The Digital Health Research Group (DHRG), headed by Kimsey Zajac and Felix Kegel, is an interdisciplinary team dedicated to advancing healthcare through innovative digital solutions. Drawing on business information systems, economics, statistics, and data science, we address key challenges in healthcare information systems with support from industry and government partners. The core competence of the DHRG is focused on the user-oriented evaluation of new technologies and concepts. Thus, our primary objectives include the development and testing of innovations, and the creation of business models and information systems regarding intelligent, effective and efficient healthcare. We pursue the collaborative development of scientific publications by working in an interdisciplinary research environment within these areas of research and application in order to exchange knowledge within both the scientific and practitioner communities.
Digital Health
Our research projects include the BMBF-funded NUM-Guide, which explores evidence-based governance in healthcare, and CAGE-TB, an EU-funded initiative for rapid tuberculosis diagnosis using smartphone audio analysis. We have successfully completed EU-funded initiatives such as the WHO-PEN@Scale project to improve diabetes and hypertension care in the Global South. We are also collaborating with several universities and university hospitals, for example, working with the University Medical Center Göttingen (UMG) on AI-driven medical report analysis and developing MITMed, a BMBF-funded telemedicine solution to improve video-based psychotherapy.
Together, we are shaping the future of digital healthcare to enhance patient care and improve health outcomes globally.
Chair of Information Management
Prof. Dr. Lutz M. Kolbe
Head of DHRG
MZG 8th Floor
Platz der Göttinger Sieben 5
37073 Göttingen
Phone: +49 (0)551 / 39 - 21202 and 39 - 21196
Fax +49 (0)551 / 39 - 9735
-DHRG Team-
Core competences and fields of application of the DHRG
Development and experimental testing of digital health solutions and business models.
Acceptance research regarding new healthcare information systems (via user surveys or methodical analysis, e.g. structural equation modeling).
Development of information systems in the context of healthcare and well-being (such as online platforms and mobile applications).
Application of data mining, machine learning and artificial intelligence to derive health-related information and knowledge from data.
Research Projects
Present
Past
Excerpt of Research Papers
Braun, M., Greve, M., Brendel, A. B., & Kolbe, L. M. (2023). Humans supervising Artificial intelligence – Investigation of Designs to optimize error detection. Journal of Decision Systems, 1–26. [VHB: B] https://doi.org/10.1080/12460125.2023.2260518
Kegel, F., Schnell, K., Zajac, K., & Kolbe, L. M. (2023): How Do You Feel? Intentions to Use Embodied Interaction in Video-Based Psychotherapy, Proceedings of the 44th International Conference on Information Systems (ICIS), Hyderabad, India [VHB: A]
Braun, M.; Kolbe, L. M.; Neumann, C (2023): Natural Language Processing for Medical Texts – A Taxonomy to Inform Integration Decisions into Clinical Practice, Proceedings of the 44th International Conference on Information Systems (ICIS), Hyderabad, India [VHB: A]
Braun, M.; Greve, M.; Gnewuch, U (2023): The New Dream Team? A Review of Human-AI Collaboration Research From a Human Teamwork Perspective, Proceedings of the 44th International Conference on Information Systems (ICIS), Hyderabad, India [VHB: A]
Zajac, K., Braun, M., Klein, J., Kolbe, L.M. (2024): Towards Digital Health Equity? - Assessing the Inclusivity of National Digital Health Strategies for Vulnerable Groups, European Conference on Information Systems (ECIS), Paphos, Cyprus [VHB: A]
Aslan, A., Greve, M., Braun, M., Kolbe, L. M. (2022): Doctors’ Dilemma – Understanding the Perspective of Medical Experts on AI Explanations, Proceedings of International Conference on Information Systems (ICIS), 1-17 [VHB 3: A]
