# Trust Performance Indicators and Trust Stress Tests: A Conceptual Proposition for Trustworthy Health Data Spaces

## TL;DR

This paper proposes two methods to assess and strengthen trust in health data spaces: trust performance indicators and trust stress tests.

## Contribution

The novel contribution is introducing Trust Performance Indicators and Trust Stress Tests as tools to evaluate and enhance trustworthiness in health data spaces.

## Key findings

- Trust Performance Indicators can collect routine data to evaluate trust-building principles in HDS.
- Trust Stress Tests help design resilient HDS architectures by identifying future scenarios that could undermine trustworthiness.

## Abstract

The development of trustworthy Health Data Spaces (HDS) is currently in the spotlight of digital health policy. Diverse stakeholders agree on the importance of trust for the adoption and legitimacy of HDS. This emphasis on trust has led to the development of conceptual work describing what trust in HDS entails, along with initial suggestions on how trust principles can be operationalized in HDS governance and architecture. In contrast, little research has been conducted on methods to evaluate the performance of trust-building principles and the overall trustworthiness of HDS. In response, we propose two distinct methodologies that share a common focus on assessing trustworthiness: A) Trust Performance Indicators collect routine data related to trust-building principles. B) Trust Stress Tests support the design of resilient HDS architectures by identifying potential future scenarios that could undermine their trustworthiness. Through these methodologies, we aim to contribute to the ongoing development of trustworthy HDS.