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Related Concept Videos

SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

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SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
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Calculating subtransient fault currents for three-phase faults in an N-bus power system involves using the positive-sequence network. When a three-phase short circuit occurs at a specific bus, the analysis uses the superposition method to evaluate two separate circuits.
In the first circuit, all machine voltage sources are short-circuited, leaving only the prefault voltage source at the fault location. The positive-sequence bus impedance matrix can be determined by solving the nodal equations,...
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SBAR I: Understanding the Concept01:29

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Effective communication among healthcare professionals during hand-off reporting is essential to delivering safe and continuous patient care. Common professional interactions include reports to healthcare team members, hand-off, and transfer reports. Nurses routinely report information to other healthcare team members and also urgently contact healthcare providers to report changes in patient status.
Standardized methods of communication have been developed to ensure that information is...
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Health Information Technology and Healthcare Information System01:30

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Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
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Cell Diagrams and IUPAC Conventions01:21

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Electrochemical cell notation is a standardized symbolic representation that communicates the structure and reaction pathway of galvanic and electrolytic cells. This notation plays a critical role in describing redox reactions and electrochemical cell configurations without the need for detailed diagrams.In electrochemical cell notation, a single vertical line “|” denotes a phase boundary, such as between a solid electrode and an aqueous solution. A double vertical line...
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Transport Number01:31

Transport Number

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The transport number is the fraction of the total current carried by an ion in an electrolyte solution. It is defined as the ratio of the current carried by a specific ion to the total current flowing through the solution. The transport number, t, is central to understanding ionic mobility, which describes how fast an ion moves under the influence of an electric field. This link connects the physical behavior of ions in solution to the chemical processes that occur during electrochemical...
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The ITS2 Database
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Data interchange using i2b2.

Jeffrey G Klann1, Aaron Abend2, Vijay A Raghavan3

  • 1Partners Healthcare, Boston, MA, USA Harvard Medical School, Boston, MA, USA Massachusetts General Hospital, Boston, MA, USA jeff.klann@mgh.harvard.edu.

Journal of the American Medical Informatics Association : JAMIA
|February 26, 2016
PubMed
Summary
This summary is machine-generated.

Adapting electronic health record (EHR) data for research is slow. Using the Informatics for Integrating Biology and the Bedside (i2b2) project allows rapid reconfiguration of EHR data for new analytical needs without new data extraction, transform, and load (ETL) processes.

Keywords:
PCORnet CDMdata integrationdata modelsinformatics for integrating biology and the bedsidemedical informaticsontology-driven data representationpatient centered outcomes research institute

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Area of Science:

  • Health Informatics
  • Clinical Data Research Networks
  • Data Interoperability

Background:

  • Extracting and transforming electronic health record (EHR) data for research is time-consuming and costly.
  • Developing unique data models for each new research network hinders interoperability.
  • The Informatics for Integrating Biology and the Bedside (i2b2) project offers an ontology-driven approach to data network interoperability.

Purpose of the Study:

  • To develop a method for adapting existing i2b2 data to meet the requirements of new data models, specifically the PCORnet Common Data Model (CDM).
  • To enable participation in data research networks without requiring new data extraction, transform, and load (ETL) processes.
  • To reduce the time and expense associated with data reformatting for research analytics.

Main Methods:

  • Utilized the i2b2 platform as a central hub for data reconfiguration.
  • Developed a process to generate a PCORnet CDM physical database directly from existing i2b2 systems.
  • Created a formalized process for representing i2b2 information models and an information model for CDM Version 1.0.
  • Implemented a program to generate CDM tables driven by the information model, ensuring generalizability.

Main Results:

  • Eight participating sites in the National Patient-Centered Clinical Research Network (PCORnet) Clinical Data Research Network (CDRN) successfully generated a CDM database from their i2b2 systems.
  • This approach eliminated the need for new ETL processes from EHR data at these sites.
  • The implemented methodology enables federated querying within the CDRN and ensures compatibility with the national PCORnet Distributed Research Network.

Conclusions:

  • A method has been established to adapt i2b2 data to new information models without altering the underlying EHR data.
  • This approach has been validated across eight sites, supporting research on 10 million patient records.
  • i2b2 facilitates rapid and cost-effective support for new analytical requirements by eliminating the need for new EHR data extraction processes.