06-09-2024 | Antibiotic | Research
The impact of optimizing microbial diagnosis processes on clinical and healthcare economic outcomes in hospitalized patients with bloodstream infections
Authors:
Genwei Ai, Ying Zhang, Kunshan Guo, Lu Zhao, Zhi Li, He Hai, Erjuan Jia, Junying Liu
Published in:
European Journal of Clinical Microbiology & Infectious Diseases
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Abstract
Purpose
Bloodstream infections (BSIs) are associated with significant morbidity, mortality and costs, while prolonged blood culture (BC) diagnosis may delay the initiation of targeted therapy. This study evaluates the impact of an optimized microbiology laboratory process on turnaround times, antibiotic use, clinical outcomes and economics for hospitalized BSI patients.
Methods
A pre-post study was conducted in a Chinese hospital in which BSI derived BC results before (Oct. 2020- Sep. 2021) and after (Oct. 2021- Sep. 2022) newly implemented microbiology diagnostics and workflow changes were analyzed. Turnaround times, antibiotic initiation, length of stay and in-hospital costs were compared.
Results
From 213 included patients, 134 were pre-optimization (pre-op) and 79 were post-optimization (post-op) cases. The median time from blood sample collection (BSC) to pathogen identification (ID) decreased from 70.12 to 47.43 h post-op (P < 0.001). The median time from BSC to the first ID report related initiation of pathogen-directed antibiotic use decreased from 88.48 to 47.85 h post-op (P < 0.001). The average hospital stay decreased from 19.54 to 16.79 days and 30-day readmissions declined from 18.7 to 13.9%, while the mean total antimicrobial drug usage costs decreased by 3,889 CNY per patient (P = 0.022) after optimization.
Conclusions
Implementing new diagnostics technologies and optimizing laboratory workflows significantly reduced antimicrobial drug usage costs, shortened the time to ID results and improved the timeliness of appropriate antibiotic choices to treat BSIs. Investments in faster testing and process improvements were clearly beneficial for patient outcomes and healthcare economics.