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Using AI and remote patient monitoring technology in pain management enables ongoing real-time monitoring, facilitating personalized adjustments to therapy.
The American Society of Health-System Pharmacists (ASHP) hosted its 2024 Midyear Clinical Meeting and Exhibition over 6 days in New Orleans. Several sessions at the meeting focused on pain management, including one led by Tanya J. Uritsky, PharmD, BCPP, and faculty member Jessica Geiger, PharmD, MS, BCPS.
Together, Dr. Uritsky and Dr. Geiger moderated a session on how patients present with pain in different clinical settings. They explored how language influences stigma and bias among this patient population and analyzed best practices for pain management in both inpatient and outpatient settings.
In a separate study not presented at the meeting, Prachi Patel, MD, and colleagues examined the use of remote patient monitoring (RPM) enhanced with AI for pain management.
“RPM represents a paradigm shift from reactive to proactive healthcare,” Dr. Patel and colleagues wrote in the Journal of Pain Research. “This shift significantly enhances the potential for early intervention, personalized treatment strategies, and ultimately, improved patient outcomes.”
Leveraging AI-Assisted RPM for Real-Time Adjustments
NXTSTIM EcoAI shows promise for monitoring pain as part of RPM. Using biomarkers and physiological signals, it can detect changes in pain pathways. More specifically, it can monitor cytokine levels, neurotransmitter fluctuations, and nerve conduction velocities in real-time. It can even recognize if a patient is developing a tolerance to neuromodulation therapies.
“By enabling continuous, real-time monitoring of physiological parameters and biomarkers, RPM facilitates timely interventions and tailored treatment strategies, significantly improving patient outcomes and optimizing healthcare resource utilization,” the researchers wrote.
These advancements in RPM are especially promising for monitoring the efficacy of neuromodulation therapies that work by disrupting pain pathways, such as spinal cord stimulation (SCS), peripheral nerve stimulation (PNS), transcutaneous electrical nerve stimulation (TENS), and electromyographic stimulation (EMS). In addition to monitoring biomarkers and other physiological signals, AI can also detect lead migration, battery depletion, and therapy adjustments to improve pain management outcomes.
When AI recognizes waning efficacy for neuromodulation therapy, it can provide recommendations for pulse width, frequency, or amplitude to help manage a patient’s pain more proactively. However, neuromodulation therapy isn’t the only way AI has the potential to help with pain management. There are also AI-enhanced patient-controlled analgesia (AI-PCA) systems that are changing the way healthcare providers manage pain.
AI-PCA works similarly to neuromodulation therapy enhanced by AI. It assesses “pain-related biomarkers and patient inputs in real-time, enabling precise dose adjustments that minimize adverse effects while optimizing pain relief,” Dr. Patel and colleagues wrote. “And it does all of this while simultaneously reducing the risk for overmedication and the adverse effects associated with that.
Adopting AI-Enhanced RPM for Pain Management
RPM and AI are transforming the way clinicians manage patients’ pain. “The adoption of RPM and AI represents a paradigm shift in chronic disease management,” Dr. Patel and colleagues noted. “By enabling continuous, real-time monitoring and facilitating personalized, dynamic adjustments to therapy, these technologies enhance patient outcomes while reducing the strain on healthcare resources.”
However, many clinicians have concerns about data security, especially since this technology continuously collects data. They may also lack an understanding of AI algorithms, so training and transparency are required to ensure a smooth transition to using these tools.
“Addressing these challenges will be key to maximizing the benefits of RPM and ensuring that it contributes meaningfully to improved patient outcomes and more efficient healthcare delivery,” the researchers wrote.
