Unlocking the Potential of Electronic Health Records for Health Research

Area of Science:

• Health Informatics
• Biomedical Research Data Management

Background:

• Electronic health records (EHRs) are evolving from clinical tools to vital research data sources.
• EHR systems comprise front-end data entry and back-end data warehousing.
• Data within EHRs include structured, unstructured free-text, and imaging formats.

Purpose of the Study:

• To describe the Sunrise Clinical Manager (SCM) EHR system for health research applications.
• To generalize findings from the SCM EHR to other EHR systems used in research.
• To outline the advantages, challenges, analytical capabilities, and requirements for EHR research.

Main Methods:

• Descriptive analysis of the Sunrise Clinical Manager (SCM) EHR system architecture.
• Exploration of data types (structured, unstructured, imaging) within the SCM EHR.
• Review of research-related functionalities and considerations for EHR data.

Main Results:

• The SCM EHR in Calgary, Alberta, is being evaluated for research utility.
• EHR data present opportunities and challenges, including potential bias and data quality concerns.
• Various analytical approaches can be applied to EHR data for research.

Conclusions:

• EHRs, exemplified by the SCM system, are increasingly important for health research.
• Understanding EHR system components and data types is crucial for effective research utilization.
• Addressing challenges like data quality and bias is essential for reliable EHR-based research findings.