Estimating the population health burden of musculoskeletal conditions using primary care electronic health records
| Autor: | Steven Blackburn, George Peat, Victoria Y Strauss, Kate M. Dunn, Alan J. Silman, Dahai Yu, James Bailey, Kelvin P. Jordan, Joanne Protheroe, Daniel Prieto-Alhambra, Karen Walker-Bone, Stephen Dent, Mamas A. Mamas, Ross Wilkie, Danielle E Robinson, Andrew Judge |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
0302 clinical medicine Cost of Illness RA0421 Surveys and Questionnaires Back pain Electronic Health Records pain Pharmacology (medical) Musculoskeletal Diseases 030212 general & internal medicine AcademicSubjects/MED00360 Aged 80 and over education.field_of_study 030503 health policy & services Age Factors Chronic pain Health services research Middle Aged Clinical Science Low back pain health services research England surveillance Female medicine.symptom 0305 other medical science Adult medicine.medical_specialty shoulder pain Population back pain Population health primary care 03 medical and health sciences Sex Factors Quality of life (healthcare) Rheumatology RC925 RC927 medicine Humans Medical prescription education Aged Models Statistical musculoskeletal Primary Health Care business.industry medicine.disease electronic health records quality of life Physical therapy business RA |
| Zdroj: | Yu, D, Peat, G, Jordan, K P, Bailey, J, Prieto-Alhambra, D, Robinson, D E, Strauss, V Y, Walker-Bone, K, Silman, A, Mamas, M, Blackburn, S, Dent, S, Dunn, K, Judge, A, Protheroe, J & Wilkie, R 2021, ' Estimating the population health burden of musculoskeletal conditions using primary care electronic health records ', Rheumatology, vol. 60, no. 10, keab109, pp. 4832-4843 . https://doi.org/10.1093/rheumatology/keab109 Rheumatology (Oxford, England) |
| ISSN: | 1462-0332 1462-0324 |
| DOI: | 10.1093/rheumatology/keab109 |
| Popis: | 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 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. 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 (≥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. 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. |
| Databáze: | OpenAIRE |
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