Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach

Abstract Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonosc...

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Autores principales:	Julian C. Hong, Elizabeth R. Hauser, Thomas S. Redding, Kellie J. Sims, Ziad F. Gellad, Meghan C. O’Leary, Terry Hyslop, Ashton N. Madison, Xuejun Qin, David Weiss, A. Jasmine Bullard, Christina D. Williams, Brian A. Sullivan, David Lieberman, Dawn Provenzale
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/06ec3afaeed74231959160bb1fdf31d0
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spelling	oai:doaj.org-article:06ec3afaeed74231959160bb1fdf31d02021-12-02T18:02:48ZCharacterizing chronological accumulation of comorbidities in healthy veterans: a computational approach10.1038/s41598-021-85546-22045-2322https://doaj.org/article/06ec3afaeed74231959160bb1fdf31d02021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85546-2https://doaj.org/toc/2045-2322Abstract Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care.Julian C. HongElizabeth R. HauserThomas S. ReddingKellie J. SimsZiad F. GelladMeghan C. O’LearyTerry HyslopAshton N. MadisonXuejun QinDavid WeissA. Jasmine BullardChristina D. WilliamsBrian A. SullivanDavid LiebermanDawn ProvenzaleNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Julian C. Hong Elizabeth R. Hauser Thomas S. Redding Kellie J. Sims Ziad F. Gellad Meghan C. O’Leary Terry Hyslop Ashton N. Madison Xuejun Qin David Weiss A. Jasmine Bullard Christina D. Williams Brian A. Sullivan David Lieberman Dawn Provenzale Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
description	Abstract Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care.
format	article
author	Julian C. Hong Elizabeth R. Hauser Thomas S. Redding Kellie J. Sims Ziad F. Gellad Meghan C. O’Leary Terry Hyslop Ashton N. Madison Xuejun Qin David Weiss A. Jasmine Bullard Christina D. Williams Brian A. Sullivan David Lieberman Dawn Provenzale
author_facet	Julian C. Hong Elizabeth R. Hauser Thomas S. Redding Kellie J. Sims Ziad F. Gellad Meghan C. O’Leary Terry Hyslop Ashton N. Madison Xuejun Qin David Weiss A. Jasmine Bullard Christina D. Williams Brian A. Sullivan David Lieberman Dawn Provenzale
author_sort	Julian C. Hong
title	Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
title_short	Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
title_full	Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
title_fullStr	Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
title_full_unstemmed	Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
title_sort	characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/06ec3afaeed74231959160bb1fdf31d0
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Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach

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