Cargando…

Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit

BACKGROUND: The development and validation of automated electronic medical record (EMR) search strategies are important for establishing the timing of mechanical ventilation initiation in the intensive care unit (ICU). Thus, we sought to develop and validate an automated EMR search algorithm (strate...

Descripción completa

Detalles Bibliográficos
Autores principales: Smischney, Nathan J, Velagapudi, Venu M, Onigkeit, James A, Pickering, Brian W, Herasevich, Vitaly, Kashyap, Rahul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4082421/
https://www.ncbi.nlm.nih.gov/pubmed/24965680
http://dx.doi.org/10.1186/1472-6947-14-55
_version_ 1782324255848923136
author Smischney, Nathan J
Velagapudi, Venu M
Onigkeit, James A
Pickering, Brian W
Herasevich, Vitaly
Kashyap, Rahul
author_facet Smischney, Nathan J
Velagapudi, Venu M
Onigkeit, James A
Pickering, Brian W
Herasevich, Vitaly
Kashyap, Rahul
author_sort Smischney, Nathan J
collection PubMed
description BACKGROUND: The development and validation of automated electronic medical record (EMR) search strategies are important for establishing the timing of mechanical ventilation initiation in the intensive care unit (ICU). Thus, we sought to develop and validate an automated EMR search algorithm (strategy) for time zero, the moment of mechanical ventilation initiation in the critically ill patient. METHODS: The EMR search algorithm was developed on the basis of several mechanical ventilation parameters, with the final parameter being positive end-expiratory pressure (PEEP), and was applied to a comprehensive institutional EMR database. The search algorithm was derived from a secondary retrospective analysis of a subset of 450 patients from a cohort of 2,684 patients admitted to a medical ICU and a surgical ICU from January 1, 2010, through December 31, 2011. It was then validated in an independent subset of 450 patients from the same period. The overall percent of agreement between our search algorithm and a comprehensive manual medical record review in the derivation and validation subsets, using peak inspiratory pressure (PIP) as the reference standard, was compared to assess timing of mechanical ventilation initiation. RESULTS: In the derivation subset, the automated electronic search strategy achieved an 87% (κ = 0.87) perfect agreement, with 94% agreement to within one minute. In validating this search algorithm, perfect agreement was found in 92% (κ = 0.92) of patients, with 99% agreement occurring within one minute. CONCLUSIONS: The use of an electronic search strategy resulted in highly accurate extraction of mechanical ventilation initiation in the ICU. The search algorithm of mechanical ventilation initiation is highly efficient and reliable and can facilitate both clinical research and patient care management in a timely manner.
format Online
Article
Text
id pubmed-4082421
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-40824212014-07-05 Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit Smischney, Nathan J Velagapudi, Venu M Onigkeit, James A Pickering, Brian W Herasevich, Vitaly Kashyap, Rahul BMC Med Inform Decis Mak Research Article BACKGROUND: The development and validation of automated electronic medical record (EMR) search strategies are important for establishing the timing of mechanical ventilation initiation in the intensive care unit (ICU). Thus, we sought to develop and validate an automated EMR search algorithm (strategy) for time zero, the moment of mechanical ventilation initiation in the critically ill patient. METHODS: The EMR search algorithm was developed on the basis of several mechanical ventilation parameters, with the final parameter being positive end-expiratory pressure (PEEP), and was applied to a comprehensive institutional EMR database. The search algorithm was derived from a secondary retrospective analysis of a subset of 450 patients from a cohort of 2,684 patients admitted to a medical ICU and a surgical ICU from January 1, 2010, through December 31, 2011. It was then validated in an independent subset of 450 patients from the same period. The overall percent of agreement between our search algorithm and a comprehensive manual medical record review in the derivation and validation subsets, using peak inspiratory pressure (PIP) as the reference standard, was compared to assess timing of mechanical ventilation initiation. RESULTS: In the derivation subset, the automated electronic search strategy achieved an 87% (κ = 0.87) perfect agreement, with 94% agreement to within one minute. In validating this search algorithm, perfect agreement was found in 92% (κ = 0.92) of patients, with 99% agreement occurring within one minute. CONCLUSIONS: The use of an electronic search strategy resulted in highly accurate extraction of mechanical ventilation initiation in the ICU. The search algorithm of mechanical ventilation initiation is highly efficient and reliable and can facilitate both clinical research and patient care management in a timely manner. BioMed Central 2014-06-25 /pmc/articles/PMC4082421/ /pubmed/24965680 http://dx.doi.org/10.1186/1472-6947-14-55 Text en Copyright © 2014 Smischney et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Smischney, Nathan J
Velagapudi, Venu M
Onigkeit, James A
Pickering, Brian W
Herasevich, Vitaly
Kashyap, Rahul
Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
title Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
title_full Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
title_fullStr Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
title_full_unstemmed Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
title_short Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
title_sort derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4082421/
https://www.ncbi.nlm.nih.gov/pubmed/24965680
http://dx.doi.org/10.1186/1472-6947-14-55
work_keys_str_mv AT smischneynathanj derivationandvalidationofasearchalgorithmtoretrospectivelyidentifymechanicalventilationinitiationintheintensivecareunit
AT velagapudivenum derivationandvalidationofasearchalgorithmtoretrospectivelyidentifymechanicalventilationinitiationintheintensivecareunit
AT onigkeitjamesa derivationandvalidationofasearchalgorithmtoretrospectivelyidentifymechanicalventilationinitiationintheintensivecareunit
AT pickeringbrianw derivationandvalidationofasearchalgorithmtoretrospectivelyidentifymechanicalventilationinitiationintheintensivecareunit
AT herasevichvitaly derivationandvalidationofasearchalgorithmtoretrospectivelyidentifymechanicalventilationinitiationintheintensivecareunit
AT kashyaprahul derivationandvalidationofasearchalgorithmtoretrospectivelyidentifymechanicalventilationinitiationintheintensivecareunit