Faster and active surveillance of hospital-acquired infections

A model for settings with high sensitivity predictors

Yaowen Chung, Yu Sheng Lo, Wen Sen Lee, Min-Huei Hsu, Chien Tsai Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Background: At present, passive alarm system from culture reports and announced from groups outbreak events make cases investigate delayed. Is there any predict factor can be used to suggest active high capture sensitivity surveillance and alarm outbreak early? Objectives: Is there any predict factor can be used to get active high capture sensitivity surveillance of hospital-acquired infections (HAI) in acute hospitals. Can it give alarm of outbreak early? Can it decrease the number for direct patient examination or chart review. Methods : We performed three months retrospective study to identify predictors(urine routine, device as catheter or cystoscope, antibiotics, culture, etc.) about major HAI (urinary tract infections), as defined by the Centers for Disease Control and Prevention (CDC) criteria in a medical center (733 beds). We compared patients list of predictor(s) positive collected from electronic medical record by medical information department members with confirmed nosocomial UTI cases list given from infection control department. Results: 5533 admission patients were screened. The overall prevalence of HAI was 2.5% (141/5533); 1.4% (77/5533) of patients was nosocomial UTI. At presence of urine routine examination and devices guarantees 100% capture sensitivity in detecting nosocomial UTI but requires an assessment of 2763 patients (49.9%) of the population. At presence of antibiotics and devices guarantees 98.7% capture sensitivity and requires an assessment of 1921 patients (34.7%) of the population, whereas presence of antibiotics and urine routine examination has 98.7% capture sensitivity but requires an assessment of 3019 patients (54.7%) of the population. Conclusion: A capture system based on daily list of newly order about antibiotics, devices, urine routine examination, urine culture, blood culture, infection control department of hospital can decide which high predict value criteria suggesting checklist from medical information department for infection control department member to perform active patient examination and decrease the number of direct patient examination and chart review, but still keep high capture sensitivity.

Original languageEnglish
Title of host publicationProceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
Pages443-448
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 - Taichung, Taiwan
Duration: Jun 22 2009Jun 24 2009

Other

Other2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
CountryTaiwan
CityTaichung
Period6/22/096/24/09

Fingerprint

Cross Infection
Antibiotics
Urine
Infection Control
Anti-Bacterial Agents
Disease Outbreaks
Equipment and Supplies
Disease control
Electronic medical equipment
Catheters
Alarm systems
Cystoscopes
Population
Blood
Electronic Health Records
Patient Admission
Hospital Departments
Centers for Disease Control and Prevention (U.S.)
Checklist
Urinary Tract Infections

Keywords

  • HAI
  • Hospital-acquired infection
  • Nosocomial infection
  • Predictor
  • Surveillance
  • UTI

ASJC Scopus subject areas

  • Information Systems
  • Biomedical Engineering
  • Health Informatics

Cite this

Chung, Y., Lo, Y. S., Lee, W. S., Hsu, M-H., & Liu, C. T. (2009). Faster and active surveillance of hospital-acquired infections: A model for settings with high sensitivity predictors. In Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 (pp. 443-448). [5211224] https://doi.org/10.1109/BIBE.2009.39

Faster and active surveillance of hospital-acquired infections : A model for settings with high sensitivity predictors. / Chung, Yaowen; Lo, Yu Sheng; Lee, Wen Sen; Hsu, Min-Huei; Liu, Chien Tsai.

Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. p. 443-448 5211224.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chung, Y, Lo, YS, Lee, WS, Hsu, M-H & Liu, CT 2009, Faster and active surveillance of hospital-acquired infections: A model for settings with high sensitivity predictors. in Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009., 5211224, pp. 443-448, 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009, Taichung, Taiwan, 6/22/09. https://doi.org/10.1109/BIBE.2009.39
Chung Y, Lo YS, Lee WS, Hsu M-H, Liu CT. Faster and active surveillance of hospital-acquired infections: A model for settings with high sensitivity predictors. In Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. p. 443-448. 5211224 https://doi.org/10.1109/BIBE.2009.39
Chung, Yaowen ; Lo, Yu Sheng ; Lee, Wen Sen ; Hsu, Min-Huei ; Liu, Chien Tsai. / Faster and active surveillance of hospital-acquired infections : A model for settings with high sensitivity predictors. Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. pp. 443-448
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abstract = "Background: At present, passive alarm system from culture reports and announced from groups outbreak events make cases investigate delayed. Is there any predict factor can be used to suggest active high capture sensitivity surveillance and alarm outbreak early? Objectives: Is there any predict factor can be used to get active high capture sensitivity surveillance of hospital-acquired infections (HAI) in acute hospitals. Can it give alarm of outbreak early? Can it decrease the number for direct patient examination or chart review. Methods : We performed three months retrospective study to identify predictors(urine routine, device as catheter or cystoscope, antibiotics, culture, etc.) about major HAI (urinary tract infections), as defined by the Centers for Disease Control and Prevention (CDC) criteria in a medical center (733 beds). We compared patients list of predictor(s) positive collected from electronic medical record by medical information department members with confirmed nosocomial UTI cases list given from infection control department. Results: 5533 admission patients were screened. The overall prevalence of HAI was 2.5{\%} (141/5533); 1.4{\%} (77/5533) of patients was nosocomial UTI. At presence of urine routine examination and devices guarantees 100{\%} capture sensitivity in detecting nosocomial UTI but requires an assessment of 2763 patients (49.9{\%}) of the population. At presence of antibiotics and devices guarantees 98.7{\%} capture sensitivity and requires an assessment of 1921 patients (34.7{\%}) of the population, whereas presence of antibiotics and urine routine examination has 98.7{\%} capture sensitivity but requires an assessment of 3019 patients (54.7{\%}) of the population. Conclusion: A capture system based on daily list of newly order about antibiotics, devices, urine routine examination, urine culture, blood culture, infection control department of hospital can decide which high predict value criteria suggesting checklist from medical information department for infection control department member to perform active patient examination and decrease the number of direct patient examination and chart review, but still keep high capture sensitivity.",
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