Fraunhofer Institute for Software and Systems EngineeringIn the DAVINA project, we aim to develop a pioneering Clinical Decision Support System (CDSS) that actively supports anesthetists and patients in individual anesthesia planning. The goal is for patients to be able to share their health data via a user-friendly portal, while our virtual contact person “Davina” educates them about different anesthesia procedures and their risks. The CDSS will use medical guidelines and AI-powered analytics to provide precise, evidence-based therapy recommendations. This way, we intend to strengthen patient engagement, increase the quality of therapy planning, and reduce the workload of medical staff.
DAVINA: Data-driven individualization of the anesthesia procedure in geriatric traumatology
The challenge
Demographic change and the shortage of specialists in the healthcare sector pose significant challenges, particularly in the care of older patients with multiple illnesses (multimorbidity). This requires a precise assessment of postoperative monitoring needs that goes beyond current procedures. Current decisions regarding anesthesia – the procedure used to eliminate pain during surgery – require the consideration of many complex factors, such as previous illnesses and current medication. Often, older patients are confronted with a flood of information that can overwhelm them in stressful moments.
Despite promising developments in artificial intelligence (AI) that could provide support, its application in everyday clinical practice is not yet established. Challenges such as inaccurate algorithms, skepticism towards complex AI models and legal hurdles are hindering progress. There is an urgent need to develop innovative solutions that specifically address the needs of these patients and significantly improve the quality of healthcare.
Our service
To develop the Clinical Decision Support System (CDSS), Fraunhofer ISST is pursuing an integrative approach that combines rule-based decision systems with trustworthy artificial intelligence. The aim is to improve patient-specific, informed consent and to support anesthetists in making medically valid decisions for the peri- and postoperative phase. In close collaboration with all consortium partners, the functional model is being researched and implemented. Data from existing clinical documentation systems is combined with medical guidelines to provide needs-based decision support. The diverse expertise within the consortium enables agile research and development that takes cost-effectiveness and legal compliance into account throughout the entire development proces.
The result
The Clinical Decision Support System (CDSS) leads to a significant improvement in patient involvement in the planning of anesthesia procedures. It enables patients to enter therapy-relevant information in a structured way via a user-friendly portal and to prepare specifically for their informed consent discussions. The integration of trustworthy artificial intelligence supports precise data analysis, which promotes individualized and patient-centered therapy planning in geriatric traumatology. These measures improve decision-making and take into account the specific needs of older patients, thereby increasing the overall quality of health care.
Partners
- MEDLINQ Softwaresysteme GmbH
- DiA42 - Gesellschaft für digitale Medizinprodukte mbH
- Private Universität Witten/Herdecke gGmbH; Lehrstuhl für Anästhesiologie II, Witten
Funding
- German Federal Ministry for Education and Research (Bundesministerium für Bildung und Forschung)
- Funding Code: 13GW0762 A-D
- Duration: 03/2025-02/202
