Applied Digitalization with Real Added Value!

With innovative technology and intelligent assistance systems, TEDIAS and AHEAD generate added value for both patients and medical personnel through digital transformation. Discover how automation, cross-sector data networking, and smart documentation create efficient solutions for healthcare.

• Modular Development Environment: By ensuring data continuity between different systems and orchestrating the entire process, a framework is created in which these components interact and can be easily supplemented or replaced. TEDIAS and AHEAD provide a modular development environment that creates added value by considering real clinical issues, processes, and data from various subsystems. This environment is explicitly open to third-party providers.
• Interdisciplinary Consortium: The TEDIAS and AHEAD consortium brings together an interdisciplinary team of physicians, nurses, engineers, and developers to address and evaluate various aspects of digital solutions in everyday clinical practice.
• Patient Portal and Questionnaires: AHEAD can be integrated into existing patient portals, allowing information uploaded or entered into questionnaires before a hospital stay to be utilized. These data can be supplemented or updated with additional points collected in the hospital.
• Standardized Interfaces and Process Management: By consistently using standardized interfaces and an architecture that integrates additional systems like clinical information systems, diagnostic systems, or patient portals, AHEAD can be embedded into existing systems without creating additional data silos. AHEAD orchestrates processes and data flows, ensuring that newly relevant data points are forwarded to the clinical information system.
• Automated Patient Admission: The TEDIAS cabin, equipped with integrated sensors, a chatbot, and an avatar, enables the automatic collection of relevant vital parameters, standardized questionnaire responses, and patient information. This allows for automated and standardized data collection during patient admission, ensuring structured early availability of results. The goal is to provide complete, structured, and comparable datasets to clinical target systems as early as possible, allowing more time for informed doctor-patient interactions by reducing documentation efforts.
• Use Case – Decision Support System for Outpatient Care: One solution for increasing cost efficiency in healthcare while enhancing patient acceptance is the expansion of outpatient interventions. However, determining which patients benefit from outpatient procedures, what evaluation criteria to use, and how documentation should be structured remain unclear. This has led to a comparatively low rate of outpatient interventions in Germany. Additionally, a valid decision requires numerous data points typically found in different systems, such as home conditions, medication, comorbidities, and intervention progress. AHEAD is ideally suited for this use case, systematically developing evidence-based recommendations for outpatient interventions. The aim is to improve decision-making for shifting treatments to outpatient care while ensuring that inpatient capacities are used more efficiently for complex cases.
• Chatbot: AHEAD enables the execution of a securely isolated local chatbot instance that can answer patient-specific questions. Future developments include matching relevant guidelines with patient-specific data.
• Quality Assurance via PROM: The AHEAD patient journey begins and ends at home. To ensure maximum long-term quality and system security, post-hospitalization data is collected through Patient-Reported Outcome Measures (PROMs).