FEATURED MEDICAL EDUCATION TOPIC: Artificial Intelligence in Pain Management

What is the problem?

Chronic pain is one of the most challenging conditions physicians manage, and standard treatment pathways often fall short. Clinicians must piece together information from the EHR, imaging, patient-reported outcomes, pharmacy records, and wearables in a short visit. As a result, chart review crowds out clinical thinking, and treatment becomes trial and error. High-risk patients are recognized too late, and paperwork keeps growing. The outcome is uncertainty, uneven care, and added strain on physicians.

AI is already part of pain practice through EHR risk scores, imaging triage, ambient documentation, and payer tools, often without physician input. Physicians remain responsible for the decisions these tools shape. They need to know whether a tool was tested on patients like theirs, recognize biased or inaccurate results, and explain AI-informed recommendations to patients. Without this knowledge, they may trust flawed results or miss tools that could improve care.

Early studies show promise in pain assessment, risk prediction, opioid stewardship, and decision support. Most of this research, however, is retrospective and comes from single institutions. Bias, privacy, transparency, and regulatory concerns still limit adoption. Practical, evidence-based education helps physicians close this gap.

Proposed Learning Objectives

Upon completion of this activity, participants will be able to:

• Differentiate among artificial intelligence, machine learning, deep learning, natural language processing, and generative AI, and identify appropriate uses of each in pain medicine. 
• Apply current AI tools to clinical pain scenarios, including pain assessment, postoperative risk prediction, opioid stewardship, and interventional planning. 
• Evaluate an AI model or study for accuracy, external validation, generalizability, and risk of bias. 
• Integrate AI-supported recommendations into patient care with appropriate physician oversight, privacy safeguards, and shared decision-making.

If your medical staff would benefit from an update on AI in pain management, contact our office to book a speaker at 714-505-4777 or info@speakersnetwork.com.

How do we know this is a problem?

Hagedorn JM, George TK, Aiyer R, et al. Artificial intelligence and pain medicine: an introduction. J Pain Res. 2024;17:509–518. 

Abd-Elsayed A, Robinson CL, Marshall Z, et al. Applications of artificial intelligence in pain medicine. Curr Pain Headache Rep. 2024;28(4):229–238. 

Meier TA, Refahi MS, Hearne G, et al. The role and applications of artificial intelligence in the treatment of chronic pain. Curr Pain Headache Rep. 2024;28(8):769–784. 

Zhang M, Zhu L, Lin SY, et al. Using artificial intelligence to improve pain assessment and pain management: a scoping review. J Am Med Inform Assoc. 2023;30(3):570–587. 

Massey C, Latif U, Deer TR, et al. Guidelines from the American Society of Pain and Neuroscience for using artificial intelligence in interventional spine and nerve treatment. J Pain Res. 2025;18:4211–4235.