Estimating the population health burden of musculoskeletal conditions using primary care electronic health records.


Journal

Rheumatology (Oxford, England)
ISSN: 1462-0332
Titre abrégé: Rheumatology (Oxford)
Pays: England
ID NLM: 100883501

Informations de publication

Date de publication:
02 10 2021
Historique:
received: 22 10 2020
accepted: 18 01 2021
pubmed: 10 2 2021
medline: 30 12 2021
entrez: 9 2 2021
Statut: ppublish

Résumé

Better indicators from affordable, sustainable data sources are needed to monitor population burden of musculoskeletal conditions. We propose five indicators of musculoskeletal health and assessed if routinely available primary care electronic health records (EHR) can estimate population levels in musculoskeletal consulters. We collected validated patient-reported measures of pain experience, function and health status through a local survey of adults (≥35 years) presenting to English general practices over 12 months for low back pain, shoulder pain, osteoarthritis and other regional musculoskeletal disorders. Using EHR data we derived and validated models for estimating population levels of five self-reported indicators: prevalence of high impact chronic pain, overall musculoskeletal health (based on Musculoskeletal Health Questionnaire), quality of life (based on EuroQoL health utility measure), and prevalence of moderate-to-severe low back pain and moderate-to-severe shoulder pain. We applied models to a national EHR database (Clinical Practice Research Datalink) to obtain national estimates of each indicator for three successive years. The optimal models included recorded demographics, deprivation, consultation frequency, analgesic and antidepressant prescriptions, and multimorbidity. Applying models to national EHR, we estimated that 31.9% of adults (≥35 years) presenting with non-inflammatory musculoskeletal disorders in England in 2016/17 experienced high impact chronic pain. Estimated population health levels were worse in women, older aged and those in the most deprived neighbourhoods, and changed little over 3 years. National and subnational estimates for a range of subjective indicators of non-inflammatory musculoskeletal health conditions can be obtained using information from routine electronic health records.

Identifiants

pubmed: 33560340
pii: 6131799
doi: 10.1093/rheumatology/keab109
pmc: PMC8487274
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4832-4843

Subventions

Organisme : Medical Research Council
ID : MC_PC_15015
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_U147585823
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_12011/5
Pays : United Kingdom
Organisme : PRELIM
Organisme : Versus Arthritis
ID : 21403
Pays : United Kingdom
Organisme : Honorary Academic Consultant Contracts from Public Health England
Organisme : NIHR Applied Research Collaboration (West Midlands)
Organisme : National Institute for Health Research (NIHR) Oxford Biomedical Research Centre
Organisme : NIHR Senior Research Fellowship
ID : SRF-2018-11-ST2-004
Organisme : NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology.

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Auteurs

Dahai Yu (D)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.

George Peat (G)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.
MRC Versus Arthritis Centre for Musculoskeletal Health and Work, University of Southampton, Southampton.

Kelvin P Jordan (KP)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.
Centre for Prognostic Research, Primary Care Centre Versus Arthritis, School of Primary, Community and Social Care, Keele University, Keele.

James Bailey (J)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.

Daniel Prieto-Alhambra (D)

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford.

Danielle E Robinson (DE)

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford.

Victoria Y Strauss (VY)

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford.

Karen Walker-Bone (K)

MRC Versus Arthritis Centre for Musculoskeletal Health and Work, University of Southampton, Southampton.
MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton.

Alan Silman (A)

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford.

Mamas Mamas (M)

Keele Cardiovascular Research Group, Centre for Prognosis Research, School of Medicine, Keele University, Keele.

Steven Blackburn (S)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.

Kate Dunn (K)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.

Andrew Judge (A)

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford.
Musculoskeletal Research Unit, University of Bristol, Bristol, UK.

Joanne Protheroe (J)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.

Ross Wilkie (R)

Primary Care Centre Versus Arthritis, School of Medicine, Keele University.
MRC Versus Arthritis Centre for Musculoskeletal Health and Work, University of Southampton, Southampton.

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