Impact of COVID-19 pandemic on incidence of long-term conditions in Wales: a population data linkage study using primary and secondary care health records

被引:14
作者
Qi, Cathy [1 ,8 ]
Osborne, Tim [1 ]
Bailey, Rowena [1 ]
Cooper, Alison [3 ]
Hollinghurst, Joe P. [1 ]
Akbari, Ashley
Crowder, Ruth [4 ,5 ]
Peters, Holly
Law, Rebecca-Jane [6 ]
Lewis, Ruth [7 ]
Smith, Deb [3 ]
Edwards, Adrian [3 ]
Lyons, Ronan [2 ]
机构
[1] Swansea Univ, Fac Med Hlth & Life Sci, Med Sch, Populat Data Sci Res, Swansea, Wales
[2] Swansea Univ, Fac Med Hlth & Life Sci, Med Sch, Publ Hlth, Swansea, Wales
[3] Cardiff Univ, Wales COVID 19 Evidence Ctr, Div Populat Med, Gen Practice, Cardiff, Wales
[4] Welsh Govt, Hlth & Social Serv Grp, Directorate Primar Care & Mental Hlth, Cardiff, Wales
[5] Cardiff Univ, Ctr Med Educ, Cardiff, Wales
[6] Welsh Govt, Hlth & Social Serv Grp, Tech Advisory Cell, Cardiff, Wales
[7] Bangor Univ, North Wales Ctr Primar Care Res, PRIME Ctr Wales, Bangor, Wales
[8] Swansea Univ, Fac Med Hlth & Life Sci, Med Sch, Populat Data Sci, Swansea SA2 8PP, Wales
关键词
anxiety; chronic disease; COVID-19; diagnosis; primary health care; ENVIRONMENT; VALIDATION; PRIVACY;
D O I
10.3399/BJGP.2022.0353
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background The COVID-19 pandemic has directly and indirectly had an impact on health service provision owing to surges and sustained pressures on the system. The effects of these pressures on the management of long-term or chronic conditions are not fully understood.Aim To explore the effects of COVID-19 on the recorded incidence of 17 long-term conditions.Design and setting This was an observational retrospective population data linkage study on the population of Wales using primary and secondary care data within the Secure Anonymised Information Linkage (SAIL) Databank.Method Monthly rates of new diagnosis between 2000 and 2021 are presented for each long-term condition. Incidence rates post-2020 were compared with expected rates predicted using time series modelling of pre-2020 trends. The proportion of annual incidence is presented by sociodemographic factors: age, sex, social deprivation, ethnicity, frailty, and learning disability.Results A total of 5 476 012 diagnoses from 2 257 992 individuals are included. Incidence rates from 2020 to 2021 were lower than mean expected rates across all conditions. The largest relative deficit in incidence was in chronic obstructive pulmonary disease corresponding to 343 (95% confidence interval = 230 to 456) undiagnosed patients per 100 000 population, followed by depression, type 2 diabetes, hypertension, anxiety disorders, and asthma. A GP practice of 10 000 patients might have over 400 undiagnosed long-term conditions. No notable differences between sociodemographic profiles of post-and pre-2020 incidences were observed.Conclusion There is a potential backlog of undiagnosed patients with multiple long-term conditions. Resources are required to tackle anticipated workload as part of COVID-19 recovery, particularly in primary care. direct and of effects include postponement other surge that cancelled peak 12 The include screening long-term condition but other diabetes conditions age
引用
收藏
页码:E332 / E339
页数:8
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