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SMART-BCx: System-wide Management Algorithm to Reduce Testing of Blood Cultures

Published online by Cambridge University Press:  23 June 2026

Jon Johannesson
Affiliation:
Duke University Hospital
Erin Gettler
Affiliation:
Duke University Medical Center
Nitin Mehdiratta
Affiliation:
Duke University Medical Center
Rebekah Moehring
Affiliation:
Duke University Medical Center
Jessica Seidelman
Affiliation:
Duke University

Abstract

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Background: Blood culture (BCx) algorithms can safely and effectively reduce unnecessary BCxs. We compared the effect of implementing a BCx algorithm across multiple inpatient units within our hospital system, focusing on blood culture event (BCE) rates and secondary adverse events. Method: The same BCx algorithm (Figure 1) was implemented in multiple inpatient units across three hospitals in our health system (Figure 2). BCE rates were compared between pre- and post-intervention periods with interrupted time series (ITS) analyses. Differences in secondary outcomes, including incidence of central line-associated bloodstream infections (CLABSI) and Clostridioides difficile infection (CDI), were compared using χ tests. Result: The rate of BCE decreased after implementation of the BCx algorithm across all units (Figure 3). An immediate decrease in BCE rate was noted in most units upon implementation of the algorithm, except in the cardiac ICU, cardiac floors and neurocritical care unit. No unit demonstrated a significant post-intervention decrease in the BCE rate, with the surgical ICU demonstrating a significant regression to the mean with time. Antibiotic use decreased across all analyzed units (Figure 4). Readmission rates decreased significantly on the cardiac floor, neurocritical care unit and cardiothoracic ICU in hospital 1 and also in the critical care unit in hospital 2, while it increased significantly in the cardiothoracic stepdown unit. CLABSI rates decreased significantly in the cardiac ICU and the solid oncology floor, while CDI rates decreased significantly in the neurocritical care unit. No significant increase was seen in CLABSI and CDI rates or antibiotic use. Conclusion: This study demonstrated that the BCx algorithm was effective in decreasing BCEs across all units and hospitals without any clear harms. However, the effect of BCx algorithms is partially dependent on the nature of the unit where it is implemented. The decrease in BCEs was limited to the time period directly after implementation of the algorithm. No units demonstrated ongoing decreases in BCE rates, with the surgical ICU in particular demonstrating a steady increase of BCE rates as time progressed, although rates of BCE remained below pre-intervention levels. Consistent decreases were seen in antibiotic use post-implementation, although causality between the two cannot be determined. Further research is warranted on how to implement a more durable change and on the use of such algorithms in more specific populations, including immunocompromised hosts.

Flowchart for blood culture collection in immunocompetent adults.

A table comparing hospital units, types, bed counts, and reviewers across two hospitals.

A table comparing surgical intensive care unit data across different hospitals and intervention dates.

A table comparing rates of C. difficile infection, CLABSI rate, Antibiotic rate, and Readmission rate across different locations and units within a hospital.

Information

Type
Diagnostic Stewardship
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America