How AI-driven remote patient monitoring improves health

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Disease and illness disproportionately affect vulnerable people. The world’s population continues to age. Therefore, many people depend on care outside traditional healthcare settings.

A growing body of evidence suggests that remote patient monitoring (RPM) in particular can improve outcomes for sicker patients. It does so by ensuring consistent contact between a care provider and patient, which can lead to earlier medical intervention.

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You can choose from a list of the best medical alert systems to help you get medical attention and help before it is too late. Vulnerable patients disproportionately lack access to affordable healthcare. For instance, people without health insurance may never receive care due to cost.

Even those that do have health insurance often find the out-of-pocket costs associated with healthcare prohibitive. Ultimately, this leads to medical debt and reduced well-being.

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Table of Contents

Using AI-driven remote healthcare monitoring

Remote patient monitoring (RPM) is a type of telehealth that involves sensors and monitors transmitting information about a patient. That way, clinicians or other care providers get to know their welfare without requiring the patient to visit a medical clinic. There is no doubt that RPM has the potential to improve the lives of people who cannot afford traditional healthcare.

Through RPM, clinicians have access to more information about patients’ well-being, enabling them to provide better care. Most importantly, this happens instantaneously to provide help immediately. This AI-driven remote healthcare monitoring:

  • Benefit patients that live far away from health facilities
  • Works to help clinicians monitor their patients’ health
  • Solves medical service challenges by providing help instantly

How does AI-driven monitoring care work?

AI-driven healthcare monitoring uses sensors that are attached to the body or wearable cameras that track patient activity. These systems monitor symptoms at home instead of making patients go into a healthcare facility every time they feel unwell. These tools allow patients to stay in their own homes without having to travel for hours just for a simple check-up.

This type of healthcare monitoring helps to alleviate chronic conditions among the sick through continuous care back at home. It is at the point of accessing this information where the doctor can decide whether to call the patient for a physical check-up or not.

What are the current use cases?

AI and machine learning improve patient-doctor communication by providing insights into a patient’s condition 24/7. This means patients would no longer have to call their doctor or come into an office right away when a disease symptom arises. Instead, they would have a better sense of how to treat the symptom before it escalates, avoiding costly hospital stays.

These systems use algorithms to analyze data from wearable devices to detect certain body changes. For example, a change in heart rate variability (HRV) correlated with symptoms of heart disease. In that case, a patient wears a device on their chest throughout the day, which uses HRV analysis to measure their condition.

If the device detects changes, it sends an alert to both the patient and their doctor (or caregiver) via text or voice. Additionally, it records the data for analysis and can send automated reports to physicians. This alerts physicians early if their patient is at risk of heart problems or other health concerns.

Why use AI-driven healthcare monitoring?

This approach to healthcare is something, which is fundamental to humanity – looking after one another. It is very rewarding work, and the insight that AI platforms provide has already saved lives. Creating a global network of remote healthcare monitors provide peace of mind for patients with chronic conditions, as well as improves health outcomes through early detection.

An estimated 900 million people worldwide suffer from cardiovascular disease and other chronic diseases – a leading cause of death. For that reason, constant healthcare tracking helps to provide care as soon as the need arises. For that reason, these AI-driven monitoring improves health and peace of mind of vulnerable patients by:

  • Discovering emergencies before happening
  • Providing enhanced outcomes
  • Reducing the amount of time they would spend in hospitals
  • Watching over the lives of vulnerable people in our society

Final thoughts

AI-driven remote healthcare monitoring enhances healthcare and comfort for vulnerable patients in society. These products in healthcare empower patients living with chronic conditions by offering reliable care and support 24/7. That way, it is unlikely that they will go without getting the necessary care around the clock.

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