Dr. Dahai Yu d.yu@keele.ac.uk
Estimating the population health burden of musculoskeletal conditions using primary care electronic health records
Yu, D; Peat, G; Jordan, KP; Bailey, J; Prieto-Alhambra, D; Robinson, DE; Strauss, VY; Walker-Bone, K; Silman, A; Mamas, M; Blackburn, S; Dent, S; Dunn, K; Judge, A; Protheroe, J; Wilkie, R
Authors
G Peat
Kelvin Jordan k.p.jordan@keele.ac.uk
James Bailey j.bailey4@keele.ac.uk
D Prieto-Alhambra
DE Robinson
VY Strauss
K Walker-Bone
A Silman
Mamas Mamas m.mamas@keele.ac.uk
S Blackburn
S Dent
Professor Kathryn Dunn k.m.dunn@keele.ac.uk
A Judge
Joanne Protheroe j.protheroe@keele.ac.uk
Ross Wilkie r.wilkie@keele.ac.uk
Abstract
Objectives
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.
Methods
We collected validated patient-reported measures of pain experience, function, health status through a local survey of adults (?34?years) presenting to English general practices over 12-months for low back pain (LBP), 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 LBP 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.
Results
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 (?34?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 three years.
Conclusion
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.
Citation
Yu, D., Peat, G., Jordan, K., Bailey, J., Prieto-Alhambra, D., Robinson, D., …Wilkie, R. (2021). Estimating the population health burden of musculoskeletal conditions using primary care electronic health records. Rheumatology, 60(10), 4832-4843. https://doi.org/10.1093/rheumatology/keab109
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 18, 2021 |
Online Publication Date | Feb 9, 2021 |
Publication Date | 2021-10 |
Journal | Rheumatology |
Print ISSN | 1462-0324 |
Publisher | Oxford University Press |
Peer Reviewed | Peer Reviewed |
Volume | 60 |
Issue | 10 |
Pages | 4832-4843 |
DOI | https://doi.org/10.1093/rheumatology/keab109 |
Keywords | electronic health records, primary care, musculoskeletal, health services research, surveillance, pain, quality of life, back pain, shoulder pain |
Publisher URL | https://doi.org/10.1093/rheumatology/keab109 |
Files
PRELIM-2 PAPER Final submission to rheumatology.pdf
(2.6 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
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