Literature DB >> 32295793

To monitor the COVID-19 pandemic we need better quality primary care data.

Simon de Lusignan1, John Williams2.   

Abstract

Entities:  

Keywords:  Practice organisation; coronavirus; general practice; primary healthcare

Year:  2020        PMID: 32295793      PMCID: PMC7330216          DOI: 10.3399/bjgpopen20X101070

Source DB:  PubMed          Journal:  BJGP Open        ISSN: 2398-3795


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​UK primary care coding of covid-19 is a mess: we need to stop the use of bad codes, and migrate from the use of ugly to good codes, but will only be able to do so when they are finally released . Key data computerised medical record (CMR) systems are recorded using ’codes’, to standardise recording and so attendances about a medical problem can be linked.[1] At the start of the COVID-19 pandemic there was neither international agreement about nomenclature nor codes available in primary care CMRs with which to record exposure, testing, or infection. We have now been through three iterations of clinical codes in the UK since the end of January. Five temporary codes were added to all the primary care CMR systems using the ‘2019 nCoV (Wuhan)’ label in January 2020. Subsequently NHS Digital, the NHS coding organisation, released a more extensive set of SNOMED CT concepts named ‘2019 nCoV (novel coronavirus)’ because the use of ‘Wuhan’ had been deprecated; these codes were in turn replaced by ‘SARS –CoV-2 (severe acute respiratory syndrome coronavirus 2)’ [2] The situation has been further complicated by the fact that this last release is only now starting to become available in CMRs (Table 1), and because some clinicians have gone back to using old non-specific coronavirus codes (such as ‘ Suspected Coronavirus infection: 1JX ’, and ‘ Coronavirus infection: A795 ’).
Table 1.

Clinical concepts that should be coded, temporary and definitive codes

Clinical concepts that should be coded in CMR Temporary codes Go on using until replaced by SARS-Cov-2 Final SNOMED CT descriptionRoll-out taking place during April 2020
Exposure to COVID-19Exposure to 2019 nCoV (Wuhan) infection or Exposure to SARS-CoV-2 infection
Exposure to 2019 nCoV (novel coronavirus) infection
Suspected COVID-19 infectionSuspected 2019 nCoV (Wuhan) infection or Suspected COVID-19
Suspected 2019 nCoV (novel coronavirus) infection
Test for COVID-19 offered or taken No specific codes Swab for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) taken by healthcare professional
Self-taken swab for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) offered
Self-taken swab for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) completed
Tested for 2019 nCoV (Wuhan) infection or
Tested for 2019 nCoV (novel coronavirus) infection
COVID-19 definite caseConfirmed 2019 nCoV (Wuhan) infection or COVID-19
Confirmed 2019 nCoV (novel coronavirus) infection
COVID-19 excludedExcluded 2019 nCoV (Wuhan) infection or COVID-19 excluded
Excluded 2019 nCoV (novel coronavirus) infection
Laboratory test codes
COVID-19 confirmed by lab testCOVID-19 confirmed by laboratory test
COVID-19 excluded by lab testCOVID-19 excluded by laboratory test
COVID-19 virus detected2019-nCoV (novel coronavirus) detectedSARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) detected
COVID-19 virus not detected2019-nCoV (novel coronavirus) not detectedSARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) not detected

CMR = computerised medical record.

CMR = computerised medical record. This creates challenges for the surveillance system and others monitoring the pandemic.[3] We have previously classified the incorrect use of codes as miscoding, misclassification, or misdiagnosis.[4] In the cases of COVID-19, we are seeing[1] both Miscoding (that is, continued use of the temporary codes, which should stop once the new ones are available);[2] and Misclassification (use of non-specific coronavirus codes), which should stop. Table 1 sets out the clinical concept we currently need to consistently record in primary care, the temporary codes available to do this, and the final codes we should all eventually use. Prompt cards to help clinicians and coders are available at: https://clininf.eu/index.php/cov-19/ All UK primary care clinicians and coders are recommended to continue to use the temporary codes until the new ones are available, then switch. Accurate data is a key to understanding and monitoring the course of this pandemic. Appendix: Examples of codes not to use Exposure to coronavirus infection Suspected coronavirus infection Coronavirus infection Disease due to Coronaviridae Coronavirus contact
  4 in total

1.  Codes, classifications, terminologies and nomenclatures: definition, development and application in practice.

Authors:  Simon de Lusignan
Journal:  Inform Prim Care       Date:  2005

2.  Miscoding, misclassification and misdiagnosis of diabetes in primary care.

Authors:  S de Lusignan; N Sadek; H Mulnier; A Tahir; D Russell-Jones; K Khunti
Journal:  Diabet Med       Date:  2012-02       Impact factor: 4.359

3.  The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2.

Authors: 
Journal:  Nat Microbiol       Date:  2020-03-02       Impact factor: 17.745

4.  Emergence of a Novel Coronavirus (COVID-19): Protocol for Extending Surveillance Used by the Royal College of General Practitioners Research and Surveillance Centre and Public Health England.

