Remote patient monitoring has revolutionized the world by becoming a crucial treatment process for chronic diseases, including Parkison’s disease, cardiovascular disorders, diabetes, and numerous others. Innovative advancements in remote patient monitoring have shifted patient monitoring from regular in-person visits in the hospital to continuous virtual monitoring through RPM services, allowing medical professionals not only to diagnose but also to keep a check on patients and monitor their conditions remotely. This feature also enables them to warn patients or the hospital before any potential emergencies arise, especially in the case of patients with chronic neurological conditions.
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Remote Patient Monitoring and Artificial Intelligence
A remote patient monitoring system typically consists of a device that gathers information from specialized sensors and transmits them to a hospital or medical professional for evaluation. Thus, telehealth and remote patient monitoring has effectively eliminated the barriers and limitations surrounding traditional clinical practices by metamorphosing the medical world into a well-connected global village. However, a fundamental problem in this RPM structure was an underdeveloped communication infrastructure that needed more capacity to transmit stored and collected data. This weakness in the RPM structure has been aptly addressed by advancements in artificial intelligence, whose algorithms have provided seamless modes of information transmission.
Since the future of remote patient monitoring and telehealth rests in a world that expects instant, high-quality, and seamless access to personalized healthcare propositions, artificial intelligence has prompted the development of innovative devices that can capture vital signs, background data, and well-being metrics in a clinical setting to combat this increasing demand for personalized medicine. These advancements pave the way for well-informed clinical decisions based on accurate longitudinal metrics.
However, none of these innovations are happening haphazardly or in isolation, and some of the world’s established companies – including Apple – are engaging people to undertake remote patient monitoring even when they are not necessarily patients. This is mostly done through smart watches, along with an abundance of health apps that are rising periodically and altering how individuals interact with healthcare professionals and their health. Several other acknowledged corporations have also launched their FDA-approved wearables, amalgamating consumer-facing tech companies promoting artificial intelligence and healthcare institutions offering remote patient monitoring services. Some of these tech giants include Samsung, Apple, Amazon, and Google – all companies that hold power to metamorphose nationally-scaled consumed habits.
For reference, the Apple Watch has managed to outsell the entire Swiss watch collection numerous years in a row, with the Apple watch boasting an FDA-approved EKG monitor usable for people over the age of 22 and without a prior history of arrhythmia. Other similar artificial intelligence prompted advancements in the field of remote patient monitoring include taking vital signs through a smartwatch for all kinds of patients and non-patients, sensors in clothing, subcutaneous and epidermal sensors, and breathalyzer devices to detect standard vital signs, including blood pressure and Sp02. FDA has also approved an implantable sensor that can help with continuous glucose monitoring for people with diabetes that can passively collect blood glucose levels 24/7.
How Artificial Intelligence is Promoting Better Remote Patient Monitoring
Clinical artificial intelligence with advanced algorithms holds the potential to yield successful remote patient monitoring as they can monitor comprehensive data sets like socioeconomic, clinical, and experimental data for a more holistic clinical view of a patient. These analyses can then be used as a basis for stratification to determine not just the risk levels but also to attain a deeper understanding of which patients and medical conditions respond better to remote patient monitoring.
AI can then take the reins and make recommendations and suggestions on how and when to engage particular patients. AI-stimulated sensors and RPM devices can begin to continuously collect patient data and patient-reported data, including pain levels and symptoms. A suitable harmony between AI and RPM can play the role of additional data sources to personalize and enhance patient experiences. AI systems can also continue to stratify patients in collaboration with remote patient monitoring software data for better patient stratification, making the collected data more actionable to perform timely clinical interventions. Thus, the beneficial collaboration between remote patient monitoring and artificial intelligence holds the potential to develop a self-sustaining cycle where innovative tools can continue to become more accurate and reliable with suitable usage.
Benefits of the Collaboration Between Remote Patient Monitoring and Artificial Intelligence
Although RPM and AI offer numerous benefits to the healthcare sector on a standalone basis, it goes without saying that their amalgamated efforts can capitalize on that value. Some of the pivotal benefits of this collaboration are as follows:
Enhanced Patient Outcomes
Increased data is always helpful when it comes to making crucial clinical decisions that may involve life and death. Thus, the continuous data collection and analysis by AI-powered remote patient monitoring devices ensure that healthcare providers get a comprehensive account of a patient’s condition, enabling them to make critical clinical decisions based on them and prescribe the best possible treatment options to their patients. Apart from well-informed treatment decisions, healthcare providers can also use comprehensive data to monitor their patients closely and develop their clinical trajectory better. This allows them to make better and more timely clinical interventions and prevent ED utilization and readmissions.
Personalized Healthcare
Effective collaboration between RPM and AI offers the most holistic patient view any technology in the healthcare industry can sketch. Numerous data points help healthcare providers create patient-centered solutions, allowing them to understand individuals not just as patients but as individuals with distinct socioeconomic, clinical, and experiential factors affecting their health. Thus, this collaborative technology can empower healthcare to fit the needs and preferences of individual patients without requiring manpower and manual efforts from clinical staff. Such a high degree of personalization is likely to establish itself as a decisive factor in patient and healthcare provider success.
Reduced Healthcare Costs and Augmented Revenue
The implementation of AT-powered remote patient monitoring is most common in the chronic disease population since they are the leading cause of disability and death in the United States. They are also the leading contributor to the country’s $3.8 trillion annual healthcare cost. Therefore, AI-powered healthcare can be leveraged to lower ED utilization, reduce avoidable readmissions and admissions, optimize healthcare resources, and increase staff efficiency, all of which can be an enormous step to cutting healthcare costs. Additionally, healthcare codes are being expanded to better support healthcare professionals by using AI-powered remote patient monitoring for reimbursement opportunities.
If you are looking for top-notch remote patient monitoring services, SmartClinix is the place for you. American board-certified and fellowship-trained professionals at SmartClinix offer high-quality remote patient monitoring services in USA right at your doorstep!
