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
01 Oct 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.

Results

Counts and rates of long COVID coding stratified by demographic variable

This is equivalent to Table 2 from the paper

There were 57,100 people who have been given a diagnostic code for long COVID to date. Counts for each software system are:

TPP      15,227.0
EMIS     41,873.0
Totals   57,100.0
dtype: float64

The overall rate of long COVID coding in the population was 99.6 per 100,000 people. Rates for each software system are:

TPP       63.1
EMIS     126.0
Totals    99.6
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 0-17 397 8.2 2.6 1152 17.0 2.8 1549 2.7 13.3
18-24 924 48.4 6.1 2287 82.4 5.5 3211 5.6 68.6
25-34 2011 60.0 13.2 5892 123.2 14.1 7903 13.8 97.1
35-44 3104 96.0 20.4 9102 196.3 21.7 12206 21.4 155.1
45-54 3931 121.0 25.8 10833 242.4 25.9 14764 25.9 191.3
55-69 3914 92.6 25.7 10393 185.4 24.8 14307 25.1 145.5
70-79 706 33.7 4.6 1677 63.1 4.0 2383 4.2 50.1
80+ 240 19.6 1.6 537 34.4 1.3 777 1.4 27.9
sex F 9638 79.9 63.3 26462 159.3 63.2 36100 63.2 125.9
M 5589 46.3 36.7 15411 92.6 36.8 21000 36.8 73.2
region East of England 2677 47.2 17.6 1138 87.5 2.7 3815 6.7 54.8
East Midlands 2717 64.8 17.8 661 88.0 1.6 3378 5.9 68.3
London 873 51.3 5.7 10332 136.1 24.7 11205 19.6 120.6
North East 861 76.2 5.7 1646 141.2 3.9 2507 4.4 109.2
North West 1173 56.5 7.7 10517 156.1 25.1 11690 20.5 132.6
South East 1622 100.9 10.7 7056 100.3 16.9 8678 15.2 100.4
South West 1951 58.9 12.8 2413 99.3 5.8 4364 7.7 76.0
West Midlands 605 61.0 4.0 6740 135.9 16.1 7345 12.9 123.4
Yorkshire and The Humber 2743 79.6 18.0 1302 106.9 3.1 4045 7.1 86.7
imd Missing 351 59.6 2.3 145 123.4 0.3 496 0.9 70.2
Most deprived 1 2828 58.5 18.6 9854 143.8 23.5 12682 22.2 108.5
2 2960 62.6 19.4 9843 139.4 23.5 12803 22.4 108.6
3 3229 64.8 21.2 7981 123.7 19.1 11210 19.6 98.0
4 3049 65.1 20.0 7403 118.4 17.7 10452 18.3 95.5
Least deprived 5 2810 65.1 18.5 6647 102.0 15.9 9457 16.6 87.3
ethnicity Missing 3443 51.8 22.6 10955 100.6 26.2 14398 25.2 82.1
White 9855 67.2 64.7 23489 134.8 56.1 33344 58.4 103.9
Mixed 181 56.5 1.2 692 121.2 1.7 873 1.5 97.9
South Asian 1271 84.6 8.3 4561 185.2 10.9 5832 10.2 147.1
Black 275 53.3 1.8 1603 138.8 3.8 1878 3.3 112.4
Other 202 42.4 1.3 573 77.3 1.4 775 1.4 63.6

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 100,241 long COVID codes used in total. Counts for each software system were:

