Reports

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

Description
Descriptive analysis of the use of long-COVID codes in English primary care.
Authors
Alex J Walker, Brian MacKenna, Peter Inglesby, Laurie Tomlinson, Christopher T Rentsch, Helen J Curtis, Caroline E Morton, Jessica Morley, Amir Mehrkar, Seb Bacon, George Hickman, Chris Bates, Richard Croker, David Evans, Tom Ward, Jonathan Cockburn, Simon Davy, Krishnan Bhaskaran, Anna Schultze, Elizabeth J Williamson, William J Hulme, Helen I McDonald, Rohini Mathur, Rosalind M Eggo, Kevin Wing, Angel YS Wong, Harriet Forbes, John Tazare, John Parry, Frank Hester, Sam Harper, Shaun O’Hanlon, Alex Eavis, Richard Jarvis, Dima Avramov, Paul Griffiths, Aaron Fowles, Nasreen Parkes, Ian J Douglas, Stephen JW Evans, Liam Smeeth, Ben Goldacre and (The OpenSAFELY Collaborative)
Contact
Get in touch and tell us how you use this report or new features you'd like to see: [email protected]
First published
03 Aug 2021
Last updated
19 Aug 2021

Long COVID coding in primary care.

This OpenSAFELY report is a routine update of our peer-review paper published in the British Journal of General Practice on the Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY.

It is a routine update of the analysis described in the paper. The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussionis and the full analytical methods on this routine report are available on GitHub.

OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. You can read more about OpenSAFELY on our website.

Report last updated 19 Aug 2021

Results

Counts and rates of long COVID coding stratified by demographic variable

This is equivalent to Table 2 from the paper

There were 43,740 people who have been given a diagnostic code for long COVID to date. Counts for each software system are:

TPP      11,501.0
EMIS     32,239.0
Totals   43,740.0
dtype: float64

The overall rate of long COVID coding in the population was 152 per 100,000 people. Rates for each software system are:

TPP       95.4
EMIS     192.5
Totals   151.9
dtype: float64
TPP EMIS Totals
Long COVID Rate per 100,000 % Long COVID Rate per 100,000 % Long COVID % Rate per 100,000
age_group 0-17 273 5.6 2.4 766 11.2 2.4 1039 2.4 8.9
18-24 685 35.9 6.0 1410 50.2 4.4 2095 4.8 44.4
25-34 1514 45.2 13.2 4152 85.9 12.9 5666 13.0 69.2
35-44 2326 72.0 20.2 7122 152.5 22.1 9448 21.6 119.6
45-54 3024 93.2 26.3 8694 193.4 27.0 11718 26.8 151.4
55-69 2952 69.9 25.7 8406 149.2 26.1 11358 26.0 115.2
70-79 532 25.4 4.6 1299 48.6 4.0 1831 4.2 38.4
80+ 195 16.0 1.7 390 24.8 1.2 585 1.3 21.0
sex F 7266 60.3 63.2 20640 123.3 64.0 27906 63.8 96.9
M 4235 35.1 36.8 11599 69.2 36.0 15834 36.2 55.0
region East Midlands 2102 50.1 18.3 529 70.0 1.6 2631 6.4 53.2
London 640 37.6 5.6 8277 107.9 25.7 8917 21.8 95.2
North East 671 59.9 5.8 1271 107.7 3.9 1942 4.7 84.4
North West 792 38.3 6.9 7932 116.8 24.6 8724 21.3 98.5
South East 1347 83.8 11.7 5837 82.4 18.1 7184 17.6 82.7
South West 1427 43.1 12.4 1928 78.9 6.0 3355 8.2 58.3
West Midlands 476 48.0 4.1 4517 90.5 14.0 4993 12.2 83.4
Yorkshire and The Humber 2133 62.0 18.5 1020 82.2 3.2 3153 7.7 67.3
imd Missing 262 44.6 2.3 75 76.0 0.2 337 0.8 49.1
Most deprived 1 2125 44.0 18.5 7312 105.8 22.7 9437 21.6 80.4
2 2250 47.7 19.6 7754 108.9 24.1 10004 22.9 84.5
3 2442 49.1 21.2 6139 94.3 19.0 8581 19.6 74.7
4 2261 48.3 19.7 5721 90.8 17.7 7982 18.2 72.7
Least deprived 5 2161 50.1 18.8 5238 79.9 16.2 7399 16.9 68.0
ethnicity Missing 2634 39.6 22.9 8212 75.5 25.5 10846 24.8 61.9
White 7382 50.4 64.2 18138 102.8 56.3 25520 58.3 79.1
Mixed 140 43.7 1.2 524 90.5 1.6 664 1.5 73.8
South Asian 986 65.7 8.6 3694 148.2 11.5 4680 10.7 117.2
Black 195 37.8 1.7 1233 105.5 3.8 1428 3.3 84.8
Other 164 34.5 1.4 438 58.3 1.4 602 1.4 49.1

