Hospital-onset bacteremia and fungemia: An evaluation of predictors and feasibility of benchmarking comparing two risk-adjusted models among 267 hospitals

Abstract

Objectives: To evaluate the prevalence of hospital-onset bacteremia and fungemia (HOB), identify hospital-level predictors, and to evaluate the feasibility of an HOB metric.

Methods: We analyzed 9,202,650 admissions from 267 hospitals during 2015-2020. An HOB event was defined as the first positive blood-culture pathogen on day 3 of admission or later. We used the generalized linear model method via negative binomial regression to identify variables and risk markers for HOB. Standardized infection ratios (SIRs) were calculated based on 2 risk-adjusted models: a simple model using descriptive variables and a complex model using descriptive variables plus additional measures of blood-culture testing practices. Performance of each model was compared against the unadjusted rate of HOB.

Results: Overall median rate of HOB per 100 admissions was 0.124 (interquartile range, 0.00-0.22). Facility-level predictors included bed size, sex, ICU admissions, community-onset (CO) blood culture testing intensity, and hospital-onset (HO) testing intensity, and prevalence (all P < .001). In the complex model, CO bacteremia prevalence, HO testing intensity, and HO testing prevalence were the predictors most associated with HOB. The complex model demonstrated better model performance; 55% of hospitals that ranked in the highest quartile based on their raw rate shifted to a lower quartile when the SIR from the complex model was applied.

Conclusions: Hospital descriptors, aggregate patient characteristics, community bacteremia and/or fungemia burden, and clinical blood-culture testing practices influence rates of HOB. Benchmarking an HOB metric is feasible and should endeavor to include both facility and clinical variables.

Fig. 1.

Hospital rankings for top-quartile hospitals (designated 1–51) based on observed HOB rates compared with the simple- and complex-model–derived SIR ranking.^a Gray bars represent rank of the top quartile of hospitals based on observed unadjusted HOB rate per 100 admissions. Blue diamonds represent the simple model SIR-based rank. Orange circles represent the complex model SIR-based rank. ^aFor example, hospital 10 (of 51) is in the top 95th percentile based on observed (unadjusted) HOB; it drops in rank with simple model SIR adjustment to the 56th–60th percentile and further decreases to the 41st–45th percentile in the complex model SIR-adjusted model. Note that among the 51 hospitals, some also increased in rank after the complex-model SIR adjustment (ie, hospitals 13, 28, 34, 36, 40, 43, 47). Full movements of rankings in all 4 quartiles are summarized in Supplementary Table S3 (online).