Bridging the gap between models and reality: development of a research environment for an object-oriented hospital information system to integrate artificial intelligence and robotics into clinical practice.

Introduction: Hospital information systems (HISs) are the main access opportunity for medical professionals to computer-based patient administration. However, current HISs are primarily designed to function as office applications rather than as comprehensive management and supporting tools. Due to their inflexible architecture, integrating modern technologies like artificial intelligence (AI) models and medical robotics (MR) is hindered. Therefore, we have conceptualized an object-oriented HIS (oHIS) as a pragmatic digital twin (PDT) of the entire patient care in a hospital and developed a functional research framework software for further investigations to bridge the gap between reality and models via oHIS.

Material and methods: In an interdisciplinary team of engineers and physicians, we conducted a requirements assessment on the surgical wards of the TUM University Hospital in Munich. Then, we designed the research framework named OMNI-SYS and developed it into a functional research platform capable of bridging the gap between a model management system and real-world agents. Finally, we evaluated the framework simulating a clinical use case.

Results: Our analysis revealed that future-proof HIS is an under-researched topic. The integration of new technologies into clinical practice is not sufficiently prepared. Therefore, our approach could solve this shortcoming allowing for human agents, devices, models, and robots to interact in a PDT. Models can be integrated as quasi-natural objects and interact with representations of tangible objects in real time. This approach enables even the integration of new technologies that are still unimaginable today. Our oHIS research framework enabled a functional object representation in a simulated use case.

Conclusion: oHIS could significantly facilitate the integration of future technologies like AI models and MR. The OMNI-SYS framework could serve as a cornerstone for further research into this new approach. Studies on its clinical application and formalization are already planned in preparation for a possible future standard.