Retrospective derivation and validation of a search algorithm to identify emergent endotracheal intubations in the intensive care unit

Nathan Smischney, V. M. Velagapudi, J. A. Onigkeit, Brian W Pickering, Vitaly D Herasevich, R. Kashyap

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Background: The development and validation of automated electronic medical record (EMR) search strategies are important in identifying emergent endotracheal intubations in the intensive care unit (ICU). Objective: To develop and validate an automated search algorithm (strategy) for emergent endotracheal intubation in the critically ill patient. Methods: The EMR search algorithm was created through sequential steps with keywords applied to an institutional EMR database. The search strategy was derived retrospectively through a secondary analysis of a 450-patient subset from the 2,684 patients admitted to either a medical or surgical ICU from January 1, 2010, through December 31, 2011. This search algorithm was validated against an additional 450 randomly selected patients. Sensitivity, specificity, and negative and positive predictive values of the automated search algorithm were compared with a manual medical record review (the reference standard) for data extraction of emergent endotracheal intubations. Results: In the derivation subset, the automated electronic note search strategy achieved a sensitivity of 74% (95% CI, 69%-79%) and a specificity of 98% (95% CI, 92%-100%). With refinements in the search algorithm, sensitivity increased to 95% (95% CI, 91%-97%) and specificity decreased to 96% (95% CI, 92%-98%) in this subset. After validation of the algorithm through a separate patient subset, the final reported sensitivity and specificity were 95% (95% CI, 86%-99%) and 100% (95% CI, 98%-100%). Conclusions: Use of electronic search algorithms allows for correct extraction of emergent endotracheal intubations in the ICU, with high degrees of sensitivity and specificity. Such search algorithms are a reliable alternative to manual chart review for identification of emergent endotracheal intubations.

Original languageEnglish (US)
Pages (from-to)419-427
Number of pages9
JournalApplied Clinical Informatics
Volume4
Issue number3
DOIs
StatePublished - 2013

Fingerprint

Intensive care units
Intratracheal Intubation
Intensive Care Units
Electronic medical equipment
Electronic Health Records
Set theory
Sensitivity and Specificity
Critical Care
Critical Illness
Medical Records
Databases

Keywords

  • Electronic medical record
  • Emergent
  • Endotracheal intubation
  • Intensive care unit
  • Search algorithm

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Health Information Management

Cite this

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title = "Retrospective derivation and validation of a search algorithm to identify emergent endotracheal intubations in the intensive care unit",
abstract = "Background: The development and validation of automated electronic medical record (EMR) search strategies are important in identifying emergent endotracheal intubations in the intensive care unit (ICU). Objective: To develop and validate an automated search algorithm (strategy) for emergent endotracheal intubation in the critically ill patient. Methods: The EMR search algorithm was created through sequential steps with keywords applied to an institutional EMR database. The search strategy was derived retrospectively through a secondary analysis of a 450-patient subset from the 2,684 patients admitted to either a medical or surgical ICU from January 1, 2010, through December 31, 2011. This search algorithm was validated against an additional 450 randomly selected patients. Sensitivity, specificity, and negative and positive predictive values of the automated search algorithm were compared with a manual medical record review (the reference standard) for data extraction of emergent endotracheal intubations. Results: In the derivation subset, the automated electronic note search strategy achieved a sensitivity of 74{\%} (95{\%} CI, 69{\%}-79{\%}) and a specificity of 98{\%} (95{\%} CI, 92{\%}-100{\%}). With refinements in the search algorithm, sensitivity increased to 95{\%} (95{\%} CI, 91{\%}-97{\%}) and specificity decreased to 96{\%} (95{\%} CI, 92{\%}-98{\%}) in this subset. After validation of the algorithm through a separate patient subset, the final reported sensitivity and specificity were 95{\%} (95{\%} CI, 86{\%}-99{\%}) and 100{\%} (95{\%} CI, 98{\%}-100{\%}). Conclusions: Use of electronic search algorithms allows for correct extraction of emergent endotracheal intubations in the ICU, with high degrees of sensitivity and specificity. Such search algorithms are a reliable alternative to manual chart review for identification of emergent endotracheal intubations.",
keywords = "Electronic medical record, Emergent, Endotracheal intubation, Intensive care unit, Search algorithm",
author = "Nathan Smischney and Velagapudi, {V. M.} and Onigkeit, {J. A.} and Pickering, {Brian W} and Herasevich, {Vitaly D} and R. Kashyap",
year = "2013",
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pages = "419--427",
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TY - JOUR

