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Protocol for an OpenSAFELY cohort study collecting patient-reported outcome measures using the TPP Airmid smartphone application and linked big data to quantify the health and economic costs of long COVID (OpenPROMPT).
Herrett, Emily; Tomlin, Keith; Lin, Liang-Yu; Tomlinson, Laurie A; Jit, Mark; Briggs, Andrew; Marks, Michael; Sandmann, Frank; Parry, John; Bates, Christopher; Morley, Jessica; Bacon, Seb; Butler-Cole, Benjamin; Mahalingasivam, Viyaasan; Dennison, Alan; Smith, Deb; Gabriel, Ethan; Mehrkar, Amir; Goldacre, Ben; Smeeth, Liam; Eggo, Rosalind M M.
Afiliación
  • Herrett E; London School of Hygiene and Tropical Medicine, London, UK emily.herrett@lshtm.ac.uk.
  • Tomlin K; London School of Hygiene and Tropical Medicine, London, UK.
  • Lin LY; London School of Hygiene and Tropical Medicine, London, UK.
  • Tomlinson LA; London School of Hygiene and Tropical Medicine, London, UK.
  • Jit M; London School of Hygiene and Tropical Medicine, London, UK.
  • Briggs A; London School of Hygiene and Tropical Medicine, London, UK.
  • Marks M; London School of Hygiene and Tropical Medicine, London, UK.
  • Sandmann F; Hospital for Tropical Diseases, London, UK.
  • Parry J; London School of Hygiene and Tropical Medicine, London, UK.
  • Bates C; TPP, Leeds, UK.
  • Morley J; TPP, Leeds, UK.
  • Bacon S; Bennett Institute for Applied Data Science, University of Oxford, Oxford, UK.
  • Butler-Cole B; Bennett Institute for Applied Data Science, University of Oxford, Oxford, UK.
  • Mahalingasivam V; Bennett Institute for Applied Data Science, University of Oxford, Oxford, UK.
  • Dennison A; London School of Hygiene and Tropical Medicine, London, UK.
  • Smith D; Patient and Public Involvement Steering Committee, London, UK.
  • Gabriel E; Patient and Public Involvement Steering Committee, London, UK.
  • Mehrkar A; Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
  • Goldacre B; Patient and Public Involvement Steering Committee, London, UK.
  • Smeeth L; Bennett Institute for Applied Data Science, University of Oxford, Oxford, UK.
  • Eggo RMM; Bennett Institute for Applied Data Science, University of Oxford, Oxford, UK.
BMJ Open ; 13(2): e071261, 2023 02 17.
Article en En | MEDLINE | ID: mdl-36806073
INTRODUCTION: The impact of long COVID on health-related quality of-life (HRQoL) and productivity is not currently known. It is important to understand who is worst affected by long COVID and the cost to the National Health Service (NHS) and society, so that strategies like booster vaccines can be prioritised to the right people. OpenPROMPT aims to understand the impact of long COVID on HRQoL in adults attending English primary care. METHODS AND ANALYSIS: We will ask people to participate in this cohort study through a smartphone app (Airmid), and completing a series of questionnaires held within the app. Questionnaires will ask about HRQoL, productivity and symptoms of long COVID. Participants will be asked to fill in the questionnaires once a month, for 90 days. Questionnaire responses will be linked, where possible, to participants' existing health records from primary care, secondary care, and COVID testing and vaccination data. Analysis will take place using the OpenSAFELY data platform and will estimate the impact of long COVID on HRQoL, productivity and cost to the NHS. ETHICS AND DISSEMINATION: The Proportionate Review Sub-Committee of the South Central-Berkshire B Research Ethics Committee has reviewed and approved the study and have agreed that we can ask people to take part (22/SC/0198). Our results will provide information to support long-term care, and make recommendations for prevention of long COVID in the future. TRIAL REGISTRATION NUMBER: NCT05552612.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aplicaciones Móviles / COVID-19 Tipo de estudio: Etiology_studies / Health_economic_evaluation / Incidence_studies / Observational_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: BMJ Open Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aplicaciones Móviles / COVID-19 Tipo de estudio: Etiology_studies / Health_economic_evaluation / Incidence_studies / Observational_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: BMJ Open Año: 2023 Tipo del documento: Article