Impact of an electronic sepsis initiative on antibiotic use and health care facility–onset Clostridium difficile infection rates
Abstract