Volume of code use in individual practices

Stratified by the electronic health record provider of the practice (TPP/SystmOne or EMIS).

Use of long COVID codes over time

Stratified by the electronic health record provider of the practice (TPP/SystmOne or EMIS). Reporting lag may affect recent dates.

This is distinct from the above table in that it counts all coded events, including where patients have been coded more than once.

There were 76,331 long COVID codes used in total. Counts for each software system were:

TPP     16,452.0
EMIS    60,026.0
Total   76,331.0
dtype: float64
TPP EMIS Total
term Total records % Total records % Total records %
code
1325161000000102 Post-COVID-19 syndrome 3,002.0 18.2 46,736.0 77.9 49,738.0 65.2
1325181000000106 Ongoing symptomatic disease caused by severe acute respiratory syndrome coronavirus 2 2,589.0 15.7 3,517.0 5.9 6,106.0 8.0
1325021000000106 Signposting to Your COVID Recovery 3,385.0 20.6 1,761.0 2.9 5,146.0 6.7
1325031000000108 Referral to post-COVID assessment clinic 3,239.0 19.7 6,380.0 10.6 9,619.0 12.6
1325041000000104 Referral to Your COVID Recovery rehabilitation platform 3,543.0 21.5 318.0 0.5 3,861.0 5.1
1325051000000101 Newcastle post-COVID syndrome Follow-up Screening Questionnaire 22.0 0.1 515.0 0.9 537.0 0.7
1325061000000103 Assessment using Newcastle post-COVID syndrome Follow-up Screening Questionnaire 30.0 0.2 230.0 0.4 260.0 0.3
1325071000000105 COVID-19 Yorkshire Rehabilitation Screening tool 196.0 1.2 242.0 0.4 438.0 0.6
1325081000000107 Assessment using COVID-19 Yorkshire Rehabilitation Screening tool 414.0 2.5 147.0 0.2 561.0 0.7
1325091000000109 Post-COVID-19 Functional Status Scale patient self-report nan nan 38.0 0.1 nan nan
1325101000000101 Assessment using Post-COVID-19 Functional Status Scale patient self-report nan nan 69.0 0.1 nan nan
1325121000000105 Post-COVID-19 Functional Status Scale patient self-report final scale grade nan nan 18.0 0.0 nan nan
1325131000000107 Post-COVID-19 Functional Status Scale structured interview final scale grade 0.0 0.0 nan nan nan nan
1325141000000103 Assessment using Post-COVID-19 Functional Status Scale structured interview 32.0 0.2 33.0 0.1 65.0 0.1
1325151000000100 Post-COVID-19 Functional Status Scale structured interview nan nan 22.0 0.0 nan nan

Characteristics of the cohort

This is equivalent to Table 1 in the paper

There were 57,604,767 people in the cohort in total. In practices that use TPP software, there were 24,106,715, while in practices that use EMIS software, there were 33,498,052 people.

