Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study

Abstract

Background: Long COVID potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined.

Methods: This study aims to assess the healthcare utilisation of individuals with long COVID. With the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records.

Results: We identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.29, 95% CI: 7.74-8.87), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.48-1.51). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58-29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73-16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.66, 95% CI = 7.20-8.15), with costs being 44% higher than the comparator group (cost ratio = 1.44, 95% CI: 1.39-1.50). The long COVID group costs approximately £2500 per person per year (predicted mean cost: £2562.50, 95% CI: £2335.60-£2819.22), and the comparator group costs £1500 (predicted mean cost: £1527.43, 95% CI: £1404.33-1664.45). Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group.

Conclusions: Long COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.

Keywords: Electronic health records; Facilities and services utilization; Health care costs; Long COVID.

Fig. 1

The study design. a Contemporary comparisons. b Historical comparisons

Fig. 2

Healthcare utilisation among people with long COVID. Each subfigure shows the first and second part of the model in the upper panel, where the first part gives the odds ratio (OR) of healthcare resource utilisation and the second part is the rate ratio (RR) of healthcare utilisation between people with long COVID and comparator groups, conditioned on people having used healthcare resources. Each lower panel shows the predicted average healthcare utilisation in long COVID and Comparator groups. Values are shown for a total healthcare utilisation, and then separately for each part of the total: b GP visits, c prescriptions, d emergency care at A&E, e inpatient hospitalisations, and f outpatient visits

Fig. 3

Total health costs among people with and without long COVID. Each subfigure shows the first and second part of the model in the upper panel, where the first part is the odds ratio (OR) of having any healthcare costs and the second part is the rate ratio (RR) of healthcare costs between people with long COVID and comparator groups, conditioned on people having any healthcare costs. Each bar chart shows the predicted average healthcare costs among the long COVID and Comparator groups. Values are shown for a total healthcare costs, and then separately for each part of the total: b GP visits, c prescriptions, d emergency care at A&E, e inpatient hospitalisations, and f outpatient visits

Fig. 4

Predicted average healthcare visits before and after the pandemic. The analysis is based on a difference-in-difference analysis comparing those with long COVID and their age-, sex- and region-matched comparators

Fig. 5

Factors associated with high healthcare use from the two-part model. The first forest plot shows the odds ratio (OR) of having non-zero healthcare use from the binomial model, the second part is the rate ratio (RR) for healthcare use from the truncated negative binomial model