TPP      22,705.0
EMIS     77,644.0
Total   100,241.0
dtype: float64
TPP EMIS Total
term Total records % Total records % Total records %
code
1325161000000102 Post-COVID-19 syndrome 4,295.0 18.9 56,598.0 72.9 60,893.0 60.7
1325181000000106 Ongoing symptomatic disease caused by severe acute respiratory syndrome coronavirus 2 3,526.0 15.5 6,428.0 8.3 9,954.0 9.9
1325021000000106 Signposting to Your COVID Recovery 4,326.0 19.1 3,658.0 4.7 7,984.0 8.0
1325031000000108 Referral to post-COVID assessment clinic 5,508.0 24.3 8,366.0 10.8 13,874.0 13.8
1325041000000104 Referral to Your COVID Recovery rehabilitation platform 4,115.0 18.1 965.0 1.2 5,080.0 5.1
1325051000000101 Newcastle post-COVID syndrome Follow-up Screening Questionnaire 36.0 0.2 599.0 0.8 635.0 0.6
1325061000000103 Assessment using Newcastle post-COVID syndrome Follow-up Screening Questionnaire 41.0 0.2 346.0 0.4 387.0 0.4
1325071000000105 COVID-19 Yorkshire Rehabilitation Screening tool 271.0 1.2 297.0 0.4 568.0 0.6
1325081000000107 Assessment using COVID-19 Yorkshire Rehabilitation Screening tool 543.0 2.4 177.0 0.2 720.0 0.7
1325091000000109 Post-COVID-19 Functional Status Scale patient self-report 6.0 0.0 37.0 0.0 43.0 0.0
1325101000000101 Assessment using Post-COVID-19 Functional Status Scale patient self-report nan nan 89.0 0.1 nan nan
1325121000000105 Post-COVID-19 Functional Status Scale patient self-report final scale grade nan nan 19.0 0.0 nan nan
1325131000000107 Post-COVID-19 Functional Status Scale structured interview final scale grade 0.0 0.0 6.0 0.0 6.0 0.0
1325141000000103 Assessment using Post-COVID-19 Functional Status Scale structured interview 32.0 0.1 36.0 0.0 68.0 0.1
1325151000000100 Post-COVID-19 Functional Status Scale structured interview 6.0 0.0 23.0 0.0 29.0 0.0

Characteristics of the cohort

This is equivalent to Table 1 in the paper

There were 57,386,436 people in the cohort in total. In practices that use TPP software, there were 24,135,847, while in practices that use EMIS software, there were 33,250,589 people.

TPP EMIS Totals
Patient count % Patient count % Patient count %
age_group 0-17 4845926 20.1 6763374 20.3 11609300 20.2
18-24 1909531 7.9 2774065 8.3 4683596 8.2
25-34 3352407 13.9 4782922 14.4 8135329 14.2
35-44 3234539 13.4 4636335 13.9 7870874 13.7
45-54 3248911 13.5 4468675 13.4 7717586 13.4
55-69 4228098 17.5 5605840 16.9 9833938 17.1
70-79 2094836 8.7 2658387 8.0 4753223 8.3
80+ 1221599 5.1 1560991 4.7 2782590 4.8
sex F 12067467 50.0 16610913 50.0 28678380 50.0
M 12068380 50.0 16639676 50.0 28708056 50.0
region East of England 5667724 23.5 1300151 3.9 6967875 12.2
East Midlands 4192354 17.4 751112 2.3 4943466 8.6
London 1701424 7.1 7591334 22.8 9292758 16.2
North East 1129913 4.7 1166122 3.5 2296035 4.0
North West 2075934 8.6 6739187 20.3 8815121 15.4
South East 1606811 6.7 7034051 21.2 8640862 15.1
South West 3311902 13.7 2430307 7.3 5742209 10.0
West Midlands 992568 4.1 4959297 14.9 5951865 10.4
Yorkshire and The Humber 3448044 14.3 1218234 3.7 4666278 8.1
imd Missing 588668 2.4 117473 0.4 706141 1.2
Most deprived 1 4833444 20.0 6852326 20.6 11685770 20.4
2 4725935 19.6 7058459 21.2 11784394 20.5
3 4983121 20.6 6453336 19.4 11436457 19.9
4 4686901 19.4 6253825 18.8 10940726 19.1
Least deprived 5 4317778 17.9 6515170 19.6 10832948 18.9
ethnicity Missing 6652486 27.6 10893716 32.8 17546202 30.6
White 14668443 60.8 17427723 52.4 32096166 55.9
Mixed 320435 1.3 570855 1.7 891290 1.6
South Asian 1501928 6.2 2462184 7.4 3964112 6.9
Black 516238 2.1 1154510 3.5 1670748 2.9
Other 476317 2.0 741601 2.2 1217918 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
01 Oct 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.