TPP EMIS Totals
Patient count % Patient count % Patient count %
age_group 0-17 4839942 20.1 6809559 20.3 11649501 20.2
18-24 1907505 7.9 2810350 8.4 4717855 8.2
25-34 3348750 13.9 4836057 14.4 8184807 14.2
35-44 3230713 13.4 4670118 13.9 7900831 13.7
45-54 3244760 13.5 4494561 13.4 7739321 13.4
55-69 4222719 17.5 5635349 16.8 9858068 17.1
70-79 2092008 8.7 2670982 8.0 4762990 8.3
80+ 1220318 5.1 1571076 4.7 2791394 4.8
sex F 12052904 50.0 16740654 50.0 28793558 50.0
M 12053811 50.0 16757398 50.0 28811209 50.0
region East Midlands 4192331 17.4 755209 2.3 4947540 9.8
London 1700812 7.1 7667631 22.9 9368443 18.5
North East 1119823 4.6 1180482 3.5 2300305 4.5
North West 2067400 8.6 6788243 20.3 8855643 17.5
South East 1606770 6.7 7080996 21.1 8687766 17.2
South West 3308916 13.7 2443955 7.3 5752871 11.4
West Midlands 992257 4.1 4993534 14.9 5985791 11.8
Yorkshire and The Humber 3442158 14.3 1240398 3.7 4682556 9.3
imd Missing 587847 2.4 98704 0.3 686551 1.2
Most deprived 1 4825962 20.0 6912078 20.6 11738040 20.4
2 4717661 19.6 7122528 21.3 11840189 20.6
3 4975649 20.6 6507147 19.4 11482796 19.9
4 4684045 19.4 6298817 18.8 10982862 19.1
Least deprived 5 4315551 17.9 6558778 19.6 10874329 18.9
ethnicity Missing 6646638 27.6 10869822 32.4 17516460 30.4
White 14647551 60.8 17635728 52.6 32283279 56.0
Mixed 320225 1.3 579138 1.7 899363 1.6
South Asian 1500486 6.2 2493105 7.4 3993591 6.9
Black 515849 2.1 1168966 3.5 1684815 2.9
Other 475966 2.0 751293 2.2 1227259 2.1

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

Description
Descriptive analysis of the use of long-COVID codes in English primary care.
Authors
Alex J Walker, Brian MacKenna, Peter Inglesby, Laurie Tomlinson, Christopher T Rentsch, Helen J Curtis, Caroline E Morton, Jessica Morley, Amir Mehrkar, Seb Bacon, George Hickman, Chris Bates, Richard Croker, David Evans, Tom Ward, Jonathan Cockburn, Simon Davy, Krishnan Bhaskaran, Anna Schultze, Elizabeth J Williamson, William J Hulme, Helen I McDonald, Rohini Mathur, Rosalind M Eggo, Kevin Wing, Angel YS Wong, Harriet Forbes, John Tazare, John Parry, Frank Hester, Sam Harper, Shaun O’Hanlon, Alex Eavis, Richard Jarvis, Dima Avramov, Paul Griffiths, Aaron Fowles, Nasreen Parkes, Ian J Douglas, Stephen JW Evans, Liam Smeeth, Ben Goldacre and (The OpenSAFELY Collaborative)
Contact
Get in touch and tell us how you use this report or new features you'd like to see: [email protected]
First published
03 Aug 2021
Last updated
19 Aug 2021

Long COVID coding in primary care.

This OpenSAFELY report is a routine update of our peer-review paper published in the British Journal of General Practice on the Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY.

It is a routine update of the analysis described in the paper. The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussionis and the full analytical methods on this routine report are available on GitHub.

OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. You can read more about OpenSAFELY on our website.

