Literature DB >> 12463801

Design and implementation of a real-time clinical alerting system for intensive care unit.

Hsiao-Ting Chen1, Wun-Chun Ma, Der Ming Liou.   

Abstract

Nowadays many hospitals use clinical information systems (CIS) to improve patient health care and information management. CIS retrieves and manages patient information such as patient administration, laboratory data and medications. Specialized CIS, especially Intensive Care Unit (ICU) CIS, needs to handle more additional information. How to process and make use of this enormous amount of physiologic data generated by ICU is a significant topic in CIS design. We have designed and implemented a real-time clinical alerting system for ICU, which executes alert algorithms on the database records of 63 ICU physiologic parameters. The user can create various alert rules with our rule editor to supervise the values or trends of these parameters. When an alert condition on a specific patient is detected, the system notices the clinicians in charge with mobile phones or pagers. With this functionality, up-to-date patient information is provided for clinicians inverted exclamation mark | use in judging the patient inverted exclamation mark |s condition and making treatment decisions.

Entities:  

Mesh:

Year:  2002        PMID: 12463801      PMCID: PMC2244389     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  7 in total

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  7 in total
  2 in total

1.  Specificity improvement for network distributed physiologic alarms based on a simple deterministic reactive intelligent agent in the critical care environment.

Authors:  James M Blum; Grant H Kruger; Kathryn L Sanders; Jorge Gutierrez; Andrew L Rosenberg
Journal:  J Clin Monit Comput       Date:  2009-01-24       Impact factor: 2.502

Review 2.  Asynchronous automated electronic laboratory result notifications: a systematic review.

Authors:  Benjamin H Slovis; Thomas A Nahass; Hojjat Salmasian; Gilad Kuperman; David K Vawdrey
Journal:  J Am Med Inform Assoc       Date:  2017-11-01       Impact factor: 4.497

  2 in total

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