Results

Counts and rates of long COVID coding stratified by demographic variable

This is equivalent to Table 2 from the paper

There were 57,100 people who have been given a diagnostic code for long COVID to date. Counts for each software system are:

TPP      15,227.0
EMIS     41,873.0
Totals   57,100.0
dtype: float64

The overall rate of long COVID coding in the population was 99.6 per 100,000 people. Rates for each software system are:

TPP       63.1
EMIS     126.0
Totals    99.6
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 0-17 397 8.2 2.6 1152 17.0 2.8 1549 2.7 13.3
18-24 924 48.4 6.1 2287 82.4 5.5 3211 5.6 68.6
25-34 2011 60.0 13.2 5892 123.2 14.1 7903 13.8 97.1
35-44 3104 96.0 20.4 9102 196.3 21.7 12206 21.4 155.1
45-54 3931 121.0 25.8 10833 242.4 25.9 14764 25.9 191.3
55-69 3914 92.6 25.7 10393 185.4 24.8 14307 25.1 145.5
70-79 706 33.7 4.6 1677 63.1 4.0 2383 4.2 50.1
80+ 240 19.6 1.6 537 34.4 1.3 777 1.4 27.9
sex F 9638 79.9 63.3 26462 159.3 63.2 36100 63.2 125.9
M 5589 46.3 36.7 15411 92.6 36.8 21000 36.8 73.2
region East of England 2677 47.2 17.6 1138 87.5 2.7 3815 6.7 54.8
East Midlands 2717 64.8 17.8 661 88.0 1.6 3378 5.9 68.3
London 873 51.3 5.7 10332 136.1 24.7 11205 19.6 120.6
North East 861 76.2 5.7 1646 141.2 3.9 2507 4.4 109.2
North West 1173 56.5 7.7 10517 156.1 25.1 11690 20.5 132.6
South East 1622 100.9 10.7 7056 100.3 16.9 8678 15.2 100.4
South West 1951 58.9 12.8 2413 99.3 5.8 4364 7.7 76.0
West Midlands 605 61.0 4.0 6740 135.9 16.1 7345 12.9 123.4
Yorkshire and The Humber 2743 79.6 18.0 1302 106.9 3.1 4045 7.1 86.7
imd Missing 351 59.6 2.3 145 123.4 0.3 496 0.9 70.2
Most deprived 1 2828 58.5 18.6 9854 143.8 23.5 12682 22.2 108.5
2 2960 62.6 19.4 9843 139.4 23.5 12803 22.4 108.6
3 3229 64.8 21.2 7981 123.7 19.1 11210 19.6 98.0
4 3049 65.1 20.0 7403 118.4 17.7 10452 18.3 95.5
Least deprived 5 2810 65.1 18.5 6647 102.0 15.9 9457 16.6 87.3
ethnicity Missing 3443 51.8 22.6 10955 100.6 26.2 14398 25.2 82.1
White 9855 67.2 64.7 23489 134.8 56.1 33344 58.4 103.9
Mixed 181 56.5 1.2 692 121.2 1.7 873 1.5 97.9
South Asian 1271 84.6 8.3 4561 185.2 10.9 5832 10.2 147.1
Black 275 53.3 1.8 1603 138.8 3.8 1878 3.3 112.4
Other 202 42.4 1.3 573 77.3 1.4 775 1.4 63.6

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 100,241 long COVID codes used in total. Counts for each software system were:

