In this Issue: Improving Treatment of Pain among Veterans
Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools
Cognitive behavioral therapy (CBT) is one of the most effective treatments for chronic low back pain. However, only half of Veterans have access to trained CBT therapists, and program expansion is costly. In partnership with the National Pain Management Program, this randomized study will apply state-of-the-art principles from "reinforcement learning" (a field of artificial intelligence or AI used successfully in robotics and online consumer targeting) to develop an evidence-based, personalized CBT pain management service (AI-CBT) that automatically adapts to each Veteran's unique and changing needs. AI-CBT will use feedback from patients about their progress in pain-related functioning measured daily via pedometer step-counts to automatically personalize the intensity and type of patient support, thereby ensuring that scarce therapist resources are used as efficiently as possible and potentially allowing programs with fixed budgets to serve many more Veterans.
Investigators are recruiting 278 Veterans with chronic low back pain from the VA Connecticut Healthcare System and the VA Ann Arbor Healthcare System. Patients then will be randomized to standard 10 sessions of telephone CBT versus AI-CBT. All patients will begin with weekly hour-long telephone counseling, but for Veterans in the AI-CBT group, those who demonstrate a significant treatment response will be stepped down through less resource-intensive alternatives to hour-long contacts, including 15-minute contacts with a therapist, and CBT clinician feedback provided via interactive voice response calls (IVR). The AI engine will learn what works best in terms of patients' personally-tailored treatment plan based on daily feedback via IVR about patients' pedometer-measured step counts, as well as their CBT skill practice and physical functioning. Outcomes will be measured post-recruitment, and will include pain-related interference, treatment satisfaction, and treatment dropout.
Results are expected to show that by scaling back the intensity of contact that is not resulting in marginal gains in pain control, the AI-CBT approach will be significantly less costly in terms of therapy time - and also will result in greater patient engagement and satisfaction.
Principal Investigator: John Piette, PhD, is part of HSR&D's Center for Clinical Management Research (CCMR) in Ann Arbor, MI, and is Director of the Center for Managing Chronic Disease (CMCD) at the University of Michigan.
Piette J, Krein S, Striplin D, et al. Patient-centered pain care using artificial intelligence and mobile health tools: Protocol for a randomized study funded by the U.S. Department of Veterans Affairs Health Services Research and Development Program. JMIR Research Protocols. April 7, 2016;5(2):e53.