The impact of the COVID-19 pandemic on Antipsychotic Prescribing in individuals with autism, dementia, learning disability, serious mental illness or living in a care home: A federated analysis of 59 million patients primary care records in situ using OpenSAFELY (preprint)

Background: The COVID-19 pandemic significantly affected health and social care services. We aimed to explore whether this impacted the prescribing rates of antipsychotics within at-risk populations. Methods With the approval of NHS England, we completed a retrospective cohort study, using the OpenSAFELY platform to explore primary care data of 59 million patients. We identified patients in five at-risk groups: autism, dementia, learning disability, serious mental illness and care home residents. We then calculated the monthly prevalence of antipsychotic prescribing in the population, as well as the incidence of new prescriptions in each month over the study period (Jan 2019-Dec 2021). Results The average monthly rate of antipsychotic prescribing increased in dementia from 82.75 patients prescribed an antipsychotic per 1000 patients (95% CI 82.30-83.19) in Q1 2019 to 90.1 (95% CI 89.68-90.60) in Q4 2021 and from 154.61 (95% CI 153.79-155.43) in Q1 2019 to 166.95 (95% CI 166.23-167.67) in Q4 2021 in care homes . There were notable spikes in the rate of new prescriptions issued to patients with dementia and in care homes. In learning disability and autism groups, the average monthly rate of prescribing per 1000 decreased from 122.97 (95% CI 122.29-123.66) in Q1 2019 to 119.29 (95% CI 118.68-119.91) in Q4 2021, and from 54.91 (95% CI 54.52-55.29) in Q1 2019 to 51.04 (95% CI 50.74-51.35) in Q4 2021 respectively. Conclusions During each of the lockdowns in 2020, we observed a significant spike in antipsychotic prescribing in the dementia and care home groups. We have shown that these peaks are likely due to prescribing of antipsychotics for palliative care purposes and may have been linked to pre-emptive prescribing, when on-site medical visits would have been restricted. Over the study period, we observed gradual increases in antipsychotic use in patients with dementia and in care homes and a decrease in their use in patients with learning disability or autism.

Eleven key measures for monitoring general practice clinical activity during COVID-19 using federated analytics on 48 million adults' primary care records through OpenSAFELY (preprint)

Background The COVID-19 pandemic has had a significant impact on delivery of NHS care. We have developed the OpenSAFELY Service Restoration Observatory (SRO) to describe this impact on primary care activity and monitor its recovery. Objectives To develop key measures of primary care activity and describe the trends in these measures throughout the COVID-19 pandemic. Methods With the approval of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care electronic health record (EHR) data on 48 million adults. We developed SNOMED-CT codelists for key measures of primary care clinical activity selected by a expert clinical advisory group and conducted a population cohort-based study to describe trends and variation in these measures January 2019-December 2021, and pragmatically classified their level of recovery one year into the pandemic using the percentage change in the median practice level rate. Results We produced 11 measures reflective of clinical activity in general practice. A substantial drop in activity was observed in all measures at the outset of the COVID-19 pandemic. By April 2021, the median rate had recovered to within 15% of the median rate in April 2019 in six measures. The remaining measures showed a sustained drop, ranging from a 18.5% reduction in medication reviews to a 42.0% reduction in blood pressure monitoring. Three measures continued to show a sustained drop by December 2021. Conclusions The COVID-19 pandemic was associated with a substantial change in primary care activity across the measures we developed, with recovery in most measures. We delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. We will continue to expand the set of key measures to be routinely monitored using our publicly available NHS OpenSAFELY SRO dashboards with near real-time data.

Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients' primary care records in situ using OpenSAFELY (preprint)

Objective: To describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data. Design: Population based cohort study, with the approval of NHS England using the OpenSAFELY platform. Setting: Electronic health record data from 56.8 million NHS patients' general practice records. Participants: All NHS patients registered at a GP practice using TPP or EMIS computer systems and recorded as at risk of at least one potentially hazardous PINCER indicator between September 2019 and September 2021. Main outcome measure: Monthly trends and between-practice variation for compliance with 13 PINCER measures between September 2019 and September 2021. Results: The indicators were successfully implemented across GP data in OpenSAFELY. Hazardous prescribing remained largely unchanged during the COVID-19 pandemic, with only small reductions in achievement of the PINCER indicators. There were transient delays in blood test monitoring for some medications, particularly ACE inhibitors. All indicators exhibited substantial recovery by September 2021. We identified 1,813,058 patients at risk of at least one hazardous prescribing event. Conclusion: Good performance was maintained during the COVID-19 pandemic across a diverse range of widely evaluated measures of safe prescribing.

Recording of 'COVID-19 vaccine declined' among vaccination priority groups: a cohort study on 57.9 million NHS patients' primary care records in situ using OpenSAFELY (preprint)

BackgroundAll patients in England within vaccine priority groups were offered a COVID-19 vaccine by mid-April 2021. Clinical record systems contain codes to denote when such an offer has been declined by a patient (although these can in some cases be entered for a variety of other reasons including vaccination delay, or other administrative issues). We set out to describe the patterns of usage of codes for COVID-19 vaccines being declined. MethodsWith the approval of NHS England and using the full pseudonymised primary care records for 57.9 million NHS patients, we identified all patients in key vaccine priority groups: aged over 50, or over 16 and at increased risk from COVID-19 (Clinically Extremely Vulnerable [CEV] or otherwise "at risk"). We describe the proportion of patients recorded as declining a COVID-19 vaccination for each priority group, and by other clinical and demographic factors; whether patients recorded as "declined" subsequently went on to receive a vaccination; and the distribution of code usage across GP practices. ResultsOf 24.5 million patients in priority groups as of May 25th 2021, 89.2% had received a vaccine, 8.8% had neither a vaccination nor a decline recorded, and 663,033 (2.7%) had a decline code recorded. Of patients with a recorded decline, 125,587 (18.9%) were subsequently vaccinated. Subsequent vaccination was slightly more common in the South Asian population than other ethnicities (e.g. 32.3% vs 22.8%, over 65s). The proportion of declining-unvaccinated patients varied strongly with ethnicity (Black 15.3%, South Asian 5.6%, White 1.5% in over 80s); and was higher in patients from more deprived areas. COVID-19 vaccine decline codes were present in almost all practices (98.8%), but with wide variation between practices in rates of usage. Among all priority groups, declining-unvaccinated status was most common in CEV (3.3%). ConclusionsClinical codes indicative of COVID-19 vaccinations being declined are widely used in English general practice. They are substantially more common among Black and South Asian patients, and patients from more deprived areas. There is a need for more detailed survey and/or qualitative research with patients and clinicians to determine the most common reasons for these recorded declines.

Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY (preprint)

BackgroundLong COVID is a term to describe new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were released in November 2020 in the UK, but it is not known how these codes have been used in practice. MethodsWorking on behalf of NHS England, we used OpenSAFELY data encompassing 96% of the English population. We measured the proportion of people with a recorded code for long COVID, overall and by demographic factors, electronic health record software system, and week. We also measured variation in recording amongst practices. ResultsLong COVID was recorded for 23,273 people. Coding was unevenly distributed amongst practices, with 26.7% of practices having not used the codes at all. Regional variation was high, ranging between 20.3 per 100,000 people for East of England (95% confidence interval 19.3-21.4) and 55.6 in London (95% CI 54.1-57.1). The rate was higher amongst women (52.1, 95% CI 51.3-52.9) compared to men (28.1, 95% CI 27.5-28.7), and higher amongst practices using EMIS software (53.7, 95% CI 52.9-54.4) compared to TPP software (20.9, 95% CI 20.3-21.4). ConclusionsLong COVID coding in primary care is low compared with early reports of long COVID prevalence. This may reflect under-coding, sub-optimal communication of clinical terms, under-diagnosis, a true low prevalence of long COVID diagnosed by clinicians, or a combination of factors. We recommend increased awareness of diagnostic codes, to facilitate research and planning of services; and surveys of clinicians experiences, to complement ongoing patient surveys.