Musculoskeletal conditions represent a considerable burden worldwide, and are predominantly managed in primary care. Evidence suggests that many musculoskeletal conditions share similar prognostic factors. Systematically assessing patient's prognosis and matching treatments based on prognostic subgroups (stratified care) has been shown to be both clinically effective and cost-effective. This study (Keele Aches and Pains Study) aims to refine and examine the validity of a brief questionnaire (Keele STarT MSK tool) designed to enable risk stratification of primary care patients with the five most common musculoskeletal pain presentations. We also describe the subgroups of patients, and explore the acceptability and feasibility of using the tool and how the tool is best implemented in clinical practice. The study design is mixed methods: a prospective, quantitative observational cohort study with a linked qualitative focus group and interview study. Patients who have consulted their GP or health care practitioner about a relevant musculoskeletal condition will be recruited from general practice. Participating patients will complete a baseline questionnaire (shortly after consultation), plus questionnaires 2 and 6 months later. A subsample of patients, along with participating GPs and health care practitioners, will be invited to take part in qualitative focus groups and interviews. The Keele STarT MSK tool will be refined based on face, discriminant, construct, and predictive validity at baseline and 2 months, and validated using data from 6-month follow-up. Patient and clinician perspectives about using the tool will be explored. This study will provide a validated prognostic tool (Keele STarT MSK) with established cutoff points to stratify patients with the five most common musculoskeletal presentations into low-, medium-, and high-risk subgroups. The qualitative analysis of patient and health care perspectives will inform practitioners on how to embed the tool into clinical practice using established general practice IT systems and clinician-support packages.
Keywords: musculoskeletal; pain; predictive; primary care; risk; stratified care.