Knowledge-based decision support for patient monitoring in cardioanesthesia.

An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia.

An interactive computer simulator of the circulation for knowledge acquisition in cardio-anesthesia.

Knowledge-based decision support systems for use in cardio-anesthesia can provide online support to the anesthesiologist by generating intelligent alarms. However, the acquisition and validation of a consistent knowledge base for this application bears problems related to the transfer of clinical experiences into a rule system. An interactive simulator of the human circulation is presented that supports the process of knowledge acquisition and testing. The simulator can be controlled in realtime by an anesthesiologist during the simulation run thus providing a basis for interdisciplinary discussion of routine as well as critical situations. The output data can be transferred to a knowledge-based system for test purposes. The simulator is currently being used for the development of the Anesthesia Expert Assist System AES-2. With regard to the special application a model of the heart-function was integrated which enables the simulation of heart insufficiency. Simulation runs under various conditions are presented and discussed. The simulator was implemented on an ATARI ST personal computer.

A knowledge-based approach to intelligent alarms in anesthesia.

The combination and aggregation of separate information sources to generate more ;intelligent' alarms using a knowledge-based approach is described. The approach gas developed as part of the knowledge-based anesthesia decision support system, AES-2, which monitors the patient's physiological state during anesthesia and eventually suggests therapeutic actions. Integration of the alarm system into a conventional information system is discussed. The state variable model used and the modeling of uncertainty are examined. The tools that support knowledge acquisition, design of knowledge-base prototypes. and test of the knowledge base of the AES-2 are described. A simulation example is given.