Critical Care Bioinformatics at Columbia University Medical Center

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Critical Care Bioinformatics atColumbia
University Medical Center

• J. Michael Schmidt, PhD
• Neurological Institute of New York
• Columbia University College of Physicians and
  Surgeons

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Disclosures

• CMA Microdialysis Speakers Bureau

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Clinical Needs for ICU Informatics System

• Understand patient physiology
• Evaluate effectiveness of treatments
• Potential for automatic processing of data for
  diagnosis and prognosis
• Support clinical decision making
• Also noteworthy
• Digital Note
• Quality Assurance
• Clinical Research support

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Meeting the Need

• 3 problems 1
• Data Collection
• Data Interrogation
• Data Analysis
• Best use of data for clinical decision making

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Columbia Neuro-ICU System
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The GOOD
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• 18 bed ICU
• Useful for threshold based alarms and nursing
  workflow.
• Data only saved for 72 hours then gone.
• Not all device data can go into system
• Difficult to visualize data

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• Saves parameter data every 5 seconds SQL database
• Saves visible waveform data
• Requires 300 GB / year data storage

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• Data from many bedside devices do not interface
  with the bedside monitor
• If they do interface, often ones want greater
  precision or all available parameters

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Data Visualization
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• Visualize data to track effects of interventions
• Can visualize physiologic relationships
• Multi-parameter event detection

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• Collect parameter and waveform data
• Collecting data from devices that do not go into
  monitor
• Able to visualize data over extended periods of
  time

• Can elucidate relationships among different
  parameters
• Data stored permanently

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The BAD
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• Labs available via copy and paste
• Infusion pump data must be manually entered
• Cant get it from EMR
• Cant get it from the pump
• Evaluate effectiveness of interventions
• Did the intervention have the desired effect?
• How quickly?
• Does repeated administrations work equally
  effectively?

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• Tools to evaluate waveforms are lacking in our
  system.
• Phase analysis between MAP and ICP to determine
  autoregulation status.
• Heart rate variability analysis can be used to
  understand dysautonomia.

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The UGLY
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• Network Performance
• Equinox boxes communicate with the server using
  UDP
• Must be in contact with server at least once
  every 60 seconds else goes offline
• Must be rebooted to reestablish the connection
• Some will not go back

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• Network Reliability
• ICU Pilot computers cant always connect to
  servers.
• Server and computer operate on different
  networks. Connection can fail (cant ping
  server).
• Network Drive mapping fails
• Map network drive
• Setup ICU Pilot to use mapped network drive for
  use as the database
• Start SQL client, which fails to connect
  sometimes, or gets corrupted and needs reinstall

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• Standard Informatics infrastructure for hospital
  level system
• Maintenance Server failure lead to corrupted
  database
• Backup was not properly done
• Used recovery tool to get data currently
  running scripts to recover the data will take 2
  years to complete (need to write special program
  to make that faster). Who is going to do that?

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• Standard Informatics infrastructure for hospital
  level system
• Server switch to Virtual server plus problems
  (OLTP versus OLAP)
• I/O disk write time delays as databases got large
• Need separate system for data processing
• Didnt work the same.
• SQL didnt load before bedmaster causing
  problems.
• Processor didnt necessarily always have enough
  resources to meet demand

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Summary of Columbia experience
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• Store data from the patient monitor forever in
  open SQL format
• Can get data from devices that do not plug into
  the patient monitor or do so inadequately
• Able to visualize relationships among parameters

• Infusion pump, intervention, and lab data not in
  system
• Tools not readily available to quantify the
  effectiveness of treatments
• No tools to perform waveform analysis

• Informatics infrastructure not robust.
• Lead to
• Connectivity failures
• Backup systems failed
• Virtual server not up to task.

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• Other data systems not connected
• Have to copy and paste in lab values
• Infusion pump data must be manually entered
• Cant get it from EMR
• Cant get it from the pump
• No good tools to evaluate effectiveness of
  interventions
• Did the intervention have the desired effect?
• How quickly?
• Does repeated administrations work equally
  effectively?
•  No tools for waveform analysis