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Living Textbook of
Pragmatic Clinical Trials

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Rethinking Clinical Trials

A Living Textbook of Pragmatic Clinical Trials

  • Design
    • What is a Pragmatic Clinical Trial?
    • Decentralized Pragmatic Clinical Trials
    • Developing a Compelling Grant Application
    • Experimental Designs and Randomization Schemes
    • Endpoints and Outcomes
    • Analysis Plan
    • Using Electronic Health Record Data
    • Building Partnerships and Teams to Ensure a Successful Trial
    • Intervention Delivery and Complexity
    • Patient Engagement
  • Data, Tools & Conduct
    • Assessing Feasibility
    • Acquiring Real-World Data
    • Assessing Fitness-for-Use of Real-World Data
    • Study Startup
    • Participant Recruitment
    • Monitoring Intervention Fidelity and Adaptations
    • Patient-Reported Outcomes
    • Clinical Decision Support
    • Mobile Health
    • Electronic Health Records–Based Phenotyping
    • Navigating the Unknown
  • Dissemination & Implementation
    • Data Sharing and Embedded Research
    • Dissemination Approaches for Different Audiences
    • Implementation
    • End-of-Trial Decision-Making
  • Ethics & Regulatory
    • Privacy Considerations
    • Identifying Those Engaged in Research
    • Collateral Findings
    • Consent, Disclosure, and Non-Disclosure
    • Data and Safety Monitoring
    • Ethical Considerations of Data Sharing in Pragmatic Clinical Trials
    • Ethics for AI and ML
    • IRB Responsibilities and Procedures

Best Practices for Collecting PRO Measures in Pragmatic Clinical Trials

CHAPTER SECTIONS

Real-World Evidence: Patient-Reported Outcomes (PROs)


Section 3

Best Practices for Collecting PRO Measures in Pragmatic Clinical Trials

Expand Contributors

Emily O'Brien, PhD
Christy Zigler, PhD, MSED

Contributing Editor

Karen Staman, MS

When conducting pragmatic clinical trials (PCTs) in partnership with health care systems, NIH Pragmatic Trials Collaboratory study teams have encountered several challenges with collecting patient-reported outcome (PRO) measures, including

  • Competing health system and research priorities
  • Additional burden of collecting PROs falling on clinicians
  • Low adoption and reach of technology, including low use of patient portals, in socioeconomically disadvantaged and rural systems
  • Lack of consensus and standardization PRO measure selection across different electronic health records (EHRs) and systems (Zigler et al. 2023)

To counter these challenges, the PCO Core, EHR Core, and study teams developed a set of recommendations (Zigler et al 2024), which are summarized below:

Competing health care system and research priorities

The PRO collection strategy for the trial should align as much as possible with the healthcare system’s goals. Adding a PRO measure to an EHR system requires resources (money and time), aligning priorities can help lessen the risk that it may increase or disrupt the workflow of overburdened clinicians and provide value for both patients and clinicians.  When these data are critical to the PCT but not considered a priority to key health system stakeholders, PRO data can be collected in systems separate from the EHR, such as RedCap.

Clinician buy-in for adoption of PRO measures

Ideally, PRO data collected for a PCT will also contribute to clinical decision-making and facilitate communication and high-quality patient care. To achieve this, help with interpretation of scores and contextual differences that may affect score interpretation are useful, along with training and clear, comprehensive explanations. This training should include contact information for the study team so clinicians can report problems or provide input.

Low adoption and reach of technology in low resource settings

Socioeconomically disadvantaged and rural systems, such as safety net hospitals and community health centers often have constrained technological resources, which can result in low use of patient portals and other technologies (Kruse et al. 2016; Adler-Milstein et al. 2017). If portal-based mechanisms to capture PRO measures are unavailable, other modes of outreach can be used, such as text messaging and interactive voice response platforms. To reach medically underserved patients, including people with incomes below the federal poverty threshold, racial or ethnically minoritized groups, or rural or frontier communities, hybrid methods are often necessary. These may involve multiple outreach modes, high-touch methods, creativity in promoting digital uptake, multi-modal participant engagement, and text messaging (Cheville et al 2024 in press).

