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Related Concept Videos

Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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General Anesthesia: Overview01:24

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Anesthesia is a medical procedure that uses drugs for CNS suppression to enable painless surgeries and procedures. The selection of anesthetics is influenced by their pharmacokinetic properties, side effects, and patient characteristics. Various types of anesthesia include general, local, regional, spinal, and inhalational.
General anesthesia induces unconsciousness in the whole body, while the others target specific areas or sensations. It is administered to minimize adverse effects, maintain...
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Related Experiment Video

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Visual Analytics to Leverage Anesthesia Electronic Health Record.

Ronald A Kahn1, Jonathan S Gal, Ira S Hofer

  • 1From the Department of Anesthesiology, Perioperative and Pain Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York.

Anesthesia and Analgesia
|September 6, 2022
PubMed
Summary
This summary is machine-generated.

Visualizing anesthesia electronic health record (EHR) data with business intelligence dashboards improves operational efficiency and provides significant cost savings. These dashboards offer near-real-time insights for better supply chain management and enhanced clinical practice compliance.

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Area of Science:

  • Health Informatics
  • Data Visualization
  • Business Intelligence

Background:

  • Visual analytics leverages interactive dashboards for analytical reasoning.
  • Challenges exist in applying visual analytics to anesthesia electronic health record (EHR) data.
  • Business intelligence platforms can be used to address these challenges.

Purpose of the Study:

  • To describe the experience of using a business intelligence platform for visual analytics of anesthesia EHR data.
  • To discuss dashboard performance metrics.
  • To outline operational enhancements and financial savings from dashboard deployment.

Main Methods:

  • EHR data was transferred to departmental servers.
  • Custom SQL queries were used for data extraction and cleaning.
  • Tableau was employed to design dashboards for clinical operation, performance improvement, and business management.

Main Results:

  • Dashboards provided near-real-time case counts from both OR and non-OR locations.
  • Visualizations revealed seasonality in case volumes, enabling supply chain adjustments.
  • Identified systemwide case volumes led to an estimated $250,000 annual cost savings.
  • Central venous pressure (CVP) dashboard improved checklist compliance from 92% to 99%.

Conclusions:

  • Customizing and visualizing EHR data is valuable for improving healthcare provision and practice management.
  • Limitations in EHR data presentation necessitate customization.
  • Continued open access to the underlying data set is crucial.