OpenSAFELY NHS Service Restoration Observatory 2: changes in primary care clinical activity in England during the COVID-19 pandemic
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Abstract
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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SciScore for 10.1101/2022.06.01.22275674: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable Study measures: We pragmatically grouped activity and selected clinical codes relevant to each of the following topics: Cardiovascular disease, Diabetes, Mental health, Female and reproductive health, Screening and related procedures, and Processes related to medication. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Software and reproducibility: Data management and analysis were performed using Python 3.8. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the …SciScore for 10.1101/2022.06.01.22275674: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable Study measures: We pragmatically grouped activity and selected clinical codes relevant to each of the following topics: Cardiovascular disease, Diabetes, Mental health, Female and reproductive health, Screening and related procedures, and Processes related to medication. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Software and reproducibility: Data management and analysis were performed using Python 3.8. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and weaknesses: The key strengths are the scale and completeness of the underlying raw EHR data, available close to real time, and we engaged with clinicians for added context. All processed data and analytical code is openly available in the Supplementary Materials or Github. We will publish our recommended key measures in a live updating report, and we encourage other groups to use OpenSafely for further exploration. Our data-driven approach is intended to generate an overall picture of primary care clinical activity, and explore high volume areas that might otherwise be missed, for example when not included in manually curated codelists. Despite the strengths we recognise some limitations as previously discussed.11 Our data-driven approach and filtering processes may have omitted some relevant codes; codes do not necessarily indicate unique or new events, and may be affected by changes in coding behaviour. All coded activity for patients registered at the end of the study period were included, and all activity was included under their latest practice. Patients who died or deregistered from TPP practices during the study period were not included. Overall, activity counts were up to 6-8% lower than database totals in the earliest months of the study period. Interpretation and context for each clinical area: Given the diversity of clinical areas covered by this overarching analysis, the clinical advisory group evaluated and interpreted the variation for each clinica...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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