Persistent Cardiometabolic Health Gaps: Can Therapeutic Care Gaps Be Precisely Identified from Electronic Health...

Area of Science:

• Cardiology
• Endocrinology
• Public Health

Background:

• Cardiometabolic (CM) health management requires identifying and addressing therapeutic care gaps.
• Structured electronic health records (EHR) offer potential for identifying these gaps.
• Medication adherence data can help attribute care gaps to patient or clinician behavior.

Purpose of the Study:

• To evaluate the utility of EHR data in identifying and managing CM health gaps.
• To differentiate between patient- and clinician-related factors contributing to care gaps.
• To assess the prevalence and impact of these gaps in a large primary care population.

Main Methods:

• Utilized medication adherence data from dispense records to categorize care gaps.
• Analyzed data for 240,582 primary care patients across hypertension, hyperlipidemia, and diabetes.
• Employed logistic regression to determine associations between care gap types and health outcomes.

Main Results:

• Prevalence of health gaps: 44% (hypertension), 33% (hyperlipidemia), 57% (diabetes).
• Patient-related gaps (e.g., medication non-retrieval) were associated with increased health gaps (OR: 1.23-1.76).
• Clinician-related gaps showed strong associations with hyperlipidemia (OR=5.8) and diabetes (OR=5.7) health gaps.

Conclusions:

• Structured EHR data effectively identifies CM health and care gaps.
• Both patient and clinician factors significantly contribute to therapeutic care gaps.
• Uncertainty in gap attribution (9-21%) impedes effective management strategies.