Project Summary

The patients’ voice, their living experiences and engagement impacts their behaviors and health outcomes such as symptoms management, severity of the disease and medication adherence. The patients’ voice can be captured by patients outside of the traditional care setting such as through secure messages sent through patient portals, surveys and interview responses, and open-ended questions on patient forms. The patients’ voice includes expressions of empathy and gratefulness, attitudes, concerns, and social determinants of health that are important to outcomes. 

To date, patient-centered methods have not incorporated the patients’ voice as another data point for a thorough description of the role they play in clinical outcomes, primarily due to the nonavailability of the patients’ voice in a structured form in the electronic health record and the challenges associated with extracting it from text narratives. This study seeks to advance patient-centered research methods by extracting the patients’ voice from qualitative text data using advanced machine learning approaches. 

To this end, the research team will compose a lexicon of the different patients’ voice domains and develop a tool called PVminer that will automatically extract those domains from qualitative textual data. While this type of data presents an opportunity to measure patients’ voice domains in large groups of patients and providers, PVminer offers a great benefit of identifying hidden domains of the patient voice – attitudes, concerns, quality of life and social determinants of health that might help explain changes in outcomes such as severity of the disease and medications adherence.

Project Information

Samah Fodeh, M.S., Ph.D.
Yale University
$1,049,995 *

Key Dates

36 months *
April 2024

*All proposed projects, including requested budgets and project periods, are approved subject to a programmatic and budget review by PCORI staff and the negotiation of a formal award contract.


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Last updated: April 23, 2024