Lack of Consensus and Standardization of PRO measure selection and administration in the EHR

There is a lack of consensus about which PRO measures are the most appropriate across healthcare systems—and even within systems. Investigators should try to use well-validated standardized measures where possible to capture meaningful health states. One example would be using the Patient Reported Outcomes Measurement Information System (PROMIS), which includes reliable measures for many chronic disease conditions.(PROMIS 2013 Jun 26). Similarly, the NIH requires all HEAL Initiative (The Helping to End Addiction Long-term Initiative)(Collins et al. 2018) trials for the reduction of chronic pain and opioid use to use the NIH Common Data Elements measures that are housed in the NIH Common Data Elements Repository. A consensus on selected measures across similar projects or shared domains can facilitate data sharing amongst researchers.

Previous Section Next Section

SECTIONS

CHAPTER SECTIONS

sections

  1. Introduction
  2. How Are PRO Measures Used?
  3. Best Practices for Collecting PRO Measures in Pragmatic Clinical Trials
  4. NIH HEAL, FDA, and Other Core Outcome Sets
  5. Choosing PRO Measures
  6. Cultural Adaptation and Linguistic Translation
  7. Case Study From Guiding Good Choices for Health
  8. Incorporating PRO Data Into the EHR
  9. Patient-Focused Drug Development
  10. Additional Resources

REFERENCES

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Adler-Milstein J, Holmgren AJ, Kralovec P, Worzala C, Searcy T, Patel V. 2017. Electronic health record adoption in US hospitals: the emergence of a digital “advanced use” divide. Journal of the American Medical Informatics Association. 24:1142–1148. doi:10.1093/jamia/ocx080.

Collins FS, Koroshetz WJ, Volkow ND. 2018. Helping to End Addiction Over the Long-term: The Research Plan for the NIH HEAL Initiative. JAMA. 320:129. doi:10.1001/jama.2018.8826.

Kruse CS, Kristof C, Jones B, Mitchell E, Martinez A. 2016. Barriers to Electronic Health Record Adoption: a Systematic Literature Review. J Med Syst. 40:252. doi:10.1007/s10916-016-0628-9.

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PROMIS: Patient-Reported Outcomes Measurement Information System - Home Page. 2013 Jun 26. https://commonfund.nih.gov/promis/index. Accessed May 31, 2023.

Zigler CK, Adeyemi O, Boyd AD, et al. 2023 Dec. Collecting patient-reported outcome measures in the electronic health record: Lessons from the NIH pragmatic trials Collaboratory. Contemporary Clinical Trials.:107426. doi:10.1016/j.cct.2023.107426.


Version History

Published March 20, 2024

current section :

Best Practices for Collecting PRO Measures in Pragmatic Clinical Trials

  1. Introduction
  2. How Are PRO Measures Used?
  3. Best Practices for Collecting PRO Measures in Pragmatic Clinical Trials
  4. NIH HEAL, FDA, and Other Core Outcome Sets
  5. Choosing PRO Measures
  6. Cultural Adaptation and Linguistic Translation
  7. Case Study From Guiding Good Choices for Health
  8. Incorporating PRO Data Into the EHR
  9. Patient-Focused Drug Development
  10. Additional Resources

Citation:

O’Brien E; Zigler C. Real-World Evidence: Patient-Reported Outcomes (PROs): Best Practices for Collecting PRO Measures in Pragmatic Clinical Trials. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Pragmatic Trials Collaboratory. Available at: https://rethinkingclinicaltrials.org/chapters/conduct/real-world-evidence-patient-reported-outcomes-pros/best-practices-for-collecting-pro-measures-in-pragmatic-clinical-trials/. Updated March 6, 2026. DOI: 10.28929/249.

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