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

Abstract

BackgroundClinically relevant bleeding risk in discharged medical patients is underestimated and leads to rehospitalization, morbidity, and mortality. Studies assessing this risk are lacking. ObjectiveThe 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. MethodsWe 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. ResultsThe 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. ConclusionWe 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.