Sequence Analysis to Phenotype Healthcare Patterns in Adults with Musculoskeletal Conditions Using Primary Care Electronic Health Records

Mathew, Smitha; Peat, George; Parry, Emma; Wilkie, Ross; Jordan, Kelvin P; Hill, Jonathan C; Yu, Dahai

Abstract

ObjectiveThe aim of this study was to apply sequence analysis (SA) to phenotype healthcare patterns of adult patients with musculoskeletal (MSK) conditions using primary care electronic health records and to investigate the association between these healthcare patterns and post‐consultation patient's self‐reported outcome.MethodsData from the Multi‐level Integrated Data for musculoskeletal health intelligence and ActionS (MIDAS) programme conducted in North Staffordshire and Stoke‐on‐Trent, UK was utilised. The study included patients aged ≥18 years who consulted primary care for MSK conditions between September 2021 and July 2022. SA was employed to categorise patients with similar healthcare patterns in primary care in the five years prior to their index consultation in respect to consultations, analgesic prescriptions, imaging, physiotherapy, and secondary care referrals. Association of socio‐demographic characteristics and self‐reported outcome with clusters were determined.ResultsIn total, 1,875 patients consulting primary care for MSK conditions were available for analysis. SA identified five clusters of prior healthcare patterns among patients with MSK conditions, including "increasing consultation and analgesia" (5.60%), "low consultation and healthcare use" (57.39%), "high consultation and healthcare use" (8.32%), "low consultation but high analgesia" (13.01%), and "low consultation but moderate healthcare use" (15.68%). Patients in the "high consultation and healthcare use" group were predominantly female, older, obese, had more comorbidities and lived in the most deprived areas compared to those in the "low consultation and healthcare use" group. Additionally, self‐reported outcome varied significantly between clusters, with patients in the "high consultation and healthcare use" group reporting worse self‐ reported outcome.ConclusionThis analysis identified five distinct clusters of healthcare patterns for patients with MSK conditions in primary care and observed substantial variations in patient's self‐reported outcome and socio‐demographic profiles across these different groups of patients.image

Citation

Mathew, S., Peat, G., Parry, E., Wilkie, R., Jordan, K. P., Hill, J. C., & Yu, D. (in press). Sequence Analysis to Phenotype Healthcare Patterns in Adults with Musculoskeletal Conditions Using Primary Care Electronic Health Records. Arthritis Care & Research, 1-29. https://doi.org/10.1002/acr.25514

• Journal Article Type: Article
• Acceptance Date: Jan 29, 2025
• Online Publication Date: Mar 2, 2025
• Deposit Date: Mar 28, 2025
• Journal: Arthritis Care & Research
• Print ISSN: 2151-464X
• Electronic ISSN: 2151-4658
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Pages: 1-29
• DOI: https://doi.org/10.1002/acr.25514
• Keywords: sequence analysis, optimal matching, cluster analysis, healthcare patterns, musculoskeletal conditions, primary care, electronic health records
• Public URL: https://keele-repository.worktribe.com/output/1110028