Implementation of remote consulting in UK primary care following the COVID-19 pandemic: a mixed-methods longitudinal study
Mairead Murphy, Lauren J Scott, Chris Salisbury, Andrew Turner, Anne Scott, Rachel Denholm, Rhys Lewis, Geeta Iyer, John Macleod and Jeremy Horwood
Background: To reduce contagion of COVID-19, in March 2020 UK general practices implemented predominantly remote consulting via telephone, video, or online consultation platforms. Aim: To investigate the rapid implementation of remote consulting and explore impact over the initial months of the COVID-19 pandemic. Design and setting: Mixed-methods study in 21 general practices in Bristol, North Somerset and South Gloucestershire. Method: Longitudinal observational quantitative analysis compared volume and type of consultation in April to July 2020 with April to July 2019. Negative binomial models were used to identify if changes differed among different groups of patients. Qualitative data from 87 longitudinal interviews with practice staff in four rounds investigated practices’ experience of the move to remote consulting, challenges faced, and solutions. A thematic analysis utilised Normalisation Process Theory. Results: There was universal consensus that remote consulting was necessary. This drove a rapid change to 90% remote GP consulting (46% for nurses) by April 2020. Consultation rates reduced in April to July 2020 compared to 2019; GPs and nurses maintained a focus on older patients, shielding patients, and patients with poor mental health. Telephone consulting was sufficient for many patient problems, video consulting was used more rarely, and was less essential as lockdown eased. SMS-messaging increased more than three-fold. GPs were concerned about increased clinical risk and some had difficulties setting thresholds for seeing patients face-to-face as lockdown eased. Conclusion: The shift to remote consulting was successful and a focus maintained on vulnerable patients. It was driven by the imperative to reduce contagion and may have risks; post-pandemic, the model will need adjustment.