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We Need Granular Sharing of De-Identified Data—But Will Patients Engage? Investigating Health System Leaders’ and Patients’ Perspectives on A Patient-Controlled Data-Sharing Platform

  • Xi Lu
  • , Di Hu
  • , An T. Nguyen
  • , Brad Morse
  • , Lisa M. Schilling
  • , Kai Zheng
  • , Michelle S. Keller
  • , Lucila Ohno-Machado
  • , Yunan Chen
  • University of California at Irvine
  • Cedars-Sinai Medical Center
  • University of Colorado Anschutz Medical Campus
  • University of Southern California
  • Yale

Research output: Contribution to journalArticlepeer-review

Abstract

Patient-controlled data-sharing systems are increasingly promoted as a way to empower patients with greater autonomy over their health data. Yet it remains unclear how different stakeholders, especially patients and health system leaders, perceive the benefits and challenges of enabling granular control over the sharing of de-identified medical data for research. To address this gap, we developed a high-fidelity prototype of a patient-controlled, web-based consent platform and conducted a two-phase mixed-methods study: semi-structured interviews with 16 health system leaders and a survey with 523 patient participants. While both groups appreciated the potential of such a platform to enhance transparency and autonomy, their views diverged in meaningful ways. Leaders viewed transparency and granular control through the lens of informed consent and institutional ethics, whereas patients interpreted these factors as safeguards against potential risks and uncertainties. Our findings underscore critical tensions such as individual control and research integrity. We offer design implications for building trustworthy, context-aware systems that support flexible granularity, provide ongoing benefit‑centered transparency, and adapt to diverse literacy and privacy needs.

Original languageEnglish
Article numberCSCW043
JournalProceedings of the ACM on Human-Computer Interaction
Volume10
Issue number2
DOIs
StatePublished - Apr 2026

Keywords

  • Data Sharing
  • De-Identified Data
  • Health System Leader
  • Medical Data
  • Medical Health Data
  • Patient
  • Stakeholder

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