Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19–a data-driven retrospective cohort study

Objectives: To use national, pre- and post-pandemic electronic health records (EHR) to develop and validate a scenario-based model incorporating baseline mortality risk, infection rate (IR) and relative risk (RR) of death for prediction of excess deaths. Design: An EHR-based, retrospective cohort study. Setting: Linked EHR in Clinical Practice Research Datalink (CPRD); and linked EHR and COVID-19 data in England provided in NHS Digital Trusted Research Environment (TRE). Participants: In the development (CPRD) and validation (TRE) cohorts, we included 3.8 million and 35.1 million individuals aged ≥30 years, respectively. Main outcome measures: One-year all-cause excess deaths related to COVID-19 from March 2020 to March 2021. Results: From 1 March 2020 to 1 March 2021, there were 127,020 observed excess deaths. Observed RR was 4.34% (95% CI, 4.31–4.38) and IR was 6.27% (95% CI, 6.26–6.28). In the validation cohort, predicted one-year excess deaths were 100,338 compared with the observed 127,020 deaths with a ratio of predicted to observed excess deaths of 0.79. Conclusions: We show that a simple, parsimonious model incorporating baseline mortality risk, one-year IR and RR of the pandemic can be used for scenario-based prediction of excess deaths in the early stages of a pandemic. Our analyses show that EHR could inform pandemic planning and surveillance, despite limited use in emergency preparedness to date. Although infection dynamics are important in the prediction of mortality, future models should take greater account of underlying conditions

Annual crude and age/sex-standardised prevalence of number of comorbidities in incident cardiovascular disease patients.

<p>(A) Crude prevalence. (B) Age/sex-standardised prevalence. Number labels for each line refer to the number of comorbidities.</p

Baseline characteristics of patients with CVD at time of diagnosis.

<p>Baseline characteristics of patients with CVD at time of diagnosis.</p

Age-standardised prevalence of comorbidities in women and men.

<p>The top 20 comorbidities ranked by sex-specific age-standardised prevalence between 2000 and 2014 are shown for men (blue) and women (red). CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; PAD, peripheral arterial disease.</p

Age/sex-standardised prevalence of comorbidities in patients with incident cardiovascular disease (<i>n =</i> 229,205).

<p>Age/sex-standardised prevalence of comorbidities in patients with incident cardiovascular disease (<i>n =</i> 229,205).</p

Age/sex-standardised prevalence of number of comorbidities in patients with incident cardiovascular disease by socioeconomic status.

<p>Socioeconomic status is split by quintiles of the Index of Multiple Deprivation for 2015, where 1 = the least deprived fifth, and 5 = the most deprived fifth.</p

Annual prevalence of the 10 most common comorbidities in patients with incident cardiovascular disease between 2000 and 2014.

<p>CKD, chronic kidney disease.</p

Comorbidities selected.

<p>Comorbidities selected.</p

Annual age/sex-standardised incidence of CVD, IHD, and stroke/TIA.

<p>Overall CVD (red line); IHD (including acute myocardial infarction and angina; green line); stroke/TIA (blue line). CVD, cardiovascular disease; IHD, ischaemic heart disease; TIA, transient ischaemic attack.</p

Age-specific ranking of the top 10 most prevalent comorbidities.

<p>Age-specific ranking of the top 10 most prevalent comorbidities.</p