The PATRICIA project: a semantic-based methodology for intelligent monitoring in the ICU

Addressing the flaws of current critical alarms: a fuzzy constraint satisfaction approach

OBJECTIVES

Threshold alarms, the support supplied by commercial monitoring devices to supervise the signs that pathologies produce over physiological variables, generate a large amount of false positives, owing to the high number of artifacts in monitoring signals, and they are not capable of satisfactorily representing and identifying all monitoring criteria used by healthcare staff. The lack of an adequate support for monitoring the evolution of physical variables prevents the suitable exploitation of the information obtained when monitoring critical patients. This work proposes a solution for designing intelligent alarms capable of addressing the flaws and limitations of threshold alarms.

MATERIALS AND METHODS

The solution proposed is based on the multivariable fuzzy temporal profile (MFTP) model, a formal model for describing certain monitoring criteria as a set of morphologies defined over the temporal evolution of the patient's physiological variables, and a set of relations between them. The MFTP model represents these morphologies through a network of fuzzy constraints between a set of points in the evolution of the variables which the physician considers especially relevant. We also provide a knowledge acquisition tool, TRACE, with which clinical staff can design and edit alarms based on the MFTP model.

RESULTS

Sixteen alarms were designed using the MFTP model; these were capable of supervising monitoring criteria that could be satisfactorily supervised with commercial monitoring devices. The alarms were validated over a total of 196h of recordings of physiological variables from 78 different patients admitted to an intensive care unit. Of the 912 alarm triggerings, only 7% were false positives. A study of the usability of the tool TRACE was also carried out. After a brief training seminar, five physicians and four nurses designed a number of alarms with this tool. They were then asked to fill in the standard System Usability Scale test. The average score was 68.2.

CONCLUSION

The proposal presented herein for describing monitoring criteria, comprising the MFTP model and TRACE, permits the supervision of monitoring criteria that cannot be represented by means of thresholds, and makes it possible to construct alarms that give a rate of false positives far below that for threshold alarms.

Information analysis and validation of intelligent monitoring systems in intensive care units

Validation of intelligent systems is an important task to perform. Typically the results of the validation analysis are used to verify whether or not the system satisfies the initial design requirements, and to acquire new knowledge and/or refine the knowledge already acquired. In practice, the validation of intelligent systems usually requires the application of several different techniques (e.g., retrospective, prospective, quantitative). In this work the authors present the methodology devised to validate PATRICIA: an intelligent monitoring system designed to advise clinicians on the management of patients dependent on mechanical ventilation. The application of this methodology requires that appropriate validation paradigms are selected, depending on both the application domain and the characteristics of the intelligent system. The article also presents and discusses validation results.