cii Research Area: Digital Health Systems
Digital transformation causes tremendous shifts in most of today’s industries, including healthcare. Yet, the healthcare sector is notoriously slow in adopting new technologies and modes of work. Reasons for this are manifold and include, amongst others, the complex nature of care activities, complex value networks, and exceptionally high levels of regulation. Although research has acknowledged the slow pace of innovation in healthcare, the COVID-19 pandemic has recently highlighted that there is still much to be done and researched to facilitate the digitization of the healthcare sector in a meaningful way. Our research in this area focuses on contemporary issues of digital transformation in healthcare. In particular, we create foundational knowledge, design solutions, and approaches surrounding digital technologies in healthcare and their use by humans.
Artificial intelligence (AI) increasingly disseminates into all walks of life, including healthcare. In some narrow application areas, AI now already surpass humans in performance capabilities, like, for example, analyzing echocardiograms. Nevertheless, many challenges regarding the explainability of AI models, privacy and data protection, and the integration of medical domain expertise into AI models remain. We research the design of and medical professionals' interaction with explainable AI approaches, the implementation of informed machine learning approaches in healthcare, and the protection of sensitive health data during the training of AI models.
Gamification describes the utilization of elements typically found in video games to evoke gameful experiences, while also supporting the completion of instrumental tasks. In healthcare settings, gamified information systems are used to support various instrumental outcomes including fostering healthy lifestyle habits, facilitating the rehabilitation from specific medical conditions, or supporting medical professionals in their daily activities. We research human interaction with immersion-related elements of gamification (i.e., narratives, avatars) in systems supporting physical activity and mental health. Further, our research is concerned with the design of gamified information systems that are used in annotation of laparoscopic surgery images.
Driven by rapidly declining costs of analysis and the emergence of new business models, genetic data have become a rich source of information for various applications. Sharing genetic data with third parties can, however, come with various benefits and risks for the disclosing individual themselves and for blood relatives that share parts of their DNA with them. Thus, the sharing of genetic data increasingly generates tensions between personal and interdependent privacy risks and benefits that individuals trade off against each other when considering sharing their genetic data. We research approaches to ensure genetic privacy as well as individuals' sharing behavior regarding genetic data and apparent personal and interdependent privacy risks.
Leiser, F.; Rank, S.; Schmidt-Kraepelin, M.; Thiebes, S.; Sunyaev, A.
2023. Artificial Intelligence in Medicine, 145, Art.-Nr.: 102676. doi:10.1016/j.artmed.2023.102676
Schmidt-Kraepelin, M.; Thiebes, S.; Warsinsky, S. L.; Petter, S.; Sunyaev, A.
2023. Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 1–9, Association for Computing Machinery (ACM). doi:10.1145/3544549.3585595
Thiebes, S.; Gao, F.; Briggs, R. O.; Schmidt-Kraepelin, M.; Sunyaev, A.
2023. Journal of Management Information Systems, 40 (1), 239–270. doi:10.1080/07421222.2023.2172771
Warsinsky, S.; Schmidt-Kraepelin, M.; Rank, S.; Thiebes, S.; Sunyaev, A.
2021. Journal of medical internet research, 23 (9), Art.-Nr.: e30390. doi:10.2196/30390
Thiebes, S.; Toussaint, P. A.; Ju, J.; Ahn, J.-H.; Lyytinen, K.; Sunyaev, A.
2020. Journal of medical internet research, 22 (1), Article: e14890. doi:10.2196/14890
