Assessing Data Adequacy for High Blood Pressure Clinical Decision Support: A Quantitative Analysis

Area of Science:

• Health Informatics
• Clinical Decision Support Systems
• Cardiovascular Health

Background:

• High blood pressure (HBP) is a significant risk factor for severe health outcomes like stroke and heart disease.
• Effective HBP management necessitates patient-centered strategies, including patient-facing clinical decision support (CDS) tools.

Purpose of the Study:

• To evaluate the data quality and logic needed for a Fast Healthcare Interoperable Resources (FHIR)-based, patient-facing CDS application for HBP.
• To assess the suitability of electronic health record (EHR) data for implementing guideline-based HBP recommendations.

Main Methods:

• Defined concept sets for 71 HBP guideline recommendations.
• Assessed EHR data quality for HBP screening and diagnosed cohorts across four use cases.
• Analyzed data completeness and accuracy for CDS functionality.

Main Results:

• 60% of required concept sets were unused or inaccurate.
• Data quality issues, including missing patient context (up to 65.6%), rendered 2 out of 4 use cases insufficient for accurate alerting.
• Despite inconsistencies, data adequacy was confirmed for two specific test use cases.

Conclusions:

• Inconsistent EHR data quality, stemming from healthcare fragmentation and incomplete standardization, hinders the development of robust HBP CDS tools.
• Current data quality permits further development of patient-facing FHIR HBP applications, but rigorous validation is essential to ensure precision and safety.