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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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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 |
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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 |
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