Article

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

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.
International Journal of Clinical Monitoring and Computing (Impact Factor: 1.45). 02/2009; 23(1):21-30. DOI: 10.1007/s10877-008-9159-3
Source: PubMed

ABSTRACT 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.

1 Follower
 · 
140 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This third and final installment of this series on innovative designs for the smart ICU addresses the steps involved in conceptualizing, actualizing, using, and maintaining the advanced ICU informatics infrastructure and systems. The smart ICU comprehensively and electronically integrates the patient in the ICU with all aspects of care, displays data in a variety of formats, converts data to actionable information, uses data proactively to enhance patient safety, and monitors the ICU environment to facilitate patient care and ICU management. The keys to success in this complex informatics design process include an understanding of advanced informatics concepts, sophisticated planning, installation of a robust infrastructure capable of both connectivity and interoperability, and implementation of middleware solutions that provide value. Although new technologies commonly appear compelling, they are also complicated and challenging to incorporate within existing or evolving hospital informatics systems. Therefore, careful analysis, deliberate testing, and a phased approach to the implementation of innovative technologies are necessary to achieve the multilevel solutions of the smart ICU.
    Chest 04/2014; 145(4):903-12. DOI:10.1378/chest.13-0005 · 7.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Alarm fatigue desensitizes nurses to alarm signals and presents potential for patient harm. This project describes an innovative method of communicating cardiac monitor alarms to pagers using an alarm escalation algorithm. This innovation was tested on 2 surgical progressive care units over a 6-month period. There was a significant decrease in mean frequency and duration of high-priority monitor alarms and improvement in nurses' perception of alarm response time, using this method of alarm communication.
    Journal of nursing care quality 08/2013; 29(1). DOI:10.1097/NCQ.0b013e3182a61887 · 1.09 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Physicians in the Intensive Care Unit (ICU) are specially trained to deal constantly with very large and complex quantities of clinical data and make quick decisions as they face complications. However, the amount of information generated and the way the data are presented may overload the cognitive skills of even experienced professionals and lead to inaccurate or erroneous actions that put patients' lives at risk. In this paper, we present the design, development, and validation of iOSC3, an ontology-based system for intelligent supervision and treatment of critical patients with acute cardiac disorders. The system analyzes the patient's condition and provides a recommendation about the treatment that should be administered to achieve the fastest possible recovery. If the recommendation is accepted by the doctor, the system automatically modifies the quantity of drugs that are being delivered to the patient. The knowledge base is constituted by an OWL ontology and a set of SWRL rules that represent the expert's knowledge. iOSC3 has been developed in collaboration with experts from the Cardiac Intensive Care Unit (CICU) of the Meixoeiro Hospital, one of the most significant hospitals in the northwest region of Spain.
    Computational and Mathematical Methods in Medicine 02/2013; 2013:650671. DOI:10.1155/2013/650671 · 1.02 Impact Factor