TPP      22,705.0
EMIS     77,644.0
Total   100,241.0
dtype: float64
TPP EMIS Total
term Total records % Total records % Total records %
code
1325161000000102 Post-COVID-19 syndrome 4,295.0 18.9 56,598.0 72.9 60,893.0 60.7
1325181000000106 Ongoing symptomatic disease caused by severe acute respiratory syndrome coronavirus 2 3,526.0 15.5 6,428.0 8.3 9,954.0 9.9
1325021000000106 Signposting to Your COVID Recovery 4,326.0 19.1 3,658.0 4.7 7,984.0 8.0
1325031000000108 Referral to post-COVID assessment clinic 5,508.0 24.3 8,366.0 10.8 13,874.0 13.8
1325041000000104 Referral to Your COVID Recovery rehabilitation platform 4,115.0 18.1 965.0 1.2 5,080.0 5.1
1325051000000101 Newcastle post-COVID syndrome Follow-up Screening Questionnaire 36.0 0.2 599.0 0.8 635.0 0.6
1325061000000103 Assessment using Newcastle post-COVID syndrome Follow-up Screening Questionnaire 41.0 0.2 346.0 0.4 387.0 0.4
1325071000000105 COVID-19 Yorkshire Rehabilitation Screening tool 271.0 1.2 297.0 0.4 568.0 0.6
1325081000000107 Assessment using COVID-19 Yorkshire Rehabilitation Screening tool 543.0 2.4 177.0 0.2 720.0 0.7
1325091000000109 Post-COVID-19 Functional Status Scale patient self-report 6.0 0.0 37.0 0.0 43.0 0.0
1325101000000101 Assessment using Post-COVID-19 Functional Status Scale patient self-report nan nan 89.0 0.1 nan nan
1325121000000105 Post-COVID-19 Functional Status Scale patient self-report final scale grade nan nan 19.0 0.0 nan nan
1325131000000107 Post-COVID-19 Functional Status Scale structured interview final scale grade 0.0 0.0 6.0 0.0 6.0 0.0
1325141000000103 Assessment using Post-COVID-19 Functional Status Scale structured interview 32.0 0.1 36.0 0.0 68.0 0.1
1325151000000100 Post-COVID-19 Functional Status Scale structured interview 6.0 0.0 23.0 0.0 29.0 0.0

Characteristics of the cohort

This is equivalent to Table 1 in the paper

There were 57,386,436 people in the cohort in total. In practices that use TPP software, there were 24,135,847, while in practices that use EMIS software, there were 33,250,589 people.

TPP EMIS Totals
Patient count % Patient count % Patient count %
age_group 0-17 4845926 20.1 6763374 20.3 11609300 20.2
18-24 1909531 7.9 2774065 8.3 4683596 8.2
25-34 3352407 13.9 4782922 14.4 8135329 14.2
35-44 3234539 13.4 4636335 13.9 7870874 13.7
45-54 3248911 13.5 4468675 13.4 7717586 13.4
55-69 4228098 17.5 5605840 16.9 9833938 17.1
70-79 2094836 8.7 2658387 8.0 4753223 8.3
80+ 1221599 5.1 1560991 4.7 2782590 4.8
sex F 12067467 50.0 16610913 50.0 28678380 50.0
M 12068380 50.0 16639676 50.0 28708056 50.0
region East of England 5667724 23.5 1300151 3.9 6967875 12.2
East Midlands 4192354 17.4 751112 2.3 4943466 8.6
London 1701424 7.1 7591334 22.8 9292758 16.2
North East 1129913 4.7 1166122 3.5 2296035 4.0
North West 2075934 8.6 6739187 20.3 8815121 15.4
South East 1606811 6.7 7034051 21.2 8640862 15.1
South West 3311902 13.7 2430307 7.3 5742209 10.0
West Midlands 992568 4.1 4959297 14.9 5951865 10.4
Yorkshire and The Humber 3448044 14.3 1218234 3.7 4666278 8.1
imd Missing 588668 2.4 117473 0.4 706141 1.2
Most deprived 1 4833444 20.0 6852326 20.6 11685770 20.4
2 4725935 19.6 7058459 21.2 11784394 20.5
3 4983121 20.6 6453336 19.4 11436457 19.9
4 4686901 19.4 6253825 18.8 10940726 19.1
Least deprived 5 4317778 17.9 6515170 19.6 10832948 18.9
ethnicity Missing 6652486 27.6 10893716 32.8 17546202 30.6
White 14668443 60.8 17427723 52.4 32096166 55.9
Mixed 320435 1.3 570855 1.7 891290 1.6
South Asian 1501928 6.2 2462184 7.4 3964112 6.9
Black 516238 2.1 1154510 3.5 1670748 2.9
Other 476317 2.0 741601 2.2 1217918 2.1