Operational Tools and Best Practices to Support Electronic Health Record-Sourced Data Quality, Relevance, and Reliability at the Data Accrual Phase

Executive Summary

Electronic health records (EHRs) are an often reliable source of in-depth information about health care events, seeking behavior, and interactions throughout the course of a patient’s life. Data that can be sourced from an EHR often includes structured and unstructured information within data fields, including but not limited to demographic details, clinical encounter details, diagnoses, symptoms, treatments, laboratory test results, prescriptions, imaging, charts, patient experience insights, and clinical narratives. Ongoing advancements and technological developments in EHR platforms, coupled with sophisticated data accrual methods used to obtain data or analytical insights from EHR records, have rendered EHR-sourced data useful to support critical decisions made within the health system, including regulatory decisions.

EHR-sourced data used to support regulatory decision-making falls within the scope of real-world data (RWD) and real-world evidence (RWE), rendering EHR-sourced data as subject to regulatory agency scrutiny. In this white paper, we discuss complex operational workflows that exist at the EHR-sourced data accrual phase; review current initiatives and use cases that provide insights into best practices for EHR-sourced data accrual management; and outline tools and best practices that can be useful among trial sponsors and data collaborators seeking to support EHR-sourced data relevance, reliability, and quality, and communicate those aspects to regulators and others.