Literature DB >> 25224387

Design and implementation of a hospital wide waveform capture system.

James M Blum1, Heyon Joo, Henry Lee, Mohammed Saeed.   

Abstract

The use of telemetry and invasive monitoring is exceptionally common in modern healthcare. To date the vast majority of this information is not stored for more than a brief duration on the local monitor. This prohibits extensive investigation into waveform data. We describe a system to collect such data in a quaternary care facility. Using standardized "packet sniffing" technology along with routine manual documentation, we reverse engineered the Unity network protocol used to transmit waveform data across the University of Michigan mission critical monitor network. Data was subsequently captured using a proprietary piece of software writing waveform data to local disks. Nightly, this data is post-processed using data from the admit-discharge-transfer system into individual patient waveforms for the day regardless of location. Over a 10 month period, over 2,785 individual patients had a total of 65,112 waveforms captured 15,978 from the operating rooms and 49,134 from the ICUs. The average OR case collected over 11 MB of data. The average single day data collection consisted of 8.6 GB of data. Entire hospital waveform data collection is possible using internally developed software enabling research on waveform data with minimal technical burden. Further research is required to determine the long-term storage and processing of such data.

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Year:  2014        PMID: 25224387     DOI: 10.1007/s10877-014-9612-4

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


  4 in total

1.  PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

Authors:  A L Goldberger; L A Amaral; L Glass; J M Hausdorff; P C Ivanov; R G Mark; J E Mietus; G B Moody; C K Peng; H E Stanley
Journal:  Circulation       Date:  2000-06-13       Impact factor: 29.690

2.  Using "off-the-shelf" tools for terabyte-scale waveform recording in intensive care: computer system design, database description and lessons learned.

Authors:  Anton Burykin; Tyler Peck; Timothy G Buchman
Journal:  Comput Methods Programs Biomed       Date:  2010-11-18       Impact factor: 5.428

3.  MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring.

Authors:  M Saeed; C Lieu; G Raber; R G Mark
Journal:  Comput Cardiol       Date:  2002

4.  Accessing the public MIMIC-II intensive care relational database for clinical research.

Authors:  Daniel J Scott; Joon Lee; Ikaro Silva; Shinhyuk Park; George B Moody; Leo A Celi; Roger G Mark
Journal:  BMC Med Inform Decis Mak       Date:  2013-01-10       Impact factor: 2.796

  4 in total
  1 in total

Review 1.  Big Data Analytics in Healthcare.

Authors:  Ashwin Belle; Raghuram Thiagarajan; S M Reza Soroushmehr; Fatemeh Navidi; Daniel A Beard; Kayvan Najarian
Journal:  Biomed Res Int       Date:  2015-07-02       Impact factor: 3.411

  1 in total

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