Specificity Improvement for Network Distributed Physiologic Alarms Based on a Simple Deterministic Reactive Intelligent Agent in the Critical Care Environment
Purchase on Springer.com
$39.95 / €34.95 / £29.95*
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.
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.
- Evans RS, Johnson KV, Flint VB, Kinder AT, Hawley WL, Lyon CR, Vawdrey DK, Thomsen GE. Unit-wide notification of ventilator disconnections. AMIA Annu Symp Proc 2005; 951.
- McGregor JC, Weekes E, Forrest GN, Standiford HC, Perencevich EN, Furuno JP, Harris AD. Impact of a computerized clinical decision support system on reducing inappropriate antimicrobial use: a randomized controlled trial. J Am Med Inform Assoc 2006; 13: 378–384. CrossRef
- Kucher N, Koo S, Quiroz R, Cooper JM, Paterno MD, Soukonnikov B, Goldhaber SZ. Electronic alerts to prevent venous thromboembolism among hospitalized patients. N Engl J Med 2005; 352: 969–977. CrossRef
- Imhoff M, Kuhls S. Alarm algorithms in critical care monitoring. Anesth Analg 2006; 102: 1525–1537. CrossRef
- Lawless ST. Crying wolf: false alarms in a pediatric intensive care unit. Crit Care Med 1994; 22: 981–985. CrossRef
- Chambrin MC, Ravaux P, Calvelo-Aros D, Jaborska A, Chopin C, Boniface B. Multicentric study of monitoring alarms in the adult intensive care unit (ICU): a descriptive analysis. Intensive Care Med 1999; 25: 1360–1366. CrossRef
- Shabot MM, LoBue M, Chen J. Wireless clinical alerts for physiologic, laboratory and medication data. Proc AMIA Symp 2000; 789–793.
- Chen HT, Ma WC, Liou DM. Design and implementation of a real-time clinical alerting system for intensive care unit. Proc AMIA Symp 2002; 11: 131–135.
- 2008 Annual Report of the U.S. Hospital IT Market, HIMSS 2008; 36.
- Schoenberg R, Sands DZ, Safran C. Making ICU alarms meaningful: a comparison of traditional vs. trend-based algorithms. Proc AMIA Symp 1999; 355: 379–383.
- O’Carroll TM. Survey of alarms in an intensive therapy unit. Anaesthesia 1986; 41: 742–744. CrossRef
- Tsien CL, Fackler JC. Poor prognosis for existing monitors in the intensive care unit. Crit Care Med 1997; 25: 614–619. CrossRef
- Shen W, Hao Q, Joong Yoon H, Norrie DH. Applications of agent-based systems in intelligent manufacturing: an updated review. Adv Eng Inform 2006; 20: 415–431. CrossRef
- Carson ER. Artificial intelligence in critical care medicine: EC COST 13 project: report of a mini-symposium held at City University, London, 10–11 December 1987. Int J Clin Monit Comput 1988; 5: 251–257. CrossRef
- Oberli C, Urzua J, Saez C, Guarini M, Cipriano A, Garayar B, Lema G, Canessa R, Sacco C, Irarrazaval M. An expert system for monitor alarm integration. J Clin Monit 1999; 15: 29–35. CrossRef
- Uckun S. Intelligent systems in patient monitoring and therapy management: a survey of research projects. Int J Clin Monit Comput 1994; 11: 241–253. CrossRef
- Specificity Improvement for Network Distributed Physiologic Alarms Based on a Simple Deterministic Reactive Intelligent Agent in the Critical Care Environment
Journal of Clinical Monitoring and Computing
Volume 23, Issue 1 , pp 21-30
- Cover Date
- Print ISSN
- Online ISSN
- Springer Netherlands
- Additional Links
- Patient monitor
- intelligent agent
- Industry Sectors
- Author Affiliations
- 1. 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
- 2. Department of Mechanical Engineering, Ann Arbor, MI, USA