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

BACKGROUND: 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. AIM: To describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time....

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Autores principales: Walker, Alex J, MacKenna, Brian, Inglesby, Peter, Tomlinson, Laurie, Rentsch, Christopher T, Curtis, Helen J, Morton, Caroline E, Morley, Jessica, Mehrkar, Amir, Bacon, Seb, Hickman, George, Bates, Chris, Croker, Richard, Evans, David, Ward, Tom, Cockburn, Jonathan, Davy, Simon, Bhaskaran, Krishnan, Schultze, Anna, Williamson, Elizabeth J, Hulme, William J, McDonald, Helen I, Mathur, Rohini, Eggo, Rosalind M, Wing, Kevin, Wong, Angel YS, Forbes, Harriet, Tazare, John, Parry, John, Hester, Frank, Harper, Sam, O’Hanlon, Shaun, Eavis, Alex, Jarvis, Richard, Avramov, Dima, Griffiths, Paul, Fowles, Aaron, Parkes, Nasreen, Douglas, Ian J, Evans, Stephen JW, Smeeth, Liam, Goldacre, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal College of General Practitioners 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340730/
https://www.ncbi.nlm.nih.gov/pubmed/34340970
http://dx.doi.org/10.3399/BJGP.2021.0301
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author Walker, Alex J
MacKenna, Brian
Inglesby, Peter
Tomlinson, Laurie
Rentsch, Christopher T
Curtis, Helen J
Morton, Caroline E
Morley, Jessica
Mehrkar, Amir
Bacon, Seb
Hickman, George
Bates, Chris
Croker, Richard
Evans, David
Ward, Tom
Cockburn, Jonathan
Davy, Simon
Bhaskaran, Krishnan
Schultze, Anna
Williamson, Elizabeth J
Hulme, William J
McDonald, Helen I
Mathur, Rohini
Eggo, Rosalind M
Wing, Kevin
Wong, Angel YS
Forbes, Harriet
Tazare, John
Parry, John
Hester, Frank
Harper, Sam
O’Hanlon, Shaun
Eavis, Alex
Jarvis, Richard
Avramov, Dima
Griffiths, Paul
Fowles, Aaron
Parkes, Nasreen
Douglas, Ian J
Evans, Stephen JW
Smeeth, Liam
Goldacre, Ben
author_facet Walker, Alex J
MacKenna, Brian
Inglesby, Peter
Tomlinson, Laurie
Rentsch, Christopher T
Curtis, Helen J
Morton, Caroline E
Morley, Jessica
Mehrkar, Amir
Bacon, Seb
Hickman, George
Bates, Chris
Croker, Richard
Evans, David
Ward, Tom
Cockburn, Jonathan
Davy, Simon
Bhaskaran, Krishnan
Schultze, Anna
Williamson, Elizabeth J
Hulme, William J
McDonald, Helen I
Mathur, Rohini
Eggo, Rosalind M
Wing, Kevin
Wong, Angel YS
Forbes, Harriet
Tazare, John
Parry, John
Hester, Frank
Harper, Sam
O’Hanlon, Shaun
Eavis, Alex
Jarvis, Richard
Avramov, Dima
Griffiths, Paul
Fowles, Aaron
Parkes, Nasreen
Douglas, Ian J
Evans, Stephen JW
Smeeth, Liam
Goldacre, Ben
author_sort Walker, Alex J
collection PubMed
description BACKGROUND: 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. AIM: To describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time. DESIGN AND SETTING: Population-based cohort study in English primary care. METHOD: 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. RESULTS: 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). CONCLUSION: 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.
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spelling pubmed-83407302021-08-20 Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY Walker, Alex J MacKenna, Brian Inglesby, Peter Tomlinson, Laurie Rentsch, Christopher T Curtis, Helen J Morton, Caroline E Morley, Jessica Mehrkar, Amir Bacon, Seb Hickman, George Bates, Chris Croker, Richard Evans, David Ward, Tom Cockburn, Jonathan Davy, Simon Bhaskaran, Krishnan Schultze, Anna Williamson, Elizabeth J Hulme, William J McDonald, Helen I Mathur, Rohini Eggo, Rosalind M Wing, Kevin Wong, Angel YS Forbes, Harriet Tazare, John Parry, John Hester, Frank Harper, Sam O’Hanlon, Shaun Eavis, Alex Jarvis, Richard Avramov, Dima Griffiths, Paul Fowles, Aaron Parkes, Nasreen Douglas, Ian J Evans, Stephen JW Smeeth, Liam Goldacre, Ben Br J Gen Pract Research BACKGROUND: 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. AIM: To describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time. DESIGN AND SETTING: Population-based cohort study in English primary care. METHOD: 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. RESULTS: 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). CONCLUSION: 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. Royal College of General Practitioners 2021-08-03 /pmc/articles/PMC8340730/ /pubmed/34340970 http://dx.doi.org/10.3399/BJGP.2021.0301 Text en © The Authors https://creativecommons.org/licenses/by/4.0/This article is Open Access: CC BY 4.0 licence (http://creativecommons.org/licences/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Research
Walker, Alex J
MacKenna, Brian
Inglesby, Peter
Tomlinson, Laurie
Rentsch, Christopher T
Curtis, Helen J
Morton, Caroline E
Morley, Jessica
Mehrkar, Amir
Bacon, Seb
Hickman, George
Bates, Chris
Croker, Richard
Evans, David
Ward, Tom
Cockburn, Jonathan
Davy, Simon
Bhaskaran, Krishnan
Schultze, Anna
Williamson, Elizabeth J
Hulme, William J
McDonald, Helen I
Mathur, Rohini
Eggo, Rosalind M
Wing, Kevin
Wong, Angel YS
Forbes, Harriet
Tazare, John
Parry, John
Hester, Frank
Harper, Sam
O’Hanlon, Shaun
Eavis, Alex
Jarvis, Richard
Avramov, Dima
Griffiths, Paul
Fowles, Aaron
Parkes, Nasreen
Douglas, Ian J
Evans, Stephen JW
Smeeth, Liam
Goldacre, Ben
Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
title Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
title_full Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
title_fullStr Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
title_full_unstemmed Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
title_short Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
title_sort clinical coding of long covid in english primary care: a federated analysis of 58 million patient records in situ using opensafely
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340730/
https://www.ncbi.nlm.nih.gov/pubmed/34340970
http://dx.doi.org/10.3399/BJGP.2021.0301
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