Extended attributes of event monitor systems for criteria-based notification modalities.
The efficacy of event monitors (EMs) at reducing morbidity and mortality of certain clinical conditions (CCs) is well established. In addition, studies have shown that user inverted exclamation mark s preferences on the modality of notification are correlated to the type of reminder or alert. Nonetheless, few institutions have implemented large scale automated monitoring of a considerable number of distinct CCs, and to our knowledge, none of these sizable projects also offer user-customizable communication modalities (CMs) over all monitored conditions. As both the numbers of CMs and CCs increase, the complexity of customizing user preferences amplifies following a geometric progression. This paper demonstrates an automated approach, based on generic notification attributes (NAs) and notification criteria (NC), which significantly simplifies the management and personalization of the CMs for institutions where the manual assignment of a CM for every alert is forbidding. The methods by which these NAs were developed, their significance for existing CCs and their implementation using the Arden Syntax and Guideline interchange format (GLIF) are described. The proposed Criteria-Based Notification is shown to improve two facets of the management of event monitors: 1) the assignment of CMs becomes independent from clinical conditions, de-facto removing institution-specific CMs from the knowledge bases of the event monitors and inserting CC-specific and institution-independent NAs, thus increasing their reusability and sharability; 2) knowledge-based independent NAs facilitate both institution-level management and user-level preference configuration.
Tao
Ying
Y
Department of Medical Informatics, Columbia University, New York, NY, USA.
Wang
Dongwen
D
Shortliffe
Edward H
EH
Lussier
Yves A
YA
D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D006747:Hospital Communication Systems; D006801:Humans; D008991:Monitoring, Physiologic