Appl Clin Inform 2013; 04(03): 419-427
DOI: 10.4338/ACI-2013-05-RA-0033
Research Article
Schattauer GmbH

Retrospective Derivation and Validation of a Search Algorithm to Identify Emergent Endotracheal Intubations in the Intensive Care Unit

N.J. Smischney
1  Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota
2  Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, Minnesota
,
V.M. Velagapudi
1  Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota
,
J.A. Onigkeit
1  Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota
,
B.W. Pickering
1  Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota
2  Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, Minnesota
,
V. Herasevich
1  Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota
2  Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, Minnesota
,
R. Kashyap
1  Department of Anesthesiology, Mayo Clinic, Rochester, Minnesota
2  Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, Minnesota
› Author Affiliations
Further Information

Correspondence to:

Nathan J. Smischney, MD
Department of Anesthesiology
Mayo Clinic
200 First St SW, Rochester, MN 55905

Publication History

received: 20 May 2013

accepted: 15 August 2013

Publication Date:
16 December 2017 (online)

 

Summary

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.


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Conflict of Interest

The authors have no conflicts of interest in the research.


Correspondence to:

Nathan J. Smischney, MD
Department of Anesthesiology
Mayo Clinic
200 First St SW, Rochester, MN 55905