Evidence map›Paper›PMID 34340970›Full record

ArticleThe British journal of general practice : the journal of the Royal College of General Practitioners2021

Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records

Alex J Walker, Brian MacKenna, Peter Inglesby, Laurie Tomlinson, Christopher T Rentsch, Helen J Curtis, Caroline E Morton, Jessica Morley, Amir Mehrkar, Seb Bacon and 31 more

Abstract read
In one paragraph

Article in The British journal of general practice : the journal of the Royal College of General Practitioners, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

60 citing papers in PubMed.

  1. Article
  2. Observational
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  5. Review
  6. Effect of Metformin on the Risk of Post-COVID-19 Condition Among Individuals With Overweight or Obese: A Population-based Retrospective Cohort Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
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  15. Observational
  16. Article
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  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

41 authors.

Alex J WalkerThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Brian MacKennaThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Peter InglesbyThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Laurie TomlinsonFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Christopher T RentschFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Helen J CurtisThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Caroline E MortonThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Jessica MorleyThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Amir MehrkarThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Seb BaconThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
George HickmanThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Chris BatesTPP, Leeds.
Richard CrokerThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
David EvansThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Tom WardThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Jonathan CockburnTPP, Leeds.
Simon DavyThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Krishnan BhaskaranFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Anna SchultzeFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Elizabeth J WilliamsonFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
William J HulmeThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Helen I McDonaldFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Rohini MathurFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Rosalind M EggoFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Kevin WingFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Angel Ys WongFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Harriet ForbesFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
John TazareFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
John ParryTPP, Leeds.
Frank HesterTPP, Leeds.
Sam HarperTPP, Leeds.
Shaun O'HanlonEMIS Health, Leeds.
Alex EavisEMIS Health, Leeds.
Richard JarvisEMIS Health, Leeds.
Dima AvramovEMIS Health, Leeds.
Paul GriffithsEMIS Health, Leeds.
Aaron FowlesEMIS Health, Leeds.
Nasreen ParkesEMIS Health, Leeds.
Ian J DouglasFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
Stephen Jw EvansFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
(The OpenSAFELY Collaborative)

Funding

Medical Research Council MC_PC_20030Medical Research Council MC_PC_20051Medical Research Council MC_PC_20058Medical Research Council MC_PC_20059Medical Research Council MR/S003940/1Medical Research Council MR/S003975/1
6 · The paper itself

Abstract

backgroundLong 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.

aimTo describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time. DESIGN AND

settingPopulation-based cohort study in English primary care.

methodWorking 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.

resultsLong 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).

conclusionCurrent 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.

Indexed as

Clinical CodingCOVID-19Cohort StudiesEnglandFemaleHumansMalePost-Acute COVID-19 SyndromePrimary Health CareCOVID-19electronic health recordsgeneral practicelong COVIDprimary health care

Identifiers

PMID34340970
PMCPMC8340730

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.