# Ethical sourcing in the context of health data supply chain management: a value sensitive design approach

## TL;DR

This paper introduces a framework combining ethical design and supply chain management to create trustworthy health data repositories for AI/ML research.

## Contribution

A novel integration of Value Sensitive Design and Supply Chain Management to operationalize ethical sourcing in health data repositories.

## Key findings

- Identified actors, values, and tensions influencing ethical sourcing in health data repositories.
- SCM steps provide scaffolding for ethical sourcing across pre-model stages of repository development.
- Foundational decisions impact repository quality and AI/ML usability through traceability and risk management.

## Abstract

The Bridge2AI program is establishing rules of practice for creating ethically sourced health data repositories to support the effective use of ML/AI in biomedical and behavioral research. Given the initially undefined nature of ethically sourced data, this work concurrently developed definitions and guidelines alongside repository creation, grounded in a practical, operational framework.

A Value Sensitive Design (VSD) approach was used to explore ethical tensions across stages of health data repository development. The conceptual investigation drew from supply chain management (SCM) processes to (1) identify actors who would interact with or be affected by the data repository use and outcomes; (2) determine what values to consider (ie, traceability accountability, security); and (3) analyze and document value trade-offs (ie, balancing risks of harm to improvements in healthcare). This SCM framework provides operational guidance for managing complex, multi-source data flows with embedded bias mitigation strategies.

This conceptual investigation identified the actors, values, and tensions that influence ethical sourcing when creating a health data repository. The SCM steps provide a scaffolding to support ethical sourcing across the pre-model stages of health data repository development. Ethical sourcing includes documenting data provenance, articulating expectations for experts, and practices for ensuring data privacy, equity, and public benefit. Challenges include risks of ethics washing and highlight the need for transparent, value-driven practices.

Integrating VSD with SCM frameworks enables operationalization of ethical values, improving data integrity, mitigating biases, and enhancing trust. This approach highlights how foundational decisions influence repository quality and AI/ML system usability, addressing provenance, traceability, redundancy, and risk management central to ethical data sourcing.

To create authentic, impactful health data repositories that serve public health goals, organizations must prioritize transparency, accountability, and operational frameworks like SCM that comprehensively address the complexities and risks inherent in data stewardship.