Designing Granular Consent Tools for Sensitive Health Data: Challenges, User Needs, and Stakeholder Guidance

This study aimed to examine perspectives on challenges, design requirements, and implementation considerations for developing a granular, patient-facing consent tool that enables meaningful control over sensitive health data sharing in real-world healthcare settings.

Guided by the National Science Foundation I-Corps framework and conducted in collaboration with Shift-a national consortium for patient-driven sharing of health information-we conducted semi-structured interviews with 16 expert stakeholders representing clinical, health IT, governance, and policy domains. Transcripts were analyzed using thematic analysis with combined deductive and inductive coding to identify key challenges, user needs, and system constraints.

Participants most frequently emphasized the need for patient-centered, trauma-informed user experiences that recognize prior experiences of stigma, discrimination, surveillance, or harm associated with disclosure of sensitive health information, and that use plain language and education to support meaningful consent (75%). Lack of trust, stigma, and workflow burden were major barriers to sensitive data sharing (63%), alongside technical limitations in EHRs that prevent reliable segmentation and enforcement of preferences (56%). Granular, computable consent-allowing patients' choices-was viewed as essential (50%), though legal and policy fragmentation complicates implementation (50%). Additional considerations included proxy and adolescent-aware configurations (44%) and interoperability standards such as Fast Healthcare Interoperability Resources (FHIR) Consent and Data Segmentation for Privacy (19%).

Findings suggest that effective consent management requires alignment between patient-centered design, technical computability, and governance. Enforceable consent integrated into routine workflows and paired with transparency may reduce stigma-driven nondisclosure while supporting clinical safety. Granular, patient-directed consent can translate privacy expectations into practice. Embedding computable consent within interoperable standards and trauma-informed design offers a path toward more trustworthy, equitable, and safe health data sharing.