The report is a product of the VA/HSR&D Evidence Synthesis Program.
Effectiveness of Models Used to Deliver Multimodal Care for Chronic Musculoskeletal Pain
Chronic musculoskeletal pain is a growing burden on today's Veteran population. Studies of Veterans who served in Iraq and Afghanistan show that musculoskeletal system diseases are the most frequent diagnoses in inpatient and outpatient encounters, even surpassing mental health conditions. Pain is a complex condition involving dynamic interactions between biological, psychological, and social factors unique to each individual. For this reason, pain care needs to be individually tailored, involving multiple care approaches and collaboration between primary and specialty care clinicians. Pain management guidelines, including those for the VA, advocate for multimodal pain care. However, primary care providers (PCPs), who are responsible for the majority of pain management, face many system- and patient-level challenges in providing the recommended multimodal interventions. Therefore, this Evidence Brief sought to:
- Determine what multimodal care delivery models relieve chronic musculoskeletal pain and minimize unintended consequences;
- Define key elements of and the resources required for these models; and
- Identify patients who are most likely to benefit from these models.
Investigators with VA's Evidence-based Synthesis Program Center located in Portland, OR searched multiple data sources (i.e., MEDLINE, CINAHL, Cochrane Database of Systematic Reviews, etc.) for relevant articles through October 2016. After reviewing 901 records identified through this search and via reference lists and hand-searching, they identified 12 articles, including 1 secondary study, that were relevant to their analysis. Overall, most studies referenced in these articles were fair to good quality, with three rated as poor.
Summary of Findings:
Nine multimodal chronic pain care models were identified that had been evaluated in mostly good-quality randomized clinical trials (RCTs) comprised of 3,816 individuals primarily from five U.S. states. Of these nine models, five coupling decision support — most commonly algorithm-guided treatment and/or stepped care — with proactive ongoing treatment monitoring have the best evidence from good-quality RCTs of providing clinically relevant improvement in rates of pain intensity and pain-related function over 9 to 12 months (NNT range, 4.1 to 12.70), as well as variable improvement in other important core outcomes. The top five models include
- Evaluation of Stepped CAre for Chronic Pain (ESCAPE): Stepped care with analgesics, cognitive behavioral therapy, and nurse care manager.
- Study of Effectiveness of a Collaborative Approach to Pain (SEACAP): Collaborative care delivered by a psychologist care manager.
- STarT Back Screening Tool: Prognostic screening (9-item inventory) with risk-matched pathways.
- Stepped Care for Affective Disorders and Musculoskeletal Pain (SCAMP): Stepped care with antidepressants and self-management delivered by a nurse care manager.
- Stepped Care to Optimize Pain Care Effectiveness (SCOPE): Telecare collaborative management and algorithm-guided analgesic optimization.
Findings from ESCAPE, SEACAP, SCAMP, and SCOPE have the highest applicability to Veterans because they were studied in VA settings. However, as each of the top five models is only supported by a single study with imprecise findings, current evidence leaves sufficient doubt about their findings to recommend further research.
Compared to VA-based models, in the remaining models conducted in other non-VA settings, decision support components were less common, and case management teams were more diverse, representing: occupational therapy, social work, physical therapy, physiatry, pharmacy, physiotherapy, kinesiology, and dietary needs. Mental health treatment was more often a required component, and patient self-management support was more often passive in nature.
Given their consistent evidence from good-quality trials of providing clinically relevant improvement in pain and function, investigators encourage healthcare systems to consider multi-site implementation of any of the five models that couple decision-support with proactive ongoing treatment monitoring. Broader implementation should be accompanied by a plan for further evidence development to evaluate the effectiveness of the implementation—and to build and extend the evidence related to clinical efficacy and effectiveness through:
- Better characterization of patients' pain duration, opioid use at baseline, prevalence of common medical and mental health comorbidities, co-interventions, and usual care;
- More rigorous evaluation of model fidelity;
- Assessment of a broader range of clinically-relevant core outcomes per IMMPACT (Methods, Measurement, and Pain Assessment in Clinical Trials) recommendations;
- Follow-up of participants on a longer-term basis;
- Inclusion of potentially underserved populations, such as rural settings and racial/ethnic minorities; and
- Seeking to better understand how these models are affecting providers' experiences.
For additional related evidence review work, an updated review of the state-of-the-science of chronic pain outcome assessment could be useful in informing the direction of future research. Also, as this is anticipated to continue to be an important clinical area in the future, with rapid evidence development expected, investigators suggest conducting an updated evidence review in a few years. For example, several additional multimodal chronic pain care models have already shown promise for improving patient outcomes in single-arm studies, and they also identified several ongoing studies which may fill gaps in existing research or provide further support for various models of pain care.
View the full report:
Peterson K, Anderson J, Bourne D, Erickson K, Mackey K, Helfand M. Evidence Brief: Effectiveness of Models Used to Deliver Multimodal Care for Chronic Musculoskeletal Pain. VA ESP Project #09-199; 2017.
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