Interdisciplinary Multimodal Pain Rehabilitation in Patients with Chronic Musculoskeletal Pain in Primary Care-A Cohort Study from the Swedish Quality Registry for Pain Rehabilitation (SQRP).
Lukasz Mateusz FalkhamnGunilla StenbergPaul EnthovenBritt-Marie StålnackePublished in: International journal of environmental research and public health (2023)
Chronic pain is a major public health issue. Mounting evidence suggests that interdisciplinary multimodal pain rehabilitation programs (IMMRPs) performed in specialist pain care are an effective treatment for patients with chronic pain, but the effects of such treatment if performed in primary care settings have been less studied. The aims of this pragmatic study were to (1) describe characteristics of patients participating in IMMRPs in primary care; (2) examine whether IMMRPs in primary care improve pain, disability, quality of life, and sick leave 1-year post discharge in patients with chronic pain; and (3) investigate if outcomes differ between women and men. Data from 744 (645 women and 99 men, age range 18-65 years) patients with non-malignant chronic pain included in the Swedish Quality Registry for Pain Rehabilitation Primary Care were used to describe patient characteristics and changes in health and sick leave. At 1-year follow-up, the patients had improved significantly ( p < 0.01) in all health outcome measures and had reduced sick leave except in men, where no significant change was shown in physical activity level. This study indicates that MMRPs in primary care improved pain and physical and emotional health and reduced sick leave, which was maintained at the 1-year follow-up.
Keyphrases
- chronic pain
- primary care
- pain management
- public health
- physical activity
- healthcare
- end stage renal disease
- ejection fraction
- mental health
- peritoneal dialysis
- body mass index
- type diabetes
- pregnant women
- chronic kidney disease
- skeletal muscle
- spinal cord injury
- spinal cord
- deep learning
- health information
- patient reported outcomes
- artificial intelligence
- study protocol
- weight loss