¹Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
²Data Integration Center, Center for Medical Informatics, University Hospital Carl Gustav Carus, Dresden, Germany
³Universität Münster, Münster, Germany

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Introduction: Diversity and inclusion are vital to fostering innovation, equity, and excellence in healthcare and research [1]. Within the field of medical informatics, little is known about how varied demographic factors—such as gender, ethnicity, and other minority statuses – are represented [2]. The German Association for Medical Informatics, Biometry and Epidemiology (GMDS) Diversity Project Group aims to address this knowledge gap through a comprehensive survey on the current state of diversity, perceived inclusivity, and fairness within field of medical informatics in Germany.

Methods: An anonymous, cross-sectional survey will be administered primarily to professionals active in medical informatics in Germany, including members of the GMDS. Recruitment strategies involve email invitations, newsletter announcements and social media posts. The survey is implemented in REDCap [3], hosted on secure Charité servers, ensuring that no personally identifiable information is collected.

Core variables include self-identified demographic data (e.g., gender, minority status), perceptions of inclusivity, and personal experiences of discrimination or barriers in professional settings. Respondents will also be asked about potential improvements or organizational measures that could enhance diversity. Sample-size calculations suggest a target of at least 250 respondents, enabling 95% confidence interval estimates around minority-group proportions. Descriptive statistics (counts, proportions, confidence intervals) and basic comparative analyses (e.g., weighting for GMDS vs. non-GMDS participants) will be conducted.

Results: Data collection is scheduled for three months. Preliminary endpoints will include the proportion of participants identifying as members of minority groups, their perceived inclusivity within medical informatics settings, and overall fairness in professional contexts. We will further compare subgroup differences where sufficient responses permit. No individual-level identifiers will be collected, minimizing any re-identification risks.

Discussion: By systematically measuring demographic variability and viewpoints on inclusion, this study will provide evidence-based insights into the diversity landscape of medical informatics in Germany. Findings may guide future actions by professional societies, educational institutions, and healthcare organizations to reduce discrimination, eliminate barriers, and foster a more equitable environment. The analysis will also facilitate the development of policy recommendations, potentially shaping a more diverse and inclusive medical informatics community.

Conclusion: This survey constitutes the first step in establishing a robust evidence base on diversity and inclusion within medical informatics in Germany. In doing so, it aims to inspire targeted, data-driven strategies that can promote lasting and meaningful change on both institutional and societal levels.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.

References

[1] Kozlowski D, Larivière V, Sugimoto CR, Monroe-White T. Intersectional inequalities in science. Proc Natl Acad Sci. 2022 Jan 11;119(2):e2113067119.
[2] Bright TJ, Bear Don’t Walk IV OJ, Johnson CE, Petersen C, Dykes PC, Martin KG, et al. The journey to building a diverse, equitable, and inclusive American Medical Informatics Association. J Am Med Inform Assoc JAMIA. 2024 Oct 11;32(1):3–8.
[3] Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019 Jul 1;95:103208.