Artificial intelligence in the Care Process

Project ViKI pro: AI-based Organization, Design and Evaluation in Long-term Care

Inpatient care for people in need of nursing care in Germany is facing several challenges at once. Demographic change is leading to a growing number of people in need of care, the care sector is suffering from an increasing shortage of skilled workers, the relevant nursing expertise is becoming ever more extensive, and complex care situations require profound, high-quality decisions in a short time. Digital support for the care process offers a great opportunity to meet these challenges.

Decision Making in Care Planning Based on Evidence and Expertise

In the ViKI pro project, we are working with partners from nursing science, nursing practice, technology and industry to develop a web application for digitally assisted care planning. This application enables care experts to identify individual care needs and plan appropriate measures on the basis of digitized expertise. The documentation of the implemented care measures in the web application serves as a basis for gaining experiential knowledge that can be used in future similar planning situations. This digital support for processes is intended to improve the quality of care in inpatient care while conserving existing scarce resources.

Concept Project ViKi pro
© freepik / Fraunhofer ITWM
Concept Project ViKi pro

Ai-Based Data Analysis and Multi-Criteria Decision Support

Digitally assisted care planning uses artificial intelligence (AI) methods and mathematical decision making. The nursing expertise is made available in the form of a rule-based system whose automatic evaluation on a nursing case to be planned provides the nursing measures in question. Based on these suggested measures, nursing experts make decisions with the help of interactive planning features. This process is repeated after each change of the nursing case in the style of sequential decision making.

The evaluation of documented nursing actions is performed using AI methods specifically designed for the analysis of sparse data. The empirical data obtained in this process is integrated into the existing knowledge base using methodological concepts of explainable artificial intelligence.

Project Partners

  • German Institute for Applied Nursing Research e.V.
  • August-Wilhelm Scheer Institute gGmbH
  • Connext Communication GmbH
  • Johanniter Senior Citizens' Homes GmbH
  • Caritas Betriebsführungs- und Trägergesellschaft GmbH
  • AOK Federal Association

Project Funding and Duration

The project is funded by the program »Together through Innovation – Interactive Technologies for Health and Quality of Life« of the Federal Ministry of Education and Research (BMBF). The project started on August 01, 2022 and is scheduled for three years.