Smart Vitality Care: Intelligent Information Logistics for People-Centered Care

Project background

Professional nursing is under enormous pressure due to demographic change and the severe shortage of skilled workers. Compounding the problem is the fact that the current software landscape consists of confusing and fragmented siloed solutions. Instead of making day-to-day care easier, complicated systems and endless amounts of data drastically increase the cognitive load on staff. This is exactly where SVC is setting a new standard: We want to move away from stressful and time-consuming “click-work” and toward a genuine “joy of use” in daily work with digital systems. 

To date, there has been a lack of robust research on how AI systems can be integrated into everyday nursing practice in an intuitive and user-centered way. 

The development project centers on two pillars of research:

• Smart Vitality Dashboard (SVD): An adaptive, AI-supported user interface that intuitively prioritizes information at critical moments.

• SVC Catalog (SVK): An open knowledge catalog based on FAIR principles that documents proven combinations of sensors, software, and use cases and makes them accessible to users.

In addition, the project follows a consistent “privacy by design” approach: The AI does not learn from sensitive patient data but uses only anonymized interaction patterns from healthcare professionals.

Project objective

As part of the project, researchers will explore and evaluate an AI-powered, open-source ecosystem designed to protect nursing staff from daily information overload and significantly ease the stress of their daily work, rather than making it even more difficult with complicated systems. The goal of the SVC ecosystem is to motivate staff, reduce frustration, and actively strengthen their clinical competence. This is ensured through active co-creation. A research-based setup for AI deployment is being developed in collaboration with nursing professionals.

SVC aims to build a strong interdisciplinary, multi-stakeholder network as the foundation for AI-in-nursing research in Bavaria and, through the “Scaling Strategy 2035,” to develop a sustainable roadmap for integration into standard care. The goal is to strengthen digital sovereignty and sustainably promote Innovation in the Bavarian healthcare sector—while consistently upholding “privacy by design.”

Project procedure

SVC conducts research at the intersection of nursing science, medical informatics, and artificial intelligence. To address the complex challenges of the nursing landscape, SVC relies on extensive and interdisciplinary collaboration among teams specializing in nursing research & evaluation, AI & Design, and Technology & Development. 

This effort is supported by close collaboration between Rosenheim University of Applied Sciences and Munich University of Applied Sciences, together with MyOn Clinic GmbH. 

Methodologically, the development follows a participatory co-creation design approach. Through iterative, agile cycles, potential solutions are developed in collaboration with nursing practitioners. Testing takes place in stages, beginning in controlled laboratory settings and progressing to implementation under real-world conditions at partner facilities in outpatient care and inpatient long-term care. The goal is a digital tool researched by and for healthcare professionals, featuring intelligent information logistics, designed to reduce cognitive load.

Innovation

The key driver of innovation is, above all, the consistent "privacy by design" approach: Unlike many AI systems in the healthcare sector, the AI examined in this project never learns from sensitive patient data. Instead, the recommender engine relies exclusively on anonymized interaction patterns from the nursing staff themselves. This avoidance of patient data in training—combined with genuine co-creation with nursing practice and an open FAIR knowledge catalog (SVK)— has rarely been tested in a nursing context to date.

In addition, nurses gain access to tools that ease their workload without raising data privacy concerns. Care facilities can use AI without disclosing patient data—a key factor in its acceptance. The HealthTech industry gains a model for data-protection-compliant AI development, and the Bavarian healthcare sector gains a secure, trustworthy foundation for routine care through the “Scaling Strategy 2035.”