Academic Journal
Hospital-onset bacteremia and fungemia: An evaluation of predictors and feasibility of benchmarking comparing two risk-adjusted models among 267 hospitals
| العنوان: | Hospital-onset bacteremia and fungemia: An evaluation of predictors and feasibility of benchmarking comparing two risk-adjusted models among 267 hospitals |
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| المؤلفون: | Yu, Kalvin C., Ye, Gang, Edwards, Jonathan R., Gupta, Vikas, Benin, Andrea L., Ai, ChinEn, Dantes, Raymund |
| المصدر: | Infection Control & Hospital Epidemiology ; volume 43, issue 10, page 1317-1325 ; ISSN 0899-823X 1559-6834 |
| بيانات النشر: | Cambridge University Press (CUP) |
| سنة النشر: | 2022 |
| الوصف: | 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. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.1017/ice.2022.211 |
| الاتاحة: | http://dx.doi.org/10.1017/ice.2022.211 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0899823X22002112 |
| Rights: | http://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.C22805F2 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1017/ice.2022.211 |
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