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Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery

BACKGROUND: To study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans...

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Autores principales: Wang, Xiao Qing, Vincent, Brenda M., Wiitala, Wyndy L., Luginbill, Kaitlyn A., Viglianti, Elizabeth M., Prescott, Hallie C., Iwashyna, Theodore J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505066/
https://www.ncbi.nlm.nih.gov/pubmed/31068135
http://dx.doi.org/10.1186/s12874-019-0740-x
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author Wang, Xiao Qing
Vincent, Brenda M.
Wiitala, Wyndy L.
Luginbill, Kaitlyn A.
Viglianti, Elizabeth M.
Prescott, Hallie C.
Iwashyna, Theodore J.
author_facet Wang, Xiao Qing
Vincent, Brenda M.
Wiitala, Wyndy L.
Luginbill, Kaitlyn A.
Viglianti, Elizabeth M.
Prescott, Hallie C.
Iwashyna, Theodore J.
author_sort Wang, Xiao Qing
collection PubMed
description BACKGROUND: To study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans Affairs Patient Database 2014–2017 (VAPD 2014–2017). The VAPD 2014–2017 contains acute hospitalizations from all parts of the nationwide VA healthcare system with daily physiology including clinical data (labs, vitals, medications, risk scores, etc.), intensive care unit (ICU) indicators, facility, patient, and hospitalization characteristics. METHODS: The VA data structure and database organization represents a complex multi-hospital system. We define a single-site hospitalization as one or more consecutive stays with an acute treating specialty at a single facility. The VAPD 2014–2017 is structured at the patient-facility-day level, where every patient-day in a hospital is a row with separate identification variables for facility, patient, and hospitalization. The VAPD 2014–2017 includes daily laboratory, vital signs, and inpatient medication. Such data were validated and verified through lab value range and comparison with patient charts. Sepsis, risk scores, and organ dysfunction definitions were standardized and calculated. RESULTS: We identified 565,242 single-site hospitalizations (SSHs) in 2014; 558,060 SSHs in 2015; 553,961 SSHs in 2016; and 550,236 SSHs in 2017 at 141 VA hospitals. The average length of stay was four days for all study years. In-hospital mortality decreased from 2014 to 2017 (1.7 to 1.4%), 30-day readmission rates increased from 15.3% in 2014 to 15.6% in 2017; 30-day mortality also decreased from 4.4% in 2014 to 4.1% in 2017. From 2014 to 2017, there were 107,512 (4.8%) of SSHs that met the Center for Disease Control and Prevention’s Electronic Health Record-based retrospective definition of sepsis. CONCLUSION: The VAPD 2014–2017 represents a large, standardized collection of granular data from a heterogeneous nationwide healthcare system. It is also a direct resource for studying the evolution of inpatient physiology during both acute and critical illness. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0740-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-65050662019-05-10 Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery Wang, Xiao Qing Vincent, Brenda M. Wiitala, Wyndy L. Luginbill, Kaitlyn A. Viglianti, Elizabeth M. Prescott, Hallie C. Iwashyna, Theodore J. BMC Med Res Methodol Database BACKGROUND: To study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans Affairs Patient Database 2014–2017 (VAPD 2014–2017). The VAPD 2014–2017 contains acute hospitalizations from all parts of the nationwide VA healthcare system with daily physiology including clinical data (labs, vitals, medications, risk scores, etc.), intensive care unit (ICU) indicators, facility, patient, and hospitalization characteristics. METHODS: The VA data structure and database organization represents a complex multi-hospital system. We define a single-site hospitalization as one or more consecutive stays with an acute treating specialty at a single facility. The VAPD 2014–2017 is structured at the patient-facility-day level, where every patient-day in a hospital is a row with separate identification variables for facility, patient, and hospitalization. The VAPD 2014–2017 includes daily laboratory, vital signs, and inpatient medication. Such data were validated and verified through lab value range and comparison with patient charts. Sepsis, risk scores, and organ dysfunction definitions were standardized and calculated. RESULTS: We identified 565,242 single-site hospitalizations (SSHs) in 2014; 558,060 SSHs in 2015; 553,961 SSHs in 2016; and 550,236 SSHs in 2017 at 141 VA hospitals. The average length of stay was four days for all study years. In-hospital mortality decreased from 2014 to 2017 (1.7 to 1.4%), 30-day readmission rates increased from 15.3% in 2014 to 15.6% in 2017; 30-day mortality also decreased from 4.4% in 2014 to 4.1% in 2017. From 2014 to 2017, there were 107,512 (4.8%) of SSHs that met the Center for Disease Control and Prevention’s Electronic Health Record-based retrospective definition of sepsis. CONCLUSION: The VAPD 2014–2017 represents a large, standardized collection of granular data from a heterogeneous nationwide healthcare system. It is also a direct resource for studying the evolution of inpatient physiology during both acute and critical illness. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0740-x) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-08 /pmc/articles/PMC6505066/ /pubmed/31068135 http://dx.doi.org/10.1186/s12874-019-0740-x Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Database
Wang, Xiao Qing
Vincent, Brenda M.
Wiitala, Wyndy L.
Luginbill, Kaitlyn A.
Viglianti, Elizabeth M.
Prescott, Hallie C.
Iwashyna, Theodore J.
Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
title Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
title_full Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
title_fullStr Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
title_full_unstemmed Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
title_short Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
title_sort veterans affairs patient database (vapd 2014–2017): building nationwide granular data for clinical discovery
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505066/
https://www.ncbi.nlm.nih.gov/pubmed/31068135
http://dx.doi.org/10.1186/s12874-019-0740-x
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