Authors:  Simon de Lusignan; Jamie Lopez Bernal; Maria Zambon; Oluwafunmi Akinyemi; Gayatri Amirthalingam; Nick Andrews; Ray Borrow; Rachel Byford; André Charlett; Gavin Dabrera; Joanna Ellis; Alex J Elliot; Michael Feher; Filipa Ferreira; Else Krajenbrink; Jonathan Leach; Ezra Linley; Harshana Liyanage; Cecilia Okusi; Mary Ramsay; Gillian Smith; Julian Sherlock; Nicholas Thomas; Manasa Tripathy; John Williams; Gary Howsam; Mark Joy; Richard Hobbs
Journal:  JMIR Public Health Surveill       Date:  2020-04-02
  4 in total
  7 in total

1.  Managing COVID-19 within and across health systems: why we need performance intelligence to coordinate a global response.

Authors:  D Kringos; F Carinci; E Barbazza; V Bos; K Gilmore; O Groene; L Gulácsi; D Ivankovic; T Jansen; S P Johnsen; S de Lusignan; J Mainz; S Nuti; N Klazinga
Journal:  Health Res Policy Syst       Date:  2020-07-14

2.  Excess mortality in the first COVID pandemic peak: cross-sectional analyses of the impact of age, sex, ethnicity, household size, and long-term conditions in people of known SARS-CoV-2 status in England.

Authors:  Mark Joy; Fd Richard Hobbs; Jamie Lopez Bernal; Julian Sherlock; Gayatri Amirthalingam; Dylan McGagh; Oluwafunmi Akinyemi; Rachel Byford; Gavin Dabrera; Jienchi Dorward; Joanna Ellis; Filipa Ferreira; Nicholas Jones; Jason Oke; Cecilia Okusi; Brian D Nicholson; Mary Ramsay; James P Sheppard; Mary Sinnathamby; Maria Zambon; Gary Howsam; John Williams; Simon de Lusignan
Journal:  Br J Gen Pract       Date:  2020-11-26       Impact factor: 5.386

3.  Regional COVID-19 registry in Khuzestan, Iran: A study protocol and lessons learned from a pilot implementation.

Authors:  Javad Zarei; Maryam Dastoorpoor; Amir Jamshidnezhad; Maria Cheraghi; Abbas Sheikhtaheri
Journal:  Inform Med Unlocked       Date:  2021-01-19

4.  Investigating the uptake, effectiveness and safety of COVID-19 vaccines: protocol for an observational study using linked UK national data.

Authors:  Eleftheria Vasileiou; Ting Shi; Steven Kerr; Chris Robertson; Mark Joy; Ruby Tsang; Dylan McGagh; John Williams; Richard Hobbs; Simon de Lusignan; Declan Bradley; Dermot OReilly; Siobhan Murphy; Antony Chuter; Jillian Beggs; David Ford; Chris Orton; Ashley Akbari; Stuart Bedston; Gareth Davies; Lucy J Griffiths; Rowena Griffiths; Emily Lowthian; Jane Lyons; Ronan A Lyons; Laura North; Malorie Perry; Fatemeh Torabi; James Pickett; Jim McMenamin; Colin McCowan; Utkarsh Agrawal; Rachael Wood; Sarah Jane Stock; Emily Moore; Paul Henery; Colin R Simpson; Aziz Sheikh
Journal:  BMJ Open       Date:  2022-02-14       Impact factor: 3.006

5.  Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study.

Authors:  Bernardo Meza-Torres; Gayathri Delanerolle; Cecilia Okusi; Nikhil Mayor; Sneha Anand; Jack Macartney; Piers Gatenby; Ben Glampson; Martin Chapman; Vasa Curcin; Erik Mayer; Mark Joy; Trisha Greenhalgh; Brendan Delaney; Simon de Lusignan
Journal:  JMIR Public Health Surveill       Date:  2022-08-16

6.  Establishing the impact of COVID-19 on the health outcomes of domiciliary care workers in Wales using routine data: a protocol for the OSCAR study.

Authors:  Fiona Lugg-Widger; Rebecca Cannings-John; Ashley Akbari; Lucy Brookes-Howell; Kerenza Hood; Ann John; Hywel Jones; Hayley Prout; Simon Schoenbuchner; Daniel Thomas; Michael Robling
Journal:  Int J Popul Data Sci       Date:  2021-07-14

7.  COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology.

Authors:  Dylan McGagh; Simon de Lusignan; Harshana Liyanage; Bhautesh Dinesh Jani; Jorgen Bauwens; Rachel Byford; Dai Evans; Tom Fahey; Trisha Greenhalgh; Nicholas Jones; Frances S Mair; Cecilia Okusi; Vaishnavi Parimalanathan; Jill P Pell; Julian Sherlock; Oscar Tamburis; Manasa Tripathy; Filipa Ferreira; John Williams; F D Richard Hobbs
Journal:  JMIR Public Health Surveill       Date:  2020-11-17
  7 in total

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