A Study Design to Harmonize Patient-Reported Outcomes Across Data Sets

  • McKelvey B
  • Berk A
  • Chin L
  • et al.
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Abstract

PURPOSE Using patient-reported outcomes (PROs) provides important insights from the patient's perspective and can be valuable to monitor and manage treatment-related adverse events during cancer treatment. Additionally , the digital administration of PROs (electronic PROs [ePROs]) provides real-time updates to clinical care teams on treatment-related symptoms in-between clinic visits. However, given the variability in the methodology and timing of the data collection, using and harmonizing these data across different systems remains challenging. Identifying data elements to capture and operating procedures for harmonization across ePRO tools will expedite efforts to generate relevant and robust data on use of ePRO data in clinical care. METHODS Friends of Cancer Research assembled a consortium of project partners from key health care sectors to align on a framework for ePRO data capture across ePRO tools and assessment of the impact of ePRO data capture on patient outcomes. RESULTS We identified challenges and opportunities to align ePRO data capture across ePRO tools and aligned on key data elements for assessing the impact of ePRO data capture on patient care and outcomes. Ultimately, we proposed a study protocol to leverage ePRO data for symptom and adverse event management to measure real-world effectiveness of ePRO tool implementation on patient care and outcomes. CONCLUSION This work provides considerations for harmonizing ePRO data sets and a common framework to align across multiple ePRO tools to assess the value of ePROs for improving patient outcomes. Future efforts to interpret evidence and evaluate the impact of ePRO tools on patient outcomes will be aided by improved alignment across studies.

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APA

McKelvey, B. A., Berk, A., Chin, L., Hudgens, S., Kudel, I., O’Hagan, R. C., … Allen, J. (2023). A Study Design to Harmonize Patient-Reported Outcomes Across Data Sets. JCO Clinical Cancer Informatics, (7). https://doi.org/10.1200/cci.22.00161

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