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OpenSAFELY NHS Service Restoration Observatory 2: changes in primary care clinical activity in England during the COVID-19 pandemic.
Curtis, Helen J; MacKenna, Brian; Wiedemann, Milan; Fisher, Louis; Croker, Richard; Morton, Caroline E; Inglesby, Peter; Walker, Alex J; Morley, Jessica; Mehrkar, Amir; Bacon, Sebastian Cj; Hickman, George; Evans, David; Ward, Tom; Davy, Simon; Hulme, William J; Macdonald, Orla; Conibere, Robin; Lewis, Tom; Myers, Martin; Wanninayake, Shamila; Collison, Kiren; Drury, Charles; Samuel, Miriam; Sood, Harpreet; Cipriani, Andrea; Fazel, Seena; Sharma, Manuj; Baqir, Wasim; Bates, Chris; Parry, John; Goldacre, Ben.
Afiliação
  • Curtis HJ; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • MacKenna B; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Wiedemann M; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Fisher L; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Croker R; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Morton CE; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Inglesby P; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Walker AJ; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Morley J; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Mehrkar A; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Bacon SC; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Hickman G; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Evans D; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Ward T; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Davy S; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Hulme WJ; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Macdonald O; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
  • Conibere R; Beacon Medical Group, Plymouth.
  • Lewis T; Royal Devon University Healthcare NHS Foundation Trust, Barnstaple.
  • Myers M; Lancashire Teaching Hospitals NHS Foundation Trust, Preston.
  • Wanninayake S; The Manor Surgery, Oxford.
  • Collison K; NHS England and NHS Improvement, London.
  • Drury C; Herefordshire and Worcestershire Health and Care NHS Trust, Worcester.
  • Samuel M; Wolfson Institute of Population Health, Queen Mary University of London, London.
  • Sood H; University College London Hospitals NHS Foundation Trust, London.
  • Cipriani A; Department of Psychiatry, University of Oxford, Oxford.
  • Fazel S; Department of Psychiatry, University of Oxford, Oxford.
  • Sharma M; Department of Primary Care and Population Health, University College London, London.
  • Baqir W; NHS England and NHS Improvement, London.
  • Bates C; TPP, Leeds.
  • Parry J; TPP, Leeds.
  • Goldacre B; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford.
Br J Gen Pract ; 73(730): e318-e331, 2023 05.
Article em En | MEDLINE | ID: mdl-37068964
ABSTRACT

BACKGROUND:

The COVID-19 pandemic has disrupted healthcare activity across a broad range of clinical services. The NHS stopped non-urgent work in March 2020, later recommending services be restored to near-normal levels before winter where possible.

AIM:

To describe changes in the volume and variation of coded clinical activity in general practice across six clinical areas cardiovascular disease, diabetes, mental health, female and reproductive health, screening and related procedures, and processes related to medication. DESIGN AND

SETTING:

With the approval of NHS England, a cohort study was conducted of 23.8 million patient records in general practice, in situ using OpenSAFELY.

METHOD:

Common primary care activities were analysed using Clinical Terms Version 3 codes and keyword searches from January 2019 to December 2020, presenting median and deciles of code usage across practices per month.

RESULTS:

Substantial and widespread changes in clinical activity in primary care were identified since the onset of the COVID-19 pandemic, with generally good recovery by December 2020. A few exceptions showed poor recovery and warrant further investigation, such as mental health (for example, for 'Depression interim review' the median occurrences across practices in December 2020 was down by 41.6% compared with December 2019).

CONCLUSION:

Granular NHS general practice data at population-scale can be used to monitor disruptions to healthcare services and guide the development of mitigation strategies. The authors are now developing real-time monitoring dashboards for the key measures identified in this study, as well as further studies using primary care data to monitor and mitigate the indirect health impacts of COVID-19 on the NHS.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2023 Tipo de documento: Article