Meredith Nahm Zozus and colleagues from the NIH Collaboratory’s Phenotypes, Data Standards, and Data Quality Core have published a new Living Textbook chapter about key considerations for secondary use of electronic health record (EHR) data for clinical research.
In contrast to traditional randomized controlled clinical trials where data are prospectively collected, many pragmatic clinical trials use data that were primarily collected for clinical purposes and are secondarily used for research. The chapter describes the steps a prospective researcher will take to acquire and use EHR data:
- Gain permission to use the data. When a prospective researcher wishes to use data, a data use agreement (DUA) is usually required that describes the purpose of the research and the proposed use of the data. This section also describes use of de-identified data and limited data sets.
- Understand fundamental differences in context. Data collected in routine care settings reflect standard procedures at an individual’s healthcare facility, and are not collected in a standard, structured manner.
- Assess the availability of health record data. Few assumptions can be made about what is available from an organization’s healthcare records; up-front, detailed discussions about data element collection over time at each facility is required.
- Understand the available data. A secondary data user must understand both the data meaning and the data quality; both can vary greatly across organizations and affect a study’s ability to support research conclusions.
- Identify populations and outcomes of interest. Because healthcare facilities are obligated to provide only the minimum necessary data to answer a research question, investigators must identify the needed patients and data elements with specificity and sensitivity to answer the research question given the available data.
- Consider record linkage. Studies using data from multiple records and sources will require matching data to ensure they refer to the correct patient.
- Manage the data. The investigator is responsible for receiving, managing, and processing data and must demonstrate that the data are reproducible and support research conclusions.
- Archive and share the data after the study. Data may be archived and shared to ensure reproducibility, enable auditing for quality assurance and regulatory compliance, or to answer other questions about the research.