Title :
Wireless clinical alerts for critical medication, laboratory and physiologic data
Author :
Shabot, M. Michael ; LoBue, Mark ; Chen, Jeannie
Author_Institution :
Dept. of Surgery, Pharmacy & Enterprise Inf. Services, Cedars-Sinai Med. Center, Los Angeles, CA, USA
Abstract :
Clinical information systems (CIS) are increasingly employed to manage the information associated with hospital and Intensive Care Unit (ICU) patients. CIS are typically interfaced to a variety of other systems which provide bedside physiologic data, laboratory results and medication information for video displays and reports. However, having all this information together in electronic format provides an opportunity to detect critically adverse patient conditions, which may be complex. The authors have devised a software system which extracts all pertinent information from the CIS on a continuous basis and sends the data through a series of event detection algorithms. These algorithms are configured to detect critically abnormal physiologic and laboratory values, critical trends and critical indicators of drug reactions and side effects. Once an alert is detected, the software system codes it into a readable alphanumeric alert message and automatically sends it to a commercial paging system. Alerts are received on pagers carried by designated physicians and pharmacists who can take immediate actions to reverse the alert condition.
Keywords :
data analysis; encoding; medical information systems; paging communication; CIS; Intensive Care Unit; alert condition; bedside physiologic data; clinical information systems; commercial paging system; critical indicators; critical medication; critically abnormal physiologic values; critically adverse patient conditions; designated physicians; drug reactions; electronic format; event detection algorithms; hospital; laboratory results; medication information; pharmacists; physiologic data; readable alphanumeric alert message; side effects; software system; video displays; wireless clinical alerts; Clinical diagnosis; Computational Intelligence Society; Data mining; Displays; Event detection; Hospitals; Information management; Laboratories; Software algorithms; Software systems;
Conference_Titel :
System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on
Print_ISBN :
0-7695-0493-0
DOI :
10.1109/HICSS.2000.926784