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Benefit analysis of the auto-verification system of intelligent inspection for microorganisms.
Ou, Yu-Hsiang; Chang, Yung-Ta; Chen, Ding-Ping; Chuang, Chun-Wei; Tsao, Kuo-Chien; Wu, Chiu-Hsiang; Kuo, An-Jing; You, Huey-Ling; Huang, Chung-Guei.
Afiliação
  • Ou YH; Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Chang YT; Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Chen DP; Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Chuang CW; Department of Medical Biotechnology and Laboratory Science, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
  • Tsao KC; Graduate Institute of Biomedical Sciences, College of Medicine, Chang, Gung University, Taoyuan,, Taiwan.
  • Wu CH; Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Kuo AJ; Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • You HL; Department of Laboratory Medicine, Chang Gung Memorial Hospital, Keelung, Taiwan.
  • Huang CG; Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Front Microbiol ; 15: 1334897, 2024.
Article em En | MEDLINE | ID: mdl-38562474
ABSTRACT
In recent years, the automatic machine for microbial identification and antibiotic susceptibility tests has been introduced into the microbiology laboratory of our hospital, but there are still many steps that need manual operation. The purpose of this study was to establish an auto-verification system for bacterial naming to improve the turnaround time (TAT) and reduce the burden on clinical laboratory technologists. After the basic interpretation of the gram staining results of microorganisms, the appearance of strain growth, etc., the 9 rules were formulated by the laboratory technologists specialized in microbiology for auto-verification of bacterial naming. The results showed that among 70,044 reports, the average pass rate of auto-verification was 68.2%, and the reason for the failure of auto-verification was further evaluated. It was found that the main causes reason the inconsistency between identification results and strain appearance rationality, the normal flora in the respiratory tract and urine that was identified, the identification limitation of the mass spectrometer, and so on. The average TAT for the preliminary report of bacterial naming was 35.2 h before, which was reduced to 31.9 h after auto-verification. In summary, after auto-verification, the laboratory could replace nearly 2/3 of manual verification and issuance of reports, reducing the daily workload of medical laboratory technologists by about 2 h. Moreover, the TAT on the preliminary identification report was reduced by 3.3 h on average, which could provide treatment evidence for clinicians in advance.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article