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

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

doi:10.1038/s41598-021-85546-2

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

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

Gastroenterology and Hepatology

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

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.

Original language	English (US)
Article number	8104
Journal	Scientific Reports
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41598-021-85546-2
State	Published - Dec 2021

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Hong, J. C., Hauser, E. R., Redding, T. S., Sims, K. J., Gellad, Z. F., O’Leary, M. C., Hyslop, T., Madison, A. N., Qin, X., Weiss, D., Bullard, A. J., Williams, C. D., Sullivan, B. A., Lieberman, D., & Provenzale, D. (2021). Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach. Scientific Reports, 11(1), Article 8104. https://doi.org/10.1038/s41598-021-85546-2

Hong, JC, Hauser, ER, Redding, TS, Sims, KJ, Gellad, ZF, O’Leary, MC, Hyslop, T, Madison, AN, Qin, X, Weiss, D, Bullard, AJ, Williams, CD, Sullivan, BA, Lieberman, D & Provenzale, D 2021, 'Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach', Scientific Reports, vol. 11, no. 1, 8104. https://doi.org/10.1038/s41598-021-85546-2

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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.",

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AU - Madison, Ashton N.

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AU - Provenzale, Dawn

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AB - 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.

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

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