MEDICINE 4.0—Interplay of Intelligent Systems and Medical Experts

Healthcare professionals often have to take decisions under time constraints within a highly complex patient situation. This risky and error-prone process is fuelled additionally by an information overload due to sensor data, guidelines and ongoing updates of clinical information. Healthcare professionals need all of their experience and a lot of good luck to manage their decisions in this complex context. Acting under serious time pressure means having not enough time to gather, analyse and combine existing information. Suboptimal or wrong decisions may occur. A solution to guide and support healthcare professionals are Clinical Decision Support (CDS) systems. Today, there are many isolated CDS systems in a clinical environment causing tremendous maintenance efforts. This is one of the main drivers to centralize the authoring, maintenance and use of clinical knowledge with the help of Clinical Knowledge Management (CKM). Digitization, Artificial Intelligence (AI) applications and CKM also involves new knowledge processes, job roles and organization principles. There are new ways how experts, knowledge engineers and information technology interacts. This article describes the components of a CKM and the interplay of related job roles, limitations and challenges, and the implications of AI, CDS and CKM systems for healthcare organisations and healthcare professionals.