How AI Can Boost Care Via Remote Patient Monitoring

Remote Patient Monitoring
Remote Patient Monitoring
Remote Patient Monitoring

There are a lot of interferences to be drawn once we close the pandemic chapter. But one thing is already evident – our healthcare system is ripe for disruption. The COVID-19 pandemic has wreaked havoc on our world, but it has also accelerated the adoption of telehealth as a safe alternative to physical appointments. And one area of telehealth that has gained a foothold in the past two years is remote patient monitoring.

Let’s see what remote patient monitoring is and how artificial intelligence saves the day once again.

Basics of Remote Patient Monitoring

Remote patient monitoring (RPM) is a growing field in the healthcare industry that uses technology to collect patient data outside of the traditional doctor’s office or hospital setting. RPM can be used to collect a variety of patient data, including vital signs, activity levels, and more.

According to Fortune Business Insights, the global remote patient monitoring devices market is projected to hit over $101 billion in 2028. The growing prevalence of chronic diseases such as diabetes, cardiovascular diseases, and others forge ahead the market and contribute to the growing adoption of RPM software.

Benefits of remote patient monitoring

Remote patient monitoring is an effective way to monitor a person or group of people who are not able to be monitored in person. In some cases, remote monitoring can be used to track a person’s vital signs, such as blood pressure or pulse rate. Remote patient monitoring can also be used to monitor patients who are at risk for hypothermia or other medical conditions that require constant attention.

Cost savings

The cost-saving potential of RPM solutions is immense. Thus, 69% of healthcare professionals ranked RPM the #1 reducer of overall costs.

Remote patient monitoring allows patients to get professional diagnostics without having to spend time and money traveling to the hospital or clinic where they are being treated. Moreover, remote treatments translate into:

  • Optimized time spent with patients (no intake of routine vitals and questions since the data is already available)
  • Improved communication thanks to the increased accessibility of RPM solutions.

Increased patient safety

During the pandemic, hospitals became the ground zero for spreading contagious diseases. Therefore, online appointments emerged as one of the safest options to get professional advice. With remote patient monitoring, doctors and nurses can monitor their patients from home, which prevents individuals from catching something in hospitals.

Quality of care

Remote patient monitoring can also help improve the quality of care, as it allows nurses and doctors to monitor a patient’s vitals without having to visit them in person. Having access to this information can also allow patients with chronic conditions to receive better treatment as they can be monitored on a more frequent basis.

Better patient outcomes

Since doctors and nurses can monitor data 24/7, this increases the odds of better adherence to treatment. Patients can also live more autonomously and have increased involvement in their treatment.

Improved healthcare accessibility

Finally, remote patient monitoring reduces inequalities associated with traditional healthcare. Online monitoring solutions also enable remote consultations and follow-ups for people living in rural areas.

How Does RPM work?

There are many RPM systems on the market, and they come in a variety of shapes and sizes. Some RPM systems are standalone devices, while others are integrated into existing electronic health records (EHRs). But what all RPM systems have in common is the ability to gather patient-generated health data and then send that data to healthcare providers for monitoring.

RPM solutions offer homecare telehealth capabilities that can be embedded in:

  • Stand-alone medical measuring devices (patches, blood glucose concentration, pulse oximeter, and others)
  • Implantable devices (e.g., Cardiac Implantable Electronic Devices (CIEDs))
  • Digital platforms to enable continuous monitoring and support for patients 24/7, including telehealth.

Usually, RPM solutions connect to the cloud, enabling compliant data sharing and seamless access to patient data.

Here’s a step-by-step flow of delivering a patient’s vitals from RPM software to the healthcare provider:

  • A patient registers to the system so that the system can authenticate a specific device.
  • The system initializes monitoring and data gathering via a medical device.
  • The device gathers and transmits data to an RPM server or the cloud.
  • Algorithms analyze patients’ data, and the system generates reports and visualizations.
  • The doctor accesses the visualization and follows corresponding actions, whether it’s adjusting the course of treatment, changing the treatment scheme, or any other follow-up.

How artificial intelligence helps telehealth

The significant impact of artificial intelligence on healthcare has resulted in the AI market growth. By 2030, artificial intelligence in the healthcare market is estimated to hit over $187 billion.

The AI potential has also manifested itself in telehealth and remote monitoring. Thus, AI-driven technologies have transformed RPM solutions from a simple data aggregator into an advanced data analytics platform. Paired with analytics, RPM platforms allow physicians to integrate patient data into clinical workflows, generate accurate predictions, and flag individual patients at risk.

Therefore, artificial intelligence enables proactive care and more personalized data-driven treatment approaches. Now, let’s see where exactly machine intelligence fits.

Diagnosis

According to the L.A. County Department of Health Services, telehealth monitoring for diabetic retinopathy minimized patient visits by approximately 14,000 visits. If we add artificial intelligence at the screening stage, the number of visits and patient wait times are expected to drop even further.

Thus, machine learning classification algorithms can analyze patient data from RPM solutions and flag patients at risk of developing certain conditions. Patients can also upload medical images to a secure server and AI-based image recognition can spot anomalies without professional assistance.

Treatment plans

Artificial intelligence has also proved helpful in precision medicine. The AI-fuelled system compares patients’ medical images with a database of high-quality treatment plans created by certified experts. It then combines these insights with personal health data to generate a personalized treatment plan.

According to IBM, expert systems can also group patients by similar responses to treatment to produce an optimal treatment regimen.

Patient engagement

Engaging patients in medication adherence or timely appointments is another responsibility of AI in remote patient monitoring. By analyzing software data, AI can be used to generate action items, including reminders for appointments, follow-up actions, and others. Fueled by AI and NLP, chatbots are indispensable for automated communication and better access to care.

Chronic disease management

Complexities of chronic disease management have always been uncharted territory for the healthcare industry. AI, however, can prevent chronic diseases such as diabetes, cancer, and kidney disease by identifying early signs of those conditions in the patient’s data. Thus, algorithms can identify CKD patients by stage and the presence of acute kidney injury.

AI and Remote patient monitoring: a match made in heaven

Remote patient monitoring is a much-needed iteration of the traditional healthcare system that makes professional diagnosis and treatment accessible to all. Artificial intelligence steps into RPM software to amplify its data processing capabilities and turn it into a viable tool that complements offline treatments. Artificial intelligence supports efficiency in disease diagnosis, personalized treatments, and disease prevention to improve patient outcomes and make treatment proactive.

Featured Image Credit: Provided by the Author; Thank you!

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