T1 - Retrospective derivation and validation of a search algorithm to identify emergent endotracheal intubations in the intensive care unit

AU - Smischney, Nathan

AU - Velagapudi, V. M.

AU - Onigkeit, J. A.

AU - Pickering, Brian W

AU - Herasevich, Vitaly D

AU - Kashyap, R.

PY - 2013

Y1 - 2013

N2 - Background: The development and validation of automated electronic medical record (EMR) search strategies are important in identifying emergent endotracheal intubations in the intensive care unit (ICU). Objective: To develop and validate an automated search algorithm (strategy) for emergent endotracheal intubation in the critically ill patient. Methods: The EMR search algorithm was created through sequential steps with keywords applied to an institutional EMR database. The search strategy was derived retrospectively through a secondary analysis of a 450-patient subset from the 2,684 patients admitted to either a medical or surgical ICU from January 1, 2010, through December 31, 2011. This search algorithm was validated against an additional 450 randomly selected patients. Sensitivity, specificity, and negative and positive predictive values of the automated search algorithm were compared with a manual medical record review (the reference standard) for data extraction of emergent endotracheal intubations. Results: In the derivation subset, the automated electronic note search strategy achieved a sensitivity of 74% (95% CI, 69%-79%) and a specificity of 98% (95% CI, 92%-100%). With refinements in the search algorithm, sensitivity increased to 95% (95% CI, 91%-97%) and specificity decreased to 96% (95% CI, 92%-98%) in this subset. After validation of the algorithm through a separate patient subset, the final reported sensitivity and specificity were 95% (95% CI, 86%-99%) and 100% (95% CI, 98%-100%). Conclusions: Use of electronic search algorithms allows for correct extraction of emergent endotracheal intubations in the ICU, with high degrees of sensitivity and specificity. Such search algorithms are a reliable alternative to manual chart review for identification of emergent endotracheal intubations.

AB - Background: The development and validation of automated electronic medical record (EMR) search strategies are important in identifying emergent endotracheal intubations in the intensive care unit (ICU). Objective: To develop and validate an automated search algorithm (strategy) for emergent endotracheal intubation in the critically ill patient. Methods: The EMR search algorithm was created through sequential steps with keywords applied to an institutional EMR database. The search strategy was derived retrospectively through a secondary analysis of a 450-patient subset from the 2,684 patients admitted to either a medical or surgical ICU from January 1, 2010, through December 31, 2011. This search algorithm was validated against an additional 450 randomly selected patients. Sensitivity, specificity, and negative and positive predictive values of the automated search algorithm were compared with a manual medical record review (the reference standard) for data extraction of emergent endotracheal intubations. Results: In the derivation subset, the automated electronic note search strategy achieved a sensitivity of 74% (95% CI, 69%-79%) and a specificity of 98% (95% CI, 92%-100%). With refinements in the search algorithm, sensitivity increased to 95% (95% CI, 91%-97%) and specificity decreased to 96% (95% CI, 92%-98%) in this subset. After validation of the algorithm through a separate patient subset, the final reported sensitivity and specificity were 95% (95% CI, 86%-99%) and 100% (95% CI, 98%-100%). Conclusions: Use of electronic search algorithms allows for correct extraction of emergent endotracheal intubations in the ICU, with high degrees of sensitivity and specificity. Such search algorithms are a reliable alternative to manual chart review for identification of emergent endotracheal intubations.

KW - Electronic medical record

KW - Emergent

KW - Endotracheal intubation

KW - Intensive care unit

KW - Search algorithm

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