The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Br J Gen Pract. 2021 Oct 28;71(712):e806-e814. doi: 10.3399/BJGP.2021.0301. Print 2021 Nov.
Long COVID describes new or persistent symptoms at least 4 weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were recently created.
To describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time.
Population-based cohort study in English primary care.
Working on behalf of NHS England, OpenSAFELY data were used encompassing 96% of the English population between 1 February 2020 and 25 May 2021. The proportion of people with a recorded code for long COVID was measured overall and by demographic factors, electronic health record software system (EMIS or TPP), and week.
Long COVID was recorded for 23 273 people. Coding was unevenly distributed among practices, with 26.7% of practices having never used the codes. Regional variation ranged between 20.3 per 100 000 people for East of England (95% confidence interval [CI] = 19.3 to 21.4) and 55.6 per 100 000 people in London (95% CI = 54.1 to 57.1). Coding was higher among females (52.1, 95% CI = 51.3 to 52.9) than males (28.1, 95% CI = 27.5 to 28.7), and higher among practices using EMIS (53.7, 95% CI = 52.9 to 54.4) than those using TPP (20.9, 95% CI = 20.3 to 21.4).
Current recording of long COVID in primary care is very low, and variable between practices. This may reflect patients not presenting; clinicians and patients holding different diagnostic thresholds; or challenges with the design and communication of diagnostic codes. Increased awareness of diagnostic codes is recommended to facilitate research and planning of services, and also surveys with qualitative work to better evaluate clinicians' understanding of the diagnosis.
长新冠是指急性 COVID-19 发病后至少 4 周出现新的或持续的症状。最近创建了用于描述这一现象的临床代码。
描述长新冠代码的使用情况,以及按一般实践、人口统计学变量和随时间的变化情况。
在英国初级保健中进行的基于人群的队列研究。
代表英格兰国民保健署(NHS England),使用 OpenSAFELY 数据,涵盖了 2020 年 2 月 1 日至 2021 年 5 月 25 日期间 96%的英格兰人口。总体上以及按人口统计学因素、电子健康记录软件系统(EMIS 或 TPP)和周来衡量记录长新冠代码的人数比例。
记录了 23273 例长新冠病例。代码在实践中分布不均,有 26.7%的实践从未使用过这些代码。区域差异范围为英格兰东部每 100000 人 20.3(95%置信区间[CI] = 19.3 至 21.4)至伦敦每 100000 人 55.6(95%CI = 54.1 至 57.1)。女性(52.1,95%CI = 51.3 至 52.9)的编码率高于男性(28.1,95%CI = 27.5 至 28.7),使用 EMIS 的实践(53.7,95%CI = 52.9 至 54.4)的编码率高于使用 TPP 的实践(20.9,95%CI = 20.3 至 21.4)。
目前初级保健中长新冠的记录非常低,而且各实践之间存在差异。这可能反映了患者未出现;临床医生和患者持有不同的诊断标准;或者诊断代码的设计和沟通存在挑战。建议提高对诊断代码的认识,以促进研究和服务规划,并进行带有定性工作的调查,以更好地评估临床医生对该诊断的理解。