Health Data for Action (HD4A), a signature research program of the Health Data for Action (HD4A), a signature research program of the Robert Wood Johnson Foundation (RWJF) administered by AcademyHealth, made access to big datasets available to researchers through competitive calls for proposals so they could use that data to answer important research questions and inform health policy -- questions that might otherwise go unstudied.
In this fourth installment of our series, moderated and facilitated by Kevin McAvey, Managing Director, Manatt Health, we explore why representative data on the LGBTQ community is critical for understanding and addressing health disparities.
Tailored Interventions Require Representative Data
Listen to 2024 HD4A grantee, Dr. Carl Streed Jr., Associate Professor, Boston University, highlight the cardiovascular health disparities that sexual and gender minority (SGM) individuals face compared to their straight cisgender peers. This interview is particularly significant at a time when the current administration is removing public health data, including data on SGM individuals. In this conversation, Carl discusses the critical and timely work being done to understand and address the cardiovascular risks and unique stressors faced by the LGBTQI+ community. Throughout the interview, Carl emphasizes the importance of having representative data to develop tailored interventions at both the individual and population-level to improve health outcomes and equity for SGM individuals.
Minority Stress, Missing Data, and the Risks of Erasure
- Minority Stress Theory: While everyone experiences unique forms of stress, not everyone is targeted due to their identity or its perceived value in society. The Minority Stress Theory suggests that SGM populations face unique stressors due to their identity that contribute to worse health outcomes. This discussion emphasized the need for targeted interventions and policy changes to address inequitable treatment based on identity.
- Importance of Representative Data in Electronic Health Records (EHR): Given the US health centers’ requirement for collecting Sexual Orientation and Gender Identity (SOGI) information in Electronic Health Records (EHR), this data source allows researchers to dive deep into specific health disparities and risk profiles within various sexual and gender minority groups.
- Federal Influences on Next Generation of Researchers and Clinicians: The federal actions targeting the removal of LGBTQ and SGM populations from surveillance and health records not only affect data collection but could also impact the next generation of scientists and clinicians. It may limit their chances to learn the skills and knowledge they need to understand and support SGM communities. Additionally, it may result in fewer clinicians being able to provide the appropriate care for these communities.
- Importance of Collaborating with Subject Matter Experts: This discussion underscored the importance of working with individuals who have a deep understanding of the data, familiarity with the research topic, and understanding of the specific population being studied, especially when developing research questions and using data resources.
What surprised you?
Populations who are less accepted by their communities are more likely to experience worse outcomes across various risk factors and outcomes. For instance, bisexual cisgender individuals may be more susceptible to cardiovascular and other health risks than straight, cisgender, and lesbian and gay counterparts, due to the isolation and discrimination they face from both society at large and even within lesbian and gay communities. This issue highlights the importance of exploring granular data to understand risk factors affecting specific subsets within the SGM population. Carl and his team are tackling this research question through their HD4A project, with a particular focus on the bisexual and transgender populations.
Join us for this year’s Health Datapalooza on September 4 and 5 in Washington D.C. We’ll have interactive workshops, unconference sessions, and networking opportunities for data innovation stakeholders to exchange ideas and expertise.
Earlier interviews in this series are available here. LibreChat was utilized to generate key takeaways from the interview transcript. The substance of the post was written by a human author.