The relative risk of bleeding after medical hospitalization: the medical inpatient thrombosis and hemorrhage study

Mansour Gergi; Katherine Wilkinson; Insu Koh; Jordan Munger; Hanny Al-Samkari; Nicholas L Smith; Nicholas S Roetker; Timothy B Plante; Mary Cushman; Allen B Repp; Chris E Holmes; Neil A Zakai

doi:10.1016/j.jtha.2022.11.023

The relative risk of bleeding after medical hospitalization: the medical inpatient thrombosis and hemorrhage study

J Thromb Haemost. 2023 Mar;21(3):513-521. doi: 10.1016/j.jtha.2022.11.023. Epub 2022 Dec 22.

Authors

Affiliations

¹ Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; University of Vermont Medical Center, Burlington, Vermont, USA.
² Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA.
³ Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
⁴ Department of Epidemiology, University of Washington, Seattle, Washington, USA; Department of Veterans Affairs Office of Research and Development, Seattle Epidemiologic Research and Information Center, Seattle, Washington, USA; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA.
⁵ Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota, USA.
⁶ Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; University of Vermont Medical Center, Burlington, Vermont, USA; Department of Pathology and Laboratory Medicine, University of Vermont Medical Center, Burlington, Vermont, USA.
⁷ Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont, USA; University of Vermont Medical Center, Burlington, Vermont, USA; Department of Pathology and Laboratory Medicine, University of Vermont Medical Center, Burlington, Vermont, USA. Electronic address: Neil.Zakai@med.uvm.edu.

Abstract

Background: Clinically relevant bleeding risk in discharged medical patients is underestimated and leads to rehospitalization, morbidity, and mortality. Studies assessing this risk are lacking.

Objective: The aim of this study was to develop and validate a computable phenotype for clinically relevant bleeding using electronic health record (EHR) data and quantify the relative and absolute risks of this bleeding after medical hospitalization.

Methods: We conducted an observational cohort study of people receiving their primary care at sites affiliated with an academic medical center in northwest Vermont, United States. We developed a computable phenotype using EHR data (diagnosis codes, procedure codes, laboratory, and transfusion data) and validated it by manual chart review. Cox proportional hazard models with hospitalization modeled as a time-varying covariate were used to estimate clinically relevant bleeding risk.

Results: The computable phenotype had a positive predictive value of 80% and a negative predictive value of 99%. The bleeding rate in individuals with no medical hospitalizations in the past 3 months was 2.9 per 1000 person-years versus 98.9 per 1000 person-years in those who were discharged in the past 3 months. This translates into a hazard ratio (95% CI) of clinically relevant bleeding of 22.9 (18.9, 27.7), 13.0 (10.0, 16.9), and 6.8 (4.7, 9.8) over the first, second, and third months after discharge, respectively.

Conclusion: We developed and validated a computable phenotype for clinically relevant bleeding and determined its relative and absolute risk in the 3 months after medical hospitalization discharge. The high rates of bleeding observed underscore the clinical importance of capturing and further studying bleeding after medical discharge.

Keywords: computable phenotype; electronic health record; informatics; medical hospitalization; postdischarge bleeding; postdischarge hemorrhage.

Publication types

Observational Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Cohort Studies
Hemorrhage
Hospitalization
Humans
Inpatients*
Risk
Thrombosis*
United States

Abstract

Publication types

MeSH terms

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