own standard processes in patient care.
  • A product team then recreates the clinical pathway on their remote care platform, with each repeatable part of the process programmed into the system.
  • The new system is tested internally with staff. By acting as test patients, they can see whether it works as desired and make any necessary changes to their protocols.
  • The system is deployed to patients, on an individualized basis or for entire cohorts. Improvements and enhancements are a must as we gain more insight about the engagement of the patient and the clinicians.

Is this AI in healthcare?

RPA is not exactly artificial intelligence (AI), because the system does not make its own decisions. Instead, an RPA system performs the tasks that it was given, in exactly the way that it is given them, and its actions are governed by pre-defined rules. Thus, rather than replacing staff members, RPA helps to use medical resources more efficiently by taking on repetitive tasks, leaving staff members free to focus on higher value, nonrepeatable tasks. The more advanced RPA systems can learn additional repetitive tasks and incorporate them into the RPA/RPM program.

A remote patient monitoring solution using robotic process automation.

The flexibility of the Datos Health platform gives it the power to improve care in any healthcare department. This is manifested in its ability to integrate with any monitoring device and – unlike specialized RPM systems which are optimized for use in specific clinical domains – its ability to be easily customized for use in many different settings, from oncology to primary care. One of the Top 10 hospitals in the world is using Datos Health RPA solutions in over 35 different departments. Each one has created its own remote care program, and they are all integrated within a single EMR, facilitating patient care across departments. We designed Datos Health to be used in virtually any healthcare setting because it would be unwieldy to use a separate RPA system for each department of a hospital.

At Datos Health, we are driven by the potential for RPA to democratize RPM and improve patient care. By decreasing the cost of RPM, it can be made more widely available thus furthering our mission to drive clinical efficiency through automation and improve the quality of life for patients. Our vision is to facilitate the adoption of RPM to the general population, making it a standard part of patient care. We have designed our platform with this goal in mind.