As monitoring requirements for healthcare-acquired infection increase, an efficient and accurate method for surveillance has been sought. The authors evaluated the accuracy of electronic surveillance in multiple intensive care unit settings. Data from 500 intensive care unit patients were reviewed to determine the presence of central line-associated blood stream infection (CLABSI) and catheter-associated urinary tract infection (CAUTI). An electronic surveillance report was obtained to determine whether patients had a blood-line nosocomial infection marker or a urine nosocomial infection marker. Manual review was based on Centers for Disease Control and Prevention criteria. An infection preventionist then reviewed all discrepant cases and made a final determination, which was used as the gold standard. Sensitivity, specificity, false-positive rate, and false-negative rate were then calculated for electronic surveillance. In the burn population the sensitivity of electronic surveillance for CAUTI was 66.66%, specificity 96.5%, false-positive rate 3.44%, false-negative rate 33%; and for CLABSI the sensitivity was 100%, specificity 95%, false-positive rate 4.96%, false-negative rate 0%. In the nonburn population the sensitivity for CAUTI was 50%, specificity 97.9%, false-positive rate 2%, and false-negative rate 30%; and for CLABSI sensitivity was 60%, specificity 98.8%, false-positive rate 1%, and false-negative rate 60%. Burn centers may experience a higher false-positive rate for electronic surveillance of CLABSI and CAUTI than other critical care units.
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http://dx.doi.org/10.1097/BCR.0b013e3182a2aa0f | DOI Listing |
JAMIA Open
February 2025
Georgia Tech Research Institute, Atlanta, GA 30308, United States.
Objective: The resurgence of syphilis in the United States presents a significant public health challenge. Much of the information needed for syphilis surveillance resides in electronic health records (EHRs). In this manuscript, we describe a surveillance platform for automating the extraction of EHR data, known as SmartChart Suite, and the results from a pilot.
View Article and Find Full Text PDFFront Public Health
December 2024
School of Economics and Management, Huainan Normal University, Huainan, China.
China's "14th Five-Year Plan" proposes the construction of a "Digital China," posing the challenge of digital transformation to coal mining enterprises. It is critical to compare the effectiveness of investing in digital devices with that of human capital. This study establishes a structural equation model based on the 'regulation-situation-behavior' theoretical framework.
View Article and Find Full Text PDFFront Med (Lausanne)
December 2024
Department of Clinical Laboratory, The Third Affiliated Hospital of Wenzhou Medical University, Ruian, Zhejiang, China.
Background: Heart failure (HF) is a life-threatening condition with a high mortality rate. The precise relationship between the heart rate and temperature (HR/T) ratio and mortality in patients with HF remains unclear. This study aimed to investigate the relationship between the HR/T ratio and 28-day intensive care unit (ICU) mortality rates in patients with HF.
View Article and Find Full Text PDFTurk J Med Sci
December 2024
Department of Cardiology, Faculty of Medicine, Mersin University, Mersin, Turkiye.
Background/aim: The epidemiological data on heart failure (HF) vary between regions within the same country. We aimed to investigate the epidemiological data on HF in Türkiye across all age groups regarding seven geographical regions.
Materials And Methods: We included all patients from the Turkish population who received a first diagnosis of HF between January 1, 2016 and December 31, 2022, using ICD-10 codes from the National Electronic Healthcare Database.
Turk J Med Sci
December 2024
Department of Cardiology, Faculty of Medicine, Mersin University, Mersin, Turkiye.
Background/aim: Final diagnosis of heart failure (HF) relies on a combination clinical findings, laboratory and imaging tests. The aim of this study was to review the diagnostic approach to HF in Türkiye.
Materials And Methods: This study is a subanalysis of the nationwide TRends-HF study, based on anonymized data from National Electronic Database between January 1, 2016, and December 31, 2022.
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