Using Electronic Health Record Data in Pragmatic Clinical Trials
Specific Uses for EHR Data in PCTs
Karen Staman, MS
EHR data and systems can be used to support 4 major activities of pragmatic trials, which include:
- Identifying the study population, often in terms of phenotypes or clinical profiles including current health status or medical history
- Estimating sample size for study design and planning
- Identifying a cohort of patients for screening, recruitment, or enrollment.
- Assessing baseline prognostic characteristics of the research sample or cohort for a number of objective and subjective measures
- Example of an objective measure: definitive lab values for a specific disease, such as chronic kidney disease or HbA1C for diabetes control. (These are subject, of course, to the kinds of limitations noted above. In PCTs, investigators make do with whatever value is in the chart, typically without capturing any information about the clinical lab’s quality control values for these tests.)
- Example of a subjective measure: clinical judgement about autism spectrum disorder or an observation by a clinician on skin discoloration or patient discomfort.
- Implementing and monitoring the delivery of an intervention (using EHR system functions, such as alerts, info-buttons, and computerized provider order entry (CPOE) interfaces)
- Measuring the outcomes for both the intervention and control populations.
- Longitudinal data linkage—following a cohort of patients over time may require aggregating data from multiple encounters, providers, and information systems. Linkage techniques to ensure that the correct data are being applied to each patient are critical for randomized PCTs, especially if the longitudinal data are being used to measure the effectiveness of the intervention.
In the following sections, we describe each of these uses for EHR data by PCT activity.
- Data as a Surrogate for Clinical Phenomena
- Developing and Refining the Research Questions
- Specific Uses for EHR Data in PCTs
- Identifying the Study Population and Assessing Baseline Prognostic Characteristics
- Implementing and Monitoring the Delivery of an Intervention
- Assessing Outcomes
- The Research Question Drives the Data Requirements
- Additional Resources
For more on data linkage, see the article Health Services Research and Data Linkages: Issues, Methods, and Directions for the Future
The National Center for Health Statistics provides this list of Data Linkage Resources