Impact of the COVID-19 pandemic on health-care usage and mental health of clinically extremely vulnerable individuals in Wales: a population-scale data linkage study

BACKGROUND: The public health response to the COVID-19 pandemic in the UK included advising those identified as clinically extremely vulnerable (CEV) to self-isolate within their homes. We compared the health-care usage and mental health of the CEV population with that of the general population during the pandemic. METHODS: In this retrospective population-scale data linkage study in Wales, we used person-level linked, routinely collected, data sources available within the Secure Anonymous Information Linkage Databank. Age-standardised rates of monthly planned and emergency care attendances between Jan 1, 2020, and Dec 31, 2020, were examined. We used a Cox model to explore risk factors for depression or anxiety (identified from primary care diagnosis, symptoms, and prescription Read codes). FINDINGS: The CEV cohort included 127 787 patients and was older than the general population (52·4% (66 963) CEV were aged ≥65 years, vs 21·0% (662 376) of the general population, p<0·0001). Average monthly trends showed that the decline in planned care was greater among the CEV than the general population from March–August, 2020 (elective admissions: –7·2% for CEV vs –0·6 for general population; outpatient attendances: –3·8% vs –1·3%), with a slower recovery into December, 2020 for CEV (elective: CEV –1.4% vs general population 3·9%; outpatient: 1·7% vs 4·1%). There were increases in both ED attendances and emergency admissions from March–August, 2020, which were greater among the general population (7·0% vs 3·1%, respectively) compared with the CEV (4·3% vs 0·5%). Being CEV (hazard ratio 1·2 [95% CI 1·2–1·3]) and historical poor mental health (3·7 [3·5–3·9]) were associated with an increased risk of anxiety or depression. INTERPRETATION: Declines in planned care were not unexpected given the impact of COVID-19 on the National Health Service, and suggest considerable unmet need. Declines in secondary care activity amongst the CEV could reflect reluctance to attend hospital, not reduced clinical need. Reliance on an algorithm to identify CEV might have led to overestimation of the heterogeneous CEV population. FUNDING: The Health Foundation as part of the Networked Data Labs.