Development of a research-oriented system for collecting mechanical ventilator waveform data

Gregory B. Rehm, Brooks Kuhn, Jean Pierre Delplanque, Edward C. Guo, Monica K. Lieng, Jimmy Nguyen, Nicholas Anderson, Jason Yeates Adams

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Lack of access to high-frequency, high-volume patient-derived data, such as mechanical ventilator waveform data, has limited the secondary use of these data for research, quality improvement, and decision support. Existing methods for collecting these data are obtrusive, require high levels of technical expertise, and are often cost-prohibitive, limiting their use and scalability for research applications. We describe here the development of an unobtrusive, open-source, scalable, and user-friendly architecture for collecting, transmitting, and storing mechanical ventilator waveform data that is generalizable to other patient care devices. The system implements a software framework that automates and enforces end-to-end data collection and transmission. A web-based data management application facilitates nontechnical end users' abilities to manage data acquisition devices, mitigates data loss and misattribution, and automates data storage. Using this integrated system, we have been able to collect ventilator waveform data from>450 patients as part of an ongoing clinical study.

Original languageEnglish (US)
Pages (from-to)295-299
Number of pages5
JournalJournal of the American Medical Informatics Association
Volume25
Issue number3
DOIs
StatePublished - Mar 1 2018

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Keywords

  • Artificial
  • Intensive care units
  • Mechanical
  • Monitoring
  • Patient ventilator asynchrony
  • Physiologic
  • Respiration
  • Translational medical research
  • Ventilators

ASJC Scopus subject areas

  • Health Informatics

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