Inequalities in the prevalence recording of 205 chronic conditions recorded in primary and secondary care for 12 million patients in the English National Health Service

被引:1
作者
Wang, Shaolin [1 ]
Lau, Yiu-Shing [1 ]
Sutton, Matt [1 ]
Anderson, Michael [1 ]
Kypridemos, Christodoulos [2 ]
Head, Anna [2 ]
Barr, Ben [2 ]
Cookson, Richard [3 ]
Bentley, Chris
Anselmi, Laura [1 ]
机构
[1] Univ Manchester, Hlth Org Policy & Econ, Manchester, England
[2] Univ Liverpool, Dept Publ Hlth Policy & Syst, Liverpool, England
[3] Univ York, Ctr Hlth Econ, York, England
来源
BMC MEDICINE | 2024年 / 22卷 / 01期
关键词
Inequality; Chronic conditions; Primary care; Secondary care; Diagnostic recording; ENGLAND;
D O I
10.1186/s12916-024-03767-4
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BackgroundUnderstanding the prevalence of diseases and where it is detected and recorded in healthcare settings is important for planning effective prevention and care provision. We examined inequalities in the prevalence of 205 chronic conditions and in the care setting where the related diagnoses were recorded in the English National Health Service.MethodsWe used data from the Clinical Practice Research Datalink Aurum linked with Hospital Episode Statistics for 12.8 million patients registered with 1406 general practices in 2018. We mapped diagnoses recorded in primary and secondary care in the previous 12 years. We used linear regressions to assess associations of ethnicity, deprivation, and general practice with a diagnosis being recorded in primary care only, secondary care only, or both settings.Results72.65% of patients had at least one diagnosis recorded in any care setting. Most diagnoses were reported only in primary care (62.56%) and a minority only in secondary care (15.24%) or in both settings (22.18%). Black (- 0.08 percentage points (pp)), Asian (- 0.08 pp), mixed (- 0.13 pp), and other ethnicity patients (- 0.31 pp) were less likely than White patients to have a condition recorded. Patients in most deprived areas were 0.27 pp more likely to have a condition recorded (+ 0.07 pp in secondary care only, + 0.10 pp in both primary and secondary care, and + 0.10 pp in primary care only). Differences in prevalence by ethnicity were driven by diagnostic recording in primary care. Higher recording of diagnoses in more deprived areas was consistent across care settings. There were large differences in prevalence and diagnostic recording between general practices after adjusting for patient characteristics.ConclusionsLinked primary and secondary care records support the identification of disease prevalence more comprehensively. There are inequalities in the prevalence and setting of diagnostic recording by ethnicity, deprivation, and providers on average across conditions. Further research should examine inequalities for each specific condition and whether they reflect also differences in access or recording as well as disease burden. Improving recording where needed and making national linked records accessible for research are key to understanding and reducing inequalities in disease prevention and management.
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页数:11
相关论文
共 33 条
[1]  
Boyd A., 2017, Understanding Hospital Episode Statistics (HES)
[2]   Keep it simple? Predicting primary health care costs with clinical morbidity measures [J].
Brilleman, Samuel L. ;
Gravelle, Hugh ;
Hollinghurst, Sandra ;
Purdy, Sarah ;
Salisbury, Chris ;
Windmeijer, Frank .
JOURNAL OF HEALTH ECONOMICS, 2014, 35 :109-122
[3]   A comparison of the recording of comorbidity in primary and secondary care by using the Charlson Index to predict short-term and long-term survival in a routine linked data cohort [J].
Crooks, C. J. ;
West, J. ;
Card, T. R. .
BMJ OPEN, 2015, 5 (06)
[4]   Recording a diagnosis of stroke, transient ischaemic attack or myocardial infarction in primary healthcare and the association with dispensation of secondary preventive medication: a registry-based prospective cohort study [J].
Dahlgren, Cecilia ;
Geary, Lukas ;
Hasselstrom, Jan ;
Rehnberg, Clas ;
Schenck-Gustafsson, Karin ;
Wandell, Per ;
von Euler, Mia .
BMJ OPEN, 2017, 7 (09)
[5]  
Denaxas S., 2019, Machine-readable version of electronic health record phenotypes for Kuan
[6]   Characterising complex health needs and the use of preventive therapies in the older population: a population-based cohort analysis of UK primary care and hospital linked data [J].
Elhussein, Leena ;
Jodicke, Annika M. M. ;
He, Ying ;
Delmestri, Antonella ;
Robinson, Danielle E. ;
Strauss, Victoria Y. ;
Prieto-Alhambra, Daniel .
BMC GERIATRICS, 2023, 23 (01)
[7]   Implicit bias in healthcare professionals: a systematic review [J].
FitzGerald, Chloe ;
Hurst, Samia .
BMC MEDICAL ETHICS, 2017, 18
[8]  
Head A, 2019, CPRDmultimorebiditycodelists
[9]   Multimorbidity research: where one size does not fit all [J].
Head, Anna ;
O'Flaherty, Martin ;
Kypridemos, Chris .
BMJ MEDICINE, 2024, 3 (01)
[10]   Inequalities in incident and prevalent multimorbidity in England, 2004-19: a population-based, descriptive study [J].
Head, Anna ;
Fleming, Kate ;
Kypridemos, Chris ;
Schofield, Pieta ;
Pearson-Stuttard, Jonathan ;
O'Flaherty, Martin .
LANCET HEALTHY LONGEVITY, 2021, 2 (08) :E489-E497