| アブストラクト | OBJECTIVE: To assess the diagnostic Read code usage for 18 conditions by examining their frequency and diversity in UK primary care between 2000 and 2013. DESIGN: Population-based cohort study SETTING: 684 UK general practices contributing data to the Clinical Practice Research Datalink (CPRD) GOLD. PARTICIPANTS: Patients with clinical codes for at least one of asthma, chronic obstructive pulmonary disease, diabetes, hypertension (HT), coronary heart disease, atrial fibrillation (AF), heart failure, stroke, hypothyroidism, chronic kidney disease, learning disability (LD), depression, dementia, epilepsy, severe mental illness (SMI), osteoarthritis, osteoporosis and cancer. PRIMARY AND SECONDARY OUTCOME MEASURES: For the frequency ranking of clinical codes, canonical correlation analysis was applied to correlations of clinical code usage of 1, 3 and 5 years. Three measures of diversity (Shannon entropy index of diversity, richness and evenness) were used to quantify changes in incident and total clinical codes. RESULTS: Overall, all examined conditions, except LD, showed positive monotonic correlation. HT, hypothyroidism, osteoarthritis and SMI codes' usage had high 5-year correlation. The codes' usage diversity remained stable overall throughout the study period. Cancer, diabetes and SMI had the highest richness (code lists need time to define) unlike AF, hypothyroidism and LD. SMI (high richness) and hypothyroidism (low richness) can last for 5 years, whereas cancer and diabetes (high richness) and LD (low richness) only last for 2 years. CONCLUSIONS: This is an under-reported research area and the findings suggest the codes' usage diversity for most conditions remained overall stable throughout the study period. Generated mental health code lists can last for a long time unlike cardiometabolic conditions and cancer. Adopting more consistent and less diverse coding would help improve data quality in primary care. Future research is needed following the transfer to the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) coding. |
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| 投稿者 | Zghebi, Salwa S; Reeves, David; Grigoroglou, Christos; McMillan, Brian; Ashcroft, Darren M; Parisi, Rosa; Kontopantelis, Evangelos |
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| 組織名 | NIHR School for Primary Care Research, Centre for Primary Care and Health;Services Research, Manchester Academic Health Science Centre (MAHSC), The;University of Manchester, Manchester, UK salwa.zghebi@manchester.ac.uk.;Division of Population Health, Health Services Research and Primary Care, School;of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic;Health Science Centre (MAHSC), The University of Manchester, Manchester, UK.;University of Manchester, Manchester, UK.;Centre for Biostatistics, School of Health Sciences, Faculty of Biology, Medicine;and Health, Manchester Academic Health Science Centre (MAHSC), The University of;Manchester, Manchester, UK.;Manchester Centre for Health Economics, Division of Population Health, Health;Services Research and Primary Care, Manchester Academic Health Science Centre;(MAHSC), The University of Manchester, Manchester, UK.;Centre for Pharmacoepidemiology and Drug Safety, School of Health Sciences,;Faculty of Biology, Medicine and Health, Manchester Academic Health Science;Centre (MAHSC), The University of Manchester, Manchester, UK.;Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, |
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