IALARM: An intelligent alert language for activation, response, and monitoring of medical alerts

Denis Klimov, Yuval Shahar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Management of alerts triggered by unexpected or hazardous changes in a patient's state is a key task in continuous monitoring of patients. Using domain knowledge enables us to specify more sophisticated triggering patterns for alerts, based on temporal patterns detected in a stream of patient data, which include both the temporal element and significant domain knowledge, such as "rapidly increasing fever" instead of monitoring of only raw vital signals, such as "temperature higher than 39 C". In the current study, we introduce iALARM, a two-tier computational architecture, accompanied by a language for specification of intelligent alerts, which represents an additional computational [meta] level above the temporal-abstraction level. Alerts in the iALARM language consist of (a) the target population part (Who is to be monitored?); (b) a declarative part (What is the triggering pattern?), i.e., a set of time and value constraints, specifying the triggering pattern to be computed by the bottom tier; and (c) a procedural part (How should we raise the alarm? How should we continue the monitoring and follow-up?), i.e., an action or a whole plan to apply when the alert is triggered, and a list of meta-properties of the alert and action. One of our underlying principles is to avoid alert fatigue as much as possible; for instance, one can specify that a certain alert should be activated only the first time that the triggering pattern is detected, or only if it has not been raised over the past hour. Thus, we introduce a complete life cycle for alerts. Finally, we discuss the implied requirements for the knowledgeacquisition tool and for the alert monitoring and procedural application engines to support the iALARM language. We intend to evaluate our architecture in several clinical domains, within a large project for remote patient monitoring.

Original languageEnglish
Title of host publicationProcess Support and Knowledge Representation in Health Care - AIME 2013 Joint Workshop, KR4HC 2013/ProHealth 2013, Revised Selected Papers
Pages128-142
Number of pages15
DOIs
StatePublished - 1 Dec 2013
EventAIME 2013 Joint Workshop on Knowledge Representation for Healthcare and Process-Oriented Information Systems in Healthcare, KR4HC 2013/ProHealth 2013 - Murcia, Spain
Duration: 1 Jun 20131 Jun 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8268 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceAIME 2013 Joint Workshop on Knowledge Representation for Healthcare and Process-Oriented Information Systems in Healthcare, KR4HC 2013/ProHealth 2013
Country/TerritorySpain
CityMurcia
Period1/06/131/06/13

Keywords

  • Alert
  • Medical informatics
  • Monitoring, Knowledge representation
  • Temporal abstraction
  • Temporal reasoning

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