Role of large clinical datasets from physiologic monitors in improving the safety of clinical alarm systems and methodological considerations: A case from philips monitors

Azizeh Khaled Sowan, Charles Calhoun Reed, Nancy Staggers

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Large datasets of the audit log of modern physiologic monitoring devices have rarely been used for predictive modeling, capturing unsafe practices, or guiding initiatives on alarm systems safety. Objective: This paper (1) describes a large clinical dataset using the audit log of the physiologic monitors, (2) discusses benefits and challenges of using the audit log in identifying the most important alarm signals and improving the safety of clinical alarm systems, and (3) provides suggestions for presenting alarm data and improving the audit log of the physiologic monitors. Methods: At a 20-bed transplant cardiac intensive care unit, alarm data recorded via the audit log of bedside monitors were retrieved from the server of the central station monitor. Results: Benefits of the audit log are many. They include easily retrievable data at no cost, complete alarm records, easy capture of inconsistent and unsafe practices, and easy identification of bedside monitors missed from a unit change of alarm settings adjustments. Challenges in analyzing the audit log are related to the time-consuming processes of data cleaning and analysis, and limited storage and retrieval capabilities of the monitors. Conclusions: The audit log is a function of current capabilities of the physiologic monitoring systems, monitor's configuration, and alarm management practices by clinicians. Despite current challenges in data retrieval and analysis, large digitalized clinical datasets hold great promise in performance, safety, and quality improvement. Vendors, clinicians, researchers, and professional organizations should work closely to identify the most useful format and type of clinical data to expand medical devices' log capacity.

Original languageEnglish (US)
Article numbere24
JournalJMIR Human Factors
Volume3
Issue number2
DOIs
StatePublished - Jul 1 2016

Keywords

  • Alarm fatigue
  • Audit log
  • Clinical alarms
  • Intensive care unit
  • Large clinical data
  • Nursing
  • Physiologic monitors

ASJC Scopus subject areas

  • Health Informatics
  • Human Factors and Ergonomics

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