How AI can enhance care through remote patient monitoring

There are a lot of interventions that will be drawn as we close the pandemic chapter. But one thing is clear – our health care system is ripe for disruption. The COVID-19 pandemic has ravaged our world, but it has also accelerated adoption telehealth as a safe alternative to physical appointments. And one area of ​​telehealth that has gained ground 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.

The basics of remote patient monitoring

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

Based on Fortune Business Insightsthe global remote patient monitoring device market is predicted to reach over $101 billion by 2028. The rise of chronic diseases such as diabetes, cardiovascular and other diseases has led 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 that cannot be monitored in person. In some cases, remote monitoring can be used to monitor a person’s vital signs, such as blood pressure or pulse rate. Remote patient monitoring can also be used to monitor patients at risk for hypothermia or other medical conditions that require constant attention.

Cost savings

The cost-saving potential of RPM solutions is enormous. So, 69% healthcare professionals RPM rating is the #1 overall cost reducer.

Remote patient monitoring allows patients to obtain professional diagnoses without having to spend time and money traveling to the hospital or clinic where they are being treated. Furthermore, telemedicine methods translate into:

  • Optimized patient time (don’t get key metrics and common questions because data is already available)
  • Communication is improved by the increased accessibility of RPM solutions.

Increase patient safety

During a pandemic, hospitals become zero points for the spread of infectious diseases. As a result, online appointments emerge as one of the safest options for getting professional advice. With remote patient monitoring, doctors and nurses can monitor their patients from home, which prevents individuals from catching something in the hospital.

Quality of care

Remote patient monitoring can also help improve quality of care, as it allows nurses and doctors to monitor a patient’s biopsies without having to visit them in person. Access to this information can also allow patients with chronic conditions to be better treated because they can be monitored more often.

Better patient outcomes

Since doctors and nurses can monitor data 24/7, this increases the rate of better adherence. Patients can also live more independently and become more involved in their treatment.

Improve access to healthcare

Finally, remote patient monitoring reduces the inequalities associated with traditional healthcare. Online monitoring solutions also enable remote consultation and monitoring 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 stand-alone devices, while others are integrated into existing electronic health records (EHRs). But what all RPM systems have in common is the ability to collect patient-generated health data and then send that data to healthcare providers for monitoring.

RPM solutions provide telehealth capabilities at home that can be integrated into:

  • Standalone medical measuring devices (patches, blood glucose levels, pulse oximeters and others)
  • Implantable devices (e.g., Heart Implant Electronic Devices (CIED))
  • Digital platforms enable 24/7 continuous patient monitoring and support, including telehealth.

Typically, RPM solutions connect to the cloud, allowing for compliance data sharing and seamless access to patient data.

Below is the step-by-step process of delivering vital patient information from RPM software to healthcare provider:

  • A patient enrolls in the system so that the system can authenticate a specific device.
  • The system initiates monitoring and data collection through a medical device.
  • The device collects and transmits data to an RPM server or to the cloud.
  • Algorithms analyze patient data and the system generates reports and visualizations.
  • The doctor accesses the visualization and takes corresponding actions, whether it is adjusting the course of treatment, changing the treatment program or any other monitoring.

How does artificial intelligence help remote health?

The significant impact of artificial intelligence on healthcare has led to the growth of the AI ​​market. By 2030, artificial intelligence in the healthcare market is estimated to surpass 187 billion dollars.

The potential of AI has also shown itself in remote and remote monitoring capabilities. As a result, AI-based technologies have transformed RPM solutions from a simple data aggregator into an advanced data analytics platform. Combined with analytics, the RPM platform allows physicians to integrate patient data into clinical workflows, generate accurate predictions, and flag each patient at risk.

Thus, artificial intelligence enables proactive care and more personalized data-driven treatments. Now, let’s see the exact location of the matching machine intelligence.


Follow LA . County Health Department, remote health monitoring for diabetic retinopathy has reduced patient visits by about 14,000 visits. If we add artificial intelligence to the screening phase, the number of visits and patient waiting time is expected to decrease further.

As a result, 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 that can detect anomalies without expert help.

Treatment plan

Artificial intelligence is also proving useful in precision medicine. The system uses artificial intelligence to compare a patient’s medical images with a database of high-quality treatment plans created by certified professionals. It then combines these insights with personal health data to create a personalized treatment plan.

Based on IBMExpert systems can also group patients according to similar responses to treatment to provide optimal treatment regimens.

Patient participation

Engaging patients with medication adherence or booking appointments in a timely manner is another responsibility of AI in remote patient monitoring. By analyzing software data, AI can be used to create action items, including reminders for appointments, next actions, and others. Powered by AI and NLP, chatbots are indispensable for automated communication and better access to care.

Chronic disease management

The complexity of chronic disease management has always been uncharted territory for the healthcare industry. However, AI can prevent chronic diseases like diabetes, cancer, and kidney disease by identifying early signs of those conditions in patient data. Therefore, the algorithm can determine CKD patients by stage and 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 everyone. Artificial intelligence stepped into the RPM software to amplify its data processing capabilities and make it a viable tool that complements offline treatments. Artificial intelligence helps effectively in disease diagnosis, personalized treatments and disease prevention to improve patient outcomes and enable proactive treatment.

Featured image credits: Provided by the author; Thank you!

Pavel Tansiura

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