Delphi Study

Using Data Safely and Fairly to Improve Mental Healthcare

Data plays a crucial role in developing technology tools to improve healthcare. however, using sensitive data from marginalized communities like the LGBTQI+ community requires careful consideration to avoid bias, promote fairness, and ensure representation.

This study aims to:

Establish best practices for collecting, coding, and standardizing data related to Sexual Orientation and Gender Identity (SOGI) for improving mental healthcare. This aims to ensure the data is accurate and consistent.
Determine acceptable ways to reuse SOGI data in data-driven technologies, considering both scenarios where it's clearly unacceptable and those where it might be acceptable with specific safeguards. This includes gaining community input on acceptable and unacceptable uses of their data.

What this study will produce:

A toolkit for AI developers, data scientists, and healthcare institutions. This toolkit, designed with the LGBTQI+ community, will provide best practices for collecting and recording SOGI information accurately and respectfully. While initially focused on mental health, the insights may benefit other healthcare settings.
An online "playbook" with examples. This will provide real-world scenarios of how SOGI data could be used, clearly explaining what's unacceptable and what might be acceptable with specific conditions.
Open-access research papers. These will summarize the study's findings and guide stakeholders like policymakers, institutions, and individuals on using data-driven technology respectfully and ethically when addressing LGBTQI+ mental health needs.

What's not included in this study:

We will only focus on data routinely collected in clinical and healthcare settings, not personal information from social media or self-publishing platforms.
While understanding how healthcare services are designed and delivered is important for LGBTQI+ experiences, this study won't explore factors related to these models as it focuses solely on ways to use data for better care.

By involving the LGBTQI+ community in this study, we aim to build trust and ensure that data-driven technologies are used fairly and inclusively to improve mental healthcare outcomes for the community.

image source: DALL-E

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