Using data to improve public health: COVID-19 secondment

Patients' willingness to seek timely medical treatment is instrumental in delivering adequate care. It is one of the National Health Service's (NHS) core missions to improve public health and well-being. Delayed treatment has been associated with higher overall healthcare costs and poor health outcomes. The COVID-19 (C19) pandemic had a profound impact on both the healthcare system as well as on patients. However, the impact of C19 on public willingness to seek timely treatment remains critically understudied. The secondment will be used to shed light on this aspect by analysing fully anonymised patient data within OpenSAFELY. Given the heavily redacted nature of the data, a combination of code lists from OpenCodelists need to be used to illustrate healthcare seeking behaviour. Specifically, healthcare seeking behaviour from patients who suffer from acute pain, as identified by all relevant CTV3 codes, are observed between the time the first national lockdown was introduced and after all restrictions had been lifted. It is hypothesized that medical treatment to alleviate pain was delayed during all national lockdown episodes due to public health interventions that aimed to protect the NHS from collapsing. Similarly, it is assumed that, on average, delayed medical treatment for acute pain patients continue to persist even after all protective public health measures had been lifted. In other words, it is hypothesized that some patients do not seek treatment for pain relief as fast as they would have prior to the pandemic. Mixed method time series modelling is used to estimate the hypothesised increase in delayed treatment. Competing explanations for delayed treatment are tested. Specifically, generalised linear models are used to derive odds ratios for competing explanations (e.g., C19 status). The aim is to identify relevant sociodemographic groups that would benefit from targeted campaigns to increase their tendency to seek timely treatment.