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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....
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Royal College of General Practitioners
2021
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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. |
format | Online Article Text |
id | pubmed-8340730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Royal College of General Practitioners |
record_format | MEDLINE/PubMed |
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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