JMIR Publications

ABSTRACT

Background:

Global trends in cardiovascular disease (CVD) exhibit considerable inter-regional and inter-ethnic differences, which in turn affect long term CVD risk across diverse populations. An in-depth understanding of the interplay between ethnicity, socio-economic status and CVD risk factors and mortality in a contemporaneous population is crucial to informing health policy and resource allocation aimed at mitigating long-term CVD risk. Generating bespoke large-scale and reliable data with sufficient numbers of events is expensive and time consuming but can be circumvented through utilisation and linkage of routine collected data in electronic health records (EHR).

Objective:

We therefore aim to characterise the burden of CVD risk factors across different ethnicities, age-groups and socio-economic groups, and study CVD incidence and mortality by EHR linkage in London.

Methods:

The proposed study will initially be a cross-sectional observational study unfolding into prospective CVD ascertainment through longitudinal follow-up involving linked data. The government funded NHS Health Check programme provides an opportunity for the systematic collation of CVD risk factors on a large-scale. NHS Health Check data on approximately 200,000 individuals will be extracted from consenting GP practices across London that use the EHR Egton Medical Information Systems (EMIS) software. Data will be analysed using appropriate statistical techniques to: (i) determine cross-sectional burden of CVD risk factors and their prospective association with CVD outcomes, (ii) validate existing prediction tools in diverse populations and (iii) develop bespoke risk prediction tools across diverse ethnic groups.

Results:

Enrolment began January 2019 and is ongoing with initial results to be published mid-to-late 2020.

Conclusions:

There is an urgent need for more real-life population health studies based on analyses of routine health data available in EHRs. Findings from our study will help quantify on a large scale, the contemporaneous burden of CVD risk factors by geography and ethnicity in a large multi-ethnic urban population. Such detailed understanding (especially inter-ethnic and socio-demographic variations) of the burden of CVD risk and its determinants, including heredity, environment, diet, lifestyle and socioeconomic factors, in a large population sample will enable development of tailored and dynamic (continuously learning from new data) risk prediction tools for diverse ethnic groups, and thereby enable personalised provision of prevention strategies and care. We anticipate that this systematic approach of linking routinely collected data from EHRs to study CVD can be conducted in other setting as EHRs are being implemented worldwide.