Report last updated 19 Aug 2021

Results

Counts and rates of long COVID coding stratified by demographic variable

This is equivalent to Table 2 from the paper

There were 43,740 people who have been given a diagnostic code for long COVID to date. Counts for each software system are:

TPP      11,501.0
EMIS     32,239.0
Totals   43,740.0
dtype: float64

The overall rate of long COVID coding in the population was 152 per 100,000 people. Rates for each software system are:

TPP       95.4
EMIS     192.5
Totals   151.9
dtype: float64
TPP EMIS Totals
Long COVID Rate per 100,000 % Long COVID Rate per 100,000 % Long COVID % Rate per 100,000
age_group 0-17 273 5.6 2.4 766 11.2 2.4 1039 2.4 8.9
18-24 685 35.9 6.0 1410 50.2 4.4 2095 4.8 44.4
25-34 1514 45.2 13.2 4152 85.9 12.9 5666 13.0 69.2
35-44 2326 72.0 20.2 7122 152.5 22.1 9448 21.6 119.6
45-54 3024 93.2 26.3 8694 193.4 27.0 11718 26.8 151.4
55-69 2952 69.9 25.7 8406 149.2 26.1 11358 26.0 115.2
70-79 532 25.4 4.6 1299 48.6 4.0 1831 4.2 38.4
80+ 195 16.0 1.7 390 24.8 1.2 585 1.3 21.0
sex F 7266 60.3 63.2 20640 123.3 64.0 27906 63.8 96.9
M 4235 35.1 36.8 11599 69.2 36.0 15834 36.2 55.0
region East Midlands 2102 50.1 18.3 529 70.0 1.6 2631 6.4 53.2
London 640 37.6 5.6 8277 107.9 25.7 8917 21.8 95.2
North East 671 59.9 5.8 1271 107.7 3.9 1942 4.7 84.4
North West 792 38.3 6.9 7932 116.8 24.6 8724 21.3 98.5
South East 1347 83.8 11.7 5837 82.4 18.1 7184 17.6 82.7
South West 1427 43.1 12.4 1928 78.9 6.0 3355 8.2 58.3
West Midlands 476 48.0 4.1 4517 90.5 14.0 4993 12.2 83.4
Yorkshire and The Humber 2133 62.0 18.5 1020 82.2 3.2 3153 7.7 67.3
imd Missing 262 44.6 2.3 75 76.0 0.2 337 0.8 49.1
Most deprived 1 2125 44.0 18.5 7312 105.8 22.7 9437 21.6 80.4
2 2250 47.7 19.6 7754 108.9 24.1 10004 22.9 84.5
3 2442 49.1 21.2 6139 94.3 19.0 8581 19.6 74.7
4 2261 48.3 19.7 5721 90.8 17.7 7982 18.2 72.7
Least deprived 5 2161 50.1 18.8 5238 79.9 16.2 7399 16.9 68.0
ethnicity Missing 2634 39.6 22.9 8212 75.5 25.5 10846 24.8 61.9
White 7382 50.4 64.2 18138 102.8 56.3 25520 58.3 79.1
Mixed 140 43.7 1.2 524 90.5 1.6 664 1.5 73.8
South Asian 986 65.7 8.6 3694 148.2 11.5 4680 10.7 117.2
Black 195 37.8 1.7 1233 105.5 3.8 1428 3.3 84.8
Other 164 34.5 1.4 438 58.3 1.4 602 1.4 49.1

Volume of code use in individual practices

Stratified by the electronic health record provider of the practice (TPP/SystmOne or EMIS).

Use of long COVID codes over time

Stratified by the electronic health record provider of the practice (TPP/SystmOne or EMIS). Reporting lag may affect recent dates.

This is distinct from the above table in that it counts all coded events, including where patients have been coded more than once.

There were 76,331 long COVID codes used in total. Counts for each software system were:

