By Devin Partida, Editor-in-Chief, ReHack.com
Twitter: @rehackmagazine
Artificial intelligence (AI) is the key to optimizing remote patient monitoring (RPM) and gaining access to next-gen care for patients. Integrating AI into RPM care strategies can have incredible benefits for both patients and care providers. Ultimately, it can result in a better experience for everyone and more effective treatment plans. While RPM is a great tool on its own, AI is the secret ingredient to make RPM a highly effective and even revolutionary health care technology.
Personalized, Adaptive Care With AI RPM
RPM may have surged in popularity due to the COVID-19 pandemic, but it has become a mainstream care technology for the long run. In theory, it is the perfect tool to meet today’s health challenges without compromising patient care. Unfortunately, RPM does rely on patients to take a certain level of initiative themselves, which can lead to poor patient adherence. In fact, keeping patients engaged is one of the key challenges of telehealth and remote medicine.
Additionally, RPM tools are not one-size-fits-all and neither is remote health care. RPM technology has significant potential to improve the patient experience, but it can fall short of this potential when patients struggle to stick to routines or don’t have their unique needs met. AI can help health care providers resolve this and take RPM to the next level. AI opens the door to personalized, adaptive care through data analysis and pattern recognition. For instance, a virtual AI health assistant on a patient’s smart watch could autonomously remind them to take medications or do physical fitness exercises at certain times.
The AI can adjust these times based on the patient’s behavior. Maybe the AI recognizes that the patient is getting up in the morning later than anticipated or eating at a certain time every day. Reminders can be personalized to the unique patient’s lifestyle and needs, intuitively improving patient adherence. This is especially important when it comes to treating chronic conditions, which relies on consistent patient adherence.
AI can even save lives. If a patient is wearing their RPM device, an AI biosigns monitor could improve the detection of key medical emergency indicators. In the event of an emergency, the AI could automatically contact emergency personnel.
For patients who are reluctant to try RPM and AI tools, accreditation can be helpful for boosting trust and confidence. Plus, RPM accreditation networks can often help doctors find innovative RPM solutions for their patients.
Additionally, doctors can discuss the many medical and logistical benefits of AI and RPM technology, for both the patient and the care provider.
Applying AI RPM to Improve Clinical Efficiency
Combining AI and RPM isn’t just good for patients. It can also be extremely helpful for health care providers. For instance, an intelligent AI health assistant and RPM device could replace at-home nursing for many patients. This reduces strain on understaffed nursing teams while also reducing care costs for the patient.
One of the great benefits of RPM technology is increased access to health data. With AI boosting patient adherence, doctors can gain an invaluable wealth of data that can transform care regimens. AI can help with this, too. AI data analysis can extract key insights and patterns from patient data. Doctors can use this information to improve care quality in an efficient and effective manner.
Additionally, alongside pattern recognition, AI can also polish RPM data. RPM devices often over-correct by reporting excessive false positives for symptoms or potential conditions. AI can comb through RPM data with precision and intelligence, reducing these false positives.
Another incredible benefit of AI medical data analysis with RPM is predictive care. AI excels at making forecasts based on pattern recognition. Doctors can leverage this with the RPM data collected using their patients’ devices. The AI analyzes the data provided on symptoms and patient behaviors and uses known and recognized patterns to predict potential symptoms and conditions that could emerge down the road. This gives doctors an opportunity to address those possible concerns with patients before they become a problem.
Advancing Remote Care
All of the above factors lead to a reduced likelihood of hospitalization for the patient. Access to efficient data analysis allows doctors to provide proactive, predictive care that catches emerging conditions before they can become emergencies. Increased patient adherence and intelligent monitoring ensure more effective care regimens. Ultimately, adopting AI alongside RPM can save lives and improve quality of life for patients while they receive the best care possible.