Remote patient monitoring has become a key buzzword for the global healthcare industry, particularly for serving patients with chronic ailments.
Remote patient monitoring systems are steadily becoming indispensable components of the treatment procedure for chronic diseases like Parkinson’s, diabetes, heart ailments, and more.
Remote health monitoring systems are doing away with the conventional method where patients were monitored periodically or regularly at hospitals or healthcare centers.
AI (artificial intelligence) is a vital element of remote patient monitoring devices and systems that helps in checking and evaluating the conditions of patients remotely and warning them or the hospital about any potential risks or emergencies.
AI adoption is rapidly increasing throughout the entire healthcare spectrum and RPM (remote patient monitoring) is one of the biggest healthcare applications enabling doctors to track patients with acute/chronic diseases across remote locations, patients who are hospitalized, and elderly people who are in-home care.
What is a patient monitoring system?
This is an AI-driven technological framework that not only classifies physical activity but also tracks chronic diseases and vital signs for emergencies.
There are various types of patient monitoring systems that are using AI-based RPM architecture for transforming healthcare tracking throughout the sector, enabling early detection of any deterioration in the health conditions of patients and also personalizing individual health parameters with federated learning.
These are deployed through patient monitoring devices which are also learning more about the behavioral patterns of patients with techniques like reinforcement learning.
RPM or CMS remote monitoring works through devices that transmit information gathered from sensors linked to patients, hospitals, or specialists.
AI has solved issues relating to the accurate determination of patient conditions and proper data processing in a timely manner as well.
The fast-growing market for remote patient monitoring devices is determined by several variables including the desire to lower costs of healthcare providers and customers alike, overall efficiencies in operations and monitoring along with increasing usage of home-based devices, and more demand for quality healthcare solutions in rural and underserved regions.
The increasing population of elderly citizens and the rapid growth of chronic ailments are other factors influencing growth in this segment.
A report by Global Data called Thematic Research: Remote Patient Monitoring Devices predicts growth in the RPM segment to $760 million in 2030 from $548.9 million in 2020, indicating a CAGR (compound annual growth rate) of 3.3%.
Investments have also increased in the wearable technology space, widening options in terms of cost-cutting, boosting results, and patient empowerment. AI and wearable technologies are bringing an evolution in healthcare via remote patient monitoring (RPM).
Remote patient monitoring (RPM) is steadily enabling care services for patients in case of any emergencies. It is also being implemented for people throughout multiple categories or target groups, including those with chronic disabilities or illnesses, mobility problems, and elderly individuals.
RPM enables better healthcare tracking and services to patients at home itself, while giving them a psychological boost since they are not in hospital settings.
It is also enabling higher comfort and freedom for patients while helping them execute daily tasks in conducive environments while being monitored actively for underlying health issues.
Doctors can also track patient health remotely via automated systems that also generate alerts in case of any issue with the parameters.
The impact of RPM is keenly felt with reports indicating its usefulness in the mainstream healthcare industry like never before.
One such analysis was published in the Journal of the American Medicine Association, which stated how RPM could be lined to 87% lesser hospitalizations along with 77% lower deaths.
It also reduced per-patient costs to the tune of $11,472 in comparison to regular healthcare in the USA.
This says all about the efficacy and effectiveness of remote patient monitoring for those with chronic conditions.
AI can be deployed for remote patient monitoring for chronic ailments via several mechanisms including wearables and frameworks that enable regular readings, early detection of vital signs and deterioration, and more education and support for patients.
AI can enable several benefits in the remote patient monitoring space, enabling more accurate readings and easy visibility for healthcare providers into patient data and conditions between visits and interactions. It helps with preventive healthcare and higher patient adherence alike.
The challenges of AI usage in remote patient monitoring include lack of awareness or support from the patient-end, issues with data collection, data quality, technological integration, and so on.
There are privacy concerns with AI usage for remote patient monitoring, especially since the data is confidential and classified in nature. However, advanced security systems are being leveraged to nip potential privacy issues in the bud.
