Challenges in and Opportunities for Electronic Health Record-Based Data Analysis and Interpretation

Area of Science:

• Clinical Informatics
• Health Services Research
• Data Science in Healthcare

Background:

• Electronic health records (EHRs) are increasingly utilized in US clinical practices.
• EHRs provide extensive longitudinal real-world data for large patient populations.
• These data are valuable for clinical research and translating findings into practice.

Purpose of the Study:

• To critically assess the types of data available in EHRs.
• To describe the impact of data heterogeneity, quality, and generalizability on research.
• To identify and discuss challenges, errors, and biases in EHR data quality.

Main Methods:

• Review of EHR data characteristics and limitations for clinical research.
• Analysis of data heterogeneity, quality issues, and generalizability concerns.
• Examination of potential sources of errors and biases in EHR data.

Main Results:

• EHR data offer significant advantages but possess inherent limitations.
• Missing data, heterogeneity, and quality issues can introduce errors and biases.
• These factors can affect cohort representativeness and outcome accuracy.

Conclusions:

• A thorough evaluation of EHR data quality, heterogeneity, and generalizability is essential before and during analysis.
• Understanding and addressing potential biases and errors is critical for robust clinical research.
• Proactive strategies are necessary to ensure the integrity and appropriate use of EHR data in studies.