Using Electronic Health Record Data to Measure Care Quality for Individuals with Multiple Chronic Medical Conditions

Area of Science:

• Health Services Research
• Geriatric Medicine
• Health Informatics

Background:

• Measuring quality care for individuals with multiple chronic conditions (MCCs) is complex.
• Existing measures often focus on outcomes rather than processes.
• Electronic health records (EHRs) offer potential for data-driven quality assessment.

Purpose of the Study:

• To develop a data-driven measure of quality care for individuals with MCCs using EHR data.
• To identify key constructs of high-quality care for patients with MCCs.
• To assess the feasibility of measuring these constructs using EHR data.

Main Methods:

• Qualitative study employing focus groups, interactive webinars, and a modified Delphi process.
• Involved 17 experts in geriatrics, primary care, health policy, and health technology.
• Included 10 patients aged 70-87 with 3-6 chronic conditions.

Main Results:

• High-priority quality care constructs focused on processes, such as physical function assessment, depression screening, and medication reconciliation.
• Feasible EHR-measurable processes included influenza vaccination and post-hospitalization outreach.
• Less feasible but important processes included goal setting, shared decision-making, and social support assessment.

Conclusions:

• High-quality care for MCCs is best measured by meaningful process indicators.
• Current EHR data can capture some processes, but technological adaptation is needed for others.
• Future efforts should focus on leveraging technology for holistic, person-centered MCC care.