Specific Uses for EHR Data in PCTs

Using Electronic Health Record Data in Pragmatic Clinical Trials

Section 4

Specific Uses for EHR Data in PCTs


Rachel Richesson, MS, PhD, MPH

Richard Platt, MD, MSc

Gregory Simon, MD, MPH

Lesley Curtis, PhD

Reesa Laws, BS

Adrian Hernandez, MD, MSH

Jon Puro, MPA-HA

Doug Zatzick, MD

Erik van Eaton, MD, FACS

Vincent Mor, PhD


Contributing Editor

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
    • In a cluster-randomized design, patient populations may be unbalanced due to facility differences in patient mix. Prognostic factors can be used to detect the balance (or imbalance) of specified independent variables. However, if the factors are used as part of the stratification scheme for cluster-randomization, then this type of balancing is not possible.
    • 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.



Version History

November 30, 2018: Updated text as part of annual update (changes made by K. Staman).

Published August 25, 2017


Richesson R, Platt P, Simon G, et al. Using Electronic Health Record Data in Pragmatic Clinical Trials: Specific Uses for EHR Data in PCTs. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Health Care Systems Research Collaboratory. Available at: https://rethinkingclinicaltrials.org/chapters/design/using-electronic-health-record-data-pragmatic-clinical-trials-top/specific-uses-ehr-data-pcts/. Updated November 30, 2018. DOI: 10.28929/033.