Project #136:
GP appointments during COVID

We are interested in describing and measuring the effect of COVID disruption on GP appointments. We have access to a database of GP appointment data that contains appointment scheduling information for 40% of the population in England.

We would like to explore the data in more detail to look at patterns over time to assist with health service recovery from COVID-19. We are particularly interested in looking at appointment lead time, which means the time between requesting an appointment and the appointment date. We will explore whether this (and other measures of interest) change over time, particularly before, during and after COVID. In addition to looking at this for the whole population, we will look at changes in particular subgroups of patients; for example, in particular age groups or ethnic groups, or for groups of patients with the same diagnosis (e.g., mental health).

With a better idea of how access to GP appointments varied over time for these groups, we would like to explore the data in more detail by applying data science methodologies to identify any short- and long-term patterns of change. We will be asking questions like: were some practices able to reduce appointment lead times faster than others in the COVID recovery period? If so, do those practices have any characteristics in common? This is important as it may help us identify best practice and describe the most effective and efficient response to primary care disruption due to COVID-19 in the future.