Monitoring and Therapy Planning without Effective Data Validation are Ineffective

Abstract

Systems for monitoring and therapy planning, which receive their data from computer-based patient records and on-line monitoring equipment, require reliable data. Reasoning on faulty data can cause unexplainable and lifethreatening conclusions. Effective and efficient data validation methods are needed to arrive at reliable conclusions. We distinguished four categories of data validation and repair based on their underlying temporal ontologies: time-point-, time-interval-, trend-based, and time-independent validation and repair. Observing single measurements is not effective to arrive at trustable data. Therefore we take into account the behavior of parameters in the past as well as knowledge derived from domain experts. Examples from VIE-VENT, a knowledge-based monitoring and therapy-planning system for artificially-ventilated newborns, demonstrate the applicability of these methods. 1 Introduction In the last years, several sophisticated knowledge-based monitoring and therapy-plann..