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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

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.

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

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.

Paper Structure

This paper contains 36 sections, 3 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Studies on Sharing Medical Record Data for Research
  4. HCI Research on Utilizing Health Data
  5. Concerns and Tensions in Sharing Medical and Health Data
  6. Methodology
  7. High-Fidelity Prototype
  8. Set Up A Granular Default Opt-in/Opt-out Preferences
  9. New Studies Requesting Your Data: A Transparent and Granular Opt-in/Opt-out Approach on Specific Studies
  10. Elaboration: Sharing Reasons for Rejecting Requests or Withholding Data
  11. Consent History: Viewing and Modifying Enrolled Studies
  12. Interview Process
  13. Interview Participants
  14. Survey Design and Process
  15. Survey Participants
  16. ...and 21 more sections

Figures (3)

  • Figure 1: The interface allows patients to have a granular way to set up default opt-in/opt-out for different data types (e.g., demographic information, social and economic information, genetic information, and mental health information).
  • Figure 2: If patients choose "I am interested" for a specific study, they can view detailed consent information and set up data-sharing preferences for each data type that the study wishes to access. In the "study information" page, the system also explains the requester's type (e.g., non-profit or for-profit organizations).
  • Figure 3: (A) If patients select “I am not interested” for a study, the system prompts them to specify their reason for opting out. (B) Patients can also state their reasons for withholding specific types of data when enrolling in a study. (C) The "Consent History" interface. Patients can track all the studies that they have already opted in to and modify their existing data-sharing preferences for an enrolled study. Selecting "MODIFY DATA SHARING PREFERENCE" leads to the "Study Information" page (shown in Figure - \ref{['fig:study_request']}), where users can review and adjust the data previously shared.