Keele Aches and Pains Study protocol: validity, acceptability, and feasibility of the Keele STarT MSK tool for subgrouping musculoskeletal patients in primary care

Paul Campbell,1 Jonathan C Hill,1 Joanne Protheroe,1 Ebenezer K Afolabi,1 Martyn Lewis,1 Ruth Beardmore,1 Elaine M Hay,1 Christian D Mallen,1 Bernadette Bartlam,1 Benjamin Saunders,1 Danielle A van der Windt,1 Sue Jowett,2 Nadine E Foster,1 Kate M Dunn1 1Arthritis Research UK Primary Care Centre, Research Institute of Primary Care and Health Sciences, Keele University, Keele, 2Health Economics Unit, University of Birmingham, Birmingham, UK Abstract: 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