Chronic musculoskeletal pain (MSP) is an enormous problem, affecting more than 100 million Americans (many from disadvantaged groups) and costing upwards of $160 billion. Current pharmaco-therapeutic strategies convey a mix of benefits and hazards. In usual practice, clinicians resort to opioid analgesics, often reluctantly, when other drugs are seemingly ineffective or contraindicated. Finding an effective regimen is frequently a matter of trial and error. This approach may work but is subject to bias. A treatment that appears effective (or ineffective) over the short term may only seem so because of random fluctuation in the patient's underlying condition. To discover the true effect and thus optimize individual treatment, a more scientific approach is needed. N-of-1 trials are randomized controlled crossover trials conducted in a single patient. By crossing a patient back and forth between two treatments several times, clinicians can identify the more effective approach for that individual patient with greater precision than can be achieved in ordinary practice. By generating individual treatment effects, n-of-1 trials pose a challenge to "evidence-based trial and error," the reigning clinical paradigm for treatment of chronic, symptomatic conditions. N-of-1 trials are an intuitively appealing and demonstrably successful approach but have failed to gain much traction, largely due to lack of infrastructure. Mobile devices can change that. This proposal weds mobile technology with personalized health care to address the clinical problem of determining what works for an individual patient. Our goal is to provide tools for identifying individual treatment effects to patients and their clinicians, and to evaluate this approach in terms of patient outcomes and costs to the health care system.
The specific aims of this application are: 1) to develop and refine a mobile web application ("the Trialist") to conduct n-of 1 trials among vulnerable patients with chronic musculoskeletal pain;and 2) to assess in a randomized controlled trial (RCT) the effects of participating in a mobile n-of-1 trial (versus usul care) on clinical outcomes;participatory decision making;satisfaction;adherence;and health care costs. Building on software architecture already developed by Open mHealth.org, the research team will develop, refine, and test the Trialist software over the first 18 months of the project. Then 296 patients with chronic musculoskeletal pain will be randomized to using Trialist to conduct an n-of-1 trial or to usual care. The main hypothesis is that patients assigned to the Trialist will experience better long term outcomes (particularly pain interference at 6 months) compared with those assigned to usual care. Achieving these aims will set the stage for broader uptake of mHealth n-of-1 trials in chronic pain and facilitate use of mHealth n-of-1 trials in designing chronic health care management. !
Chronic musculoskeletal pain is an enormous problem, and treatments are often prescribed in a trial and error fashion. This project seeks to develop a mobile phone application (app) that allows patients and their health care providers to run rigorous, personalized experiments (n-of-1 trials) comparing two different pain treatments. Once the app is developed, the investigators will enroll 296 patients in a randomized study that looks at long term pain outcomes among patients assigned to undergo an n-of-1 trial using the app versus usual care. The project enlists mobile technology to help patients engage actively and collaboratively with their clinicians to identify the pain treatment that works best for them.
|Henry, Stephen G; Chen, Meng; Matthias, Marianne S et al. (2016) Development of the Chronic Pain Coding System (CPCS) for Characterizing Patient-Clinician Discussions About Chronic Pain and Opioids. Pain Med 17:1892-1905|
|Barr, Colin; Marois, Maria; Sim, Ida et al. (2015) The PREEMPT study - evaluating smartphone-assisted n-of-1 trials in patients with chronic pain: study protocol for a randomized controlled trial. Trials 16:67|
|Duan, Naihua; Kravitz, Richard L; Schmid, Christopher H (2013) Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research. J Clin Epidemiol 66:S21-8|
|Chen, Connie; Haddad, David; Selsky, Joshua et al. (2012) Making sense of mobile health data: an open architecture to improve individual- and population-level health. J Med Internet Res 14:e112|