Abstract
AbstractOpenPROMPT is a cohort of individuals with longitudinal patient reported questionnaire data and linked to routinely collected health data from primary and secondary care. Data were collected between November 2022 and October 2023 in England. OpenPROMPT was designed to measure the impact of long COVID on health-related quality-of-life (HRQoL). With the approval of NHS England we collected responses from 7,574 individuals, with detailed questionnaire responses from 6,337 individuals who responded using a smartphone app. Data were collected from each participant over 90 days at 30-day intervals using questionnaires to ask about HRQoL, productivity and symptoms of long COVID. Responses from the majority of OpenPROMPT (6,006; 79.3%) were linked to participants’ existing health records from primary care, secondary care, COVID-19 testing and vaccination data. Analysis takes place using the OpenSAFELY data analysis platform which provides a secure software interface allowing the analysis of pseudonymized primary care patient records from England. OpenPROMPT can currently be used to estimate the impact of long COVID on HRQoL, and because of the linkage within OpenSAFELY, the data from OpenPROMPT can be used to enrich routinely collected records in further research by approved researchers on behalf of NHS England.Lay summaryOpenPROMPT is a study which used a phone app to conduct a longitudinal survey aimed at measuring the health related quality of life of people living with long COVID. The study recruited participants between November 2022 and July 2023 and followed them up for 90 days. The key advantage of this study is that the responses are linked to the individual’s personal health records, so we have access to much more data than the questionnaire responses alone.Here, we summarised who has used the app, how much data has been collected and the quality of the data. We also provide details to document how and why the data were collected so that the data can be used by other researchers in the future. This will maximise the benefit of this study, and ensure that the time invested by participants is put to best use.In this study we aimed to provide lots of important information about how many people are involved, how much information we have about them, their age, where they live, and how healthy they are. Finally, for certain variables we compared the responses people recorded in the app with what is kept on their electronic record to see if they agree or disagree.Key featuresOpenPROMPT is a cohort of individuals with longitudinal patient reported questionnaire data and linked to routinely collected health data from primary and secondary care.With the approval of NHS England we collected responses from 7,574 individuals, with detailed questionnaire responses from 6,337 individuals who responded using a smartphone app.Data were collected from each participant over 90 days at 30-day intervals using questionnaires to ask about HRQoL, productivity and symptoms of long COVID.Responses from the majority of OpenPROMPT (6,006; 79.3%) were linked to participants’ existing health records from primary care, secondary care, COVID-19 testing and vaccination data.OpenPROMPT can currently be used to estimate the impact of long COVID on HRQoL, and because of the linkage within OpenSAFELY, the data from OpenPROMPT can be used to enrich routinely collected records in further research by approved researchers on behalf of NHS England.
Publisher
Cold Spring Harbor Laboratory
Reference36 articles.
1. Sharp S , Boyce S , Karpusheff J , Glen F . Living with Long COVID: Implementing a living approach to the NICE guideline on managing the long-term effects of COVID-19 [Internet]. medRxiv; 2023 [cited 2023 Aug 18]. p. 2023.05.09.23289572. Available from: https://www.medrxiv.org/content/10.1101/2023.05.09.23289572v1
2. Overview | COVID-19 rapid guideline: managing the long-term effects of COVID-19 | Guidance | NICE [Internet]. NICE; 2020 [cited 2023 Nov 27]. Available from: https://www.nice.org.uk/guidance/ng188
3. Altmann DM , Whettlock EM , Liu S , Arachchillage DJ , Boyton RJ . The immunology of long COVID. Nat Rev Immunol. 2023 Jul 11;1–17.
4. Davis HE , McCorkell L , Vogel JM , Topol EJ . Long COVID: major findings, mechanisms and recommendations. Nat Rev Microbiol. 2023 Jan 13;1–14.
5. Bowe B , Xie Y , Al-Aly Z . Postacute sequelae of COVID-19 at 2 years. Nat Med. 2023 Aug 21;1–11.