Identifying individuals for primary cardiovascular disease prevention in UK general practice: priorities and resource...

Area of Science:

• Public Health
• Cardiology
• Health Informatics

Background:

• Effective cardiovascular disease (CVD) prevention requires accurate patient risk assessment.
• Primary care records are a crucial source for identifying individuals at risk.
• Existing risk-stratification tools may not fully capture the at-risk population.

Purpose of the Study:

• To apply the 'e-Nudge' risk algorithm to primary care data for identifying individuals at risk of CVD.
• To quantify the proportion of individuals aged 50 and over at significant 10-year CVD risk.
• To assess the prevalence of unmanaged modifiable risk factors in patients with established CVD.

Main Methods:

• Utilized data from 19 West Midlands general practices.
• Applied the 'e-Nudge' risk algorithm to patients aged 50 years and older.
• Analyzed existing patient data and identified missing risk-factor information.

Main Results:

• 5.9% of patients aged 50-74 years were identified with a >=20% 10-year CVD risk.
• An additional 26.4% were potentially at risk but lacked complete risk-factor data.
• 9.2% of patients over 50 with existing CVD had unmanaged modifiable risk factors outside audit targets.

Conclusions:

• The 'e-Nudge' algorithm effectively identifies individuals at elevated CVD risk within primary care populations.
• Significant gaps exist in risk-factor data collection and management, impacting targeted prevention.
• Findings have implications for optimizing resource allocation in cardiovascular disease prevention strategies.