A systematic review was conducted to evaluate the effectiveness of general prognostic tools in stratified care in improving pain and disability outcomes in patients with musculoskeletal disordersA systematic review was conducted to evaluate the effectiveness of general prognostic tools in stratified care in improving pain and disability outcomes in patients with musculoskeletal disorders
Peer-reviewed journal articles were adopted from databases such as MEDLINE, EMBASE, CINAHL, Web of Science (EBSCO) host, PsycINFO (OvidSP), CENTRAL, ClinicalTrial.gov, and Pedro. Studies published in English included involving human participants, with no time limits applied. The review emphasized studies that utilized stratified care models, employing prognostic tools like the STarT Back Tool and Keele STarT MSK Tool. Key outcomes analyzed included pain intensity and disability, measured by the Numeric Pain Rating Scale and the Oswestry Disability Index. Two independent reviewers conducted study selection, data extraction, and quality assessment using the QUIP tool.
26 studies involving over 9,000 patients were found to have met the set inclusion criteria and were included in the final list for review. The included studies were cluster randomized trials, prospective cohort studies, and randomized clinical trials. These studies evaluated the effectiveness of prognostic tools in stratifying patients with musculoskeletal pain and their impact on treatment outcomes.
Prognostic tools in stratified care show promise in optimizing treatment approaches for patients with musculoskeletal disorders. However, their overall effectiveness in significantly altering clinical outcomes across diverse clinical settings remains uncertain. Future research should focus on larger-scale studies to better understand the conditions under which these tools most effectively improve patient outcomes.
The use of prognostic tools, such as the STarT Back Tool and Keele STarT MSK Tool, shows promise in improving care for patients with musculoskeletal (MSK) disorders by allowing clinicians to stratify patients based on risk levels. This personalized approach can lead to more effective treatment strategies, improving pain and disability outcomes.In terms of management, integrating these tools into clinical workflows can enhance decision-making, reduce unnecessary interventions, and optimize resource use by focusing on those patients who will benefit most.For education, the results emphasize the need for training future physiotherapists and healthcare professionals in the use of prognostic tools. Incorporating this into the education curriculum will ensure that new practitioners are skilled in delivering targeted, personalized care.From a policy perspective, the findings support the integration of prognostic tools into standard care models, which could lead to improved patient outcomes and cost savings in healthcare. Policymakers could promote these tools as part of evidence-based strategies for managing MSK conditions, ensuring broader implementation across various clinical settings.
Prognostic Tools
Pain Management, Disability Outcomes
