Specificity improvement for network distributed physiologic alarms based on a simple deterministic reactive intelligent agent in the critical care environment.
Automated physiologic alarms are available in most commercial physiologic monitors. However, due to the variability of data coming from the physiologic sensors describing the state of patients, false positive alarms frequently occur. Each alarm requires review and documentation, which consumes clini...
| Published in: | Journal of Clinical Monitoring & Computing Vol. 23; no. 1; pp. 21 - 31 |
|---|---|
| Main Authors: | , , , , , , , , , |
| Format: | research Journal Article |
| Published: |
Springer Nature
Feb2009
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105468681&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105468681 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13871307 OHC jtl: Journal of Clinical Monitoring & Computing issn: 13871307 maglogo: N pubinfo: dt: Feb2009 vid: 23 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105468681 36844901 NLM19169835 2010211974 10.1007/s10877-008-9159-3 NLM19169835 105468681 ppf: 21 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Specificity improvement for network distributed physiologic alarms based on a simple deterministic reactive intelligent agent in the critical care environment. aug: au: Blum JM Kruger GH Sanders KL Gutierrez J Rosenberg AL Blum, James M Kruger, Grant H Sanders, Kathryn L Gutierrez, Jorge Rosenberg, Andrew L affil: Department of Anesthesiology and Critical Care, The University of Michigan Health Systems, 4172 Cardiovascular Center/SPC 5861, 1500 East Medical Center Drive, Ann Arbor, MI 48109-5861, USA sug: subj: Algorithms Artificial Intelligence Computer Communication Networks Critical Care Methods Diagnosis, Computer Assisted Methods Equipment Failure Monitoring, Physiologic Methods Diagnosis, Computer Assisted Equipment and Supplies Monitoring, Physiologic Equipment and Supplies Reproducibility of Results Sensitivity and Specificity Human ab: Automated physiologic alarms are available in most commercial physiologic monitors. However, due to the variability of data coming from the physiologic sensors describing the state of patients, false positive alarms frequently occur. Each alarm requires review and documentation, which consumes clinicians' time, may reduce patient safety through 'alert fatigue' and makes automated physician paging infeasible. To address these issues a computerized architecture based on simple reactive intelligent agent technology has been developed and implemented in a live critical care unit to facilitate the investigation of deterministic algorithms for the improvement of the sensitivity and specificity of physiologic alarms. The initial proposed algorithm uses a combination of median filters and production rules to make decisions about what alarms to generate. The alarms are used to classify the state of patients and alerts can be easily viewed and distributed using standard network, SQL database and Internet technologies. To evaluate the proposed algorithm, a 28 day study was conducted in the University of Michigan Medical Center's 14 bed Cardiothoracic Intensive Care Unit. Alarms generated by patient monitors, the intelligent agent and alerts documented on patient flow sheets were compared. Significant improvements in the specificity of the physiologic alarms based on systolic and mean blood pressure was found on average to be 99% and 88% respectively. Even through significant improvements were noted based on this algorithm much work still needs to be done to ensure the sensitivity of alarms and methods to handle spurious sensor data due to patient or sensor movement and other influences. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|