TPP     16,452.0
EMIS    60,026.0
Total   76,331.0
dtype: float64
TPP EMIS Total
term Total records % Total records % Total records %
code
1325161000000102 Post-COVID-19 syndrome 3,002.0 18.2 46,736.0 77.9 49,738.0 65.2
1325181000000106 Ongoing symptomatic disease caused by severe acute respiratory syndrome coronavirus 2 2,589.0 15.7 3,517.0 5.9 6,106.0 8.0
1325021000000106 Signposting to Your COVID Recovery 3,385.0 20.6 1,761.0 2.9 5,146.0 6.7
1325031000000108 Referral to post-COVID assessment clinic 3,239.0 19.7 6,380.0 10.6 9,619.0 12.6
1325041000000104 Referral to Your COVID Recovery rehabilitation platform 3,543.0 21.5 318.0 0.5 3,861.0 5.1
1325051000000101 Newcastle post-COVID syndrome Follow-up Screening Questionnaire 22.0 0.1 515.0 0.9 537.0 0.7
1325061000000103 Assessment using Newcastle post-COVID syndrome Follow-up Screening Questionnaire 30.0 0.2 230.0 0.4 260.0 0.3
1325071000000105 COVID-19 Yorkshire Rehabilitation Screening tool 196.0 1.2 242.0 0.4 438.0 0.6
1325081000000107 Assessment using COVID-19 Yorkshire Rehabilitation Screening tool 414.0 2.5 147.0 0.2 561.0 0.7
1325091000000109 Post-COVID-19 Functional Status Scale patient self-report nan nan 38.0 0.1 nan nan
1325101000000101 Assessment using Post-COVID-19 Functional Status Scale patient self-report nan nan 69.0 0.1 nan nan
1325121000000105 Post-COVID-19 Functional Status Scale patient self-report final scale grade nan nan 18.0 0.0 nan nan
1325131000000107 Post-COVID-19 Functional Status Scale structured interview final scale grade 0.0 0.0 nan nan nan nan
1325141000000103 Assessment using Post-COVID-19 Functional Status Scale structured interview 32.0 0.2 33.0 0.1 65.0 0.1
1325151000000100 Post-COVID-19 Functional Status Scale structured interview nan nan 22.0 0.0 nan nan

Characteristics of the cohort

This is equivalent to Table 1 in the paper

There were 57,604,767 people in the cohort in total. In practices that use TPP software, there were 24,106,715, while in practices that use EMIS software, there were 33,498,052 people.

TPP EMIS Totals
Patient count % Patient count % Patient count %
age_group 0-17 4839942 20.1 6809559 20.3 11649501 20.2
18-24 1907505 7.9 2810350 8.4 4717855 8.2
25-34 3348750 13.9 4836057 14.4 8184807 14.2
35-44 3230713 13.4 4670118 13.9 7900831 13.7
45-54 3244760 13.5 4494561 13.4 7739321 13.4
55-69 4222719 17.5 5635349 16.8 9858068 17.1
70-79 2092008 8.7 2670982 8.0 4762990 8.3
80+ 1220318 5.1 1571076 4.7 2791394 4.8
sex F 12052904 50.0 16740654 50.0 28793558 50.0
M 12053811 50.0 16757398 50.0 28811209 50.0
region East Midlands 4192331 17.4 755209 2.3 4947540 9.8
London 1700812 7.1 7667631 22.9 9368443 18.5
North East 1119823 4.6 1180482 3.5 2300305 4.5
North West 2067400 8.6 6788243 20.3 8855643 17.5
South East 1606770 6.7 7080996 21.1 8687766 17.2
South West 3308916 13.7 2443955 7.3 5752871 11.4
West Midlands 992257 4.1 4993534 14.9 5985791 11.8
Yorkshire and The Humber 3442158 14.3 1240398 3.7 4682556 9.3
imd Missing 587847 2.4 98704 0.3 686551 1.2
Most deprived 1 4825962 20.0 6912078 20.6 11738040 20.4
2 4717661 19.6 7122528 21.3 11840189 20.6
3 4975649 20.6 6507147 19.4 11482796 19.9
4 4684045 19.4 6298817 18.8 10982862 19.1
Least deprived 5 4315551 17.9 6558778 19.6 10874329 18.9
ethnicity Missing 6646638 27.6 10869822 32.4 17516460 30.4
White 14647551 60.8 17635728 52.6 32283279 56.0
Mixed 320225 1.3 579138 1.7 899363 1.6
South Asian 1500486 6.2 2493105 7.4 3993591 6.9
Black 515849 2.1 1168966 3.5 1684815 2.9
Other 475966 2.0 751293 2.2 1227259 2.1