Using Big Data for Cardiovascular Health Surveillance: Insights From 10.3 Million Individuals in the CANHEART Cohort

Area of Science:

• Public Health
• Epidemiology
• Health Informatics

Background:

• Large electronic health databases offer novel avenues for cardiovascular health surveillance.
• Traditional methods relied on surveys, which are resource-intensive.
• This study explores the utility of linked administrative data for population health monitoring.

Purpose of the Study:

• To assess cardiovascular risk-factor burden, preventive care, and disease incidence in Ontario adults using routinely collected health data.
• To compare these estimates with data from the Canadian Health Measures Survey (CHMS).

Main Methods:

• The Cardiovascular Health in Ambulatory Care Research Team (CANHEART) initiative linked multiple health administrative databases.
• A cohort of 10.3 million Ontario adults without prior cardiovascular disease was established.
• Data from 2016-2020 were analyzed and compared with CHMS data (2012-2017).

Main Results:

• Assessment rates for lipids and diabetes were high (76.6% and 78.2%) but lower in younger men.
• Cardiovascular risk factor prevalence (cholesterol, diabetes, hypertension) was similar between CANHEART and CHMS data.
• CANHEART participants exhibited slightly higher mean glucose and systolic blood pressure levels.

Conclusions:

• Routinely collected electronic health data are viable for cardiovascular health surveillance.
• Linkage of administrative datasets provides a robust population-based approach.
• Further research is needed to reconcile differences between administrative and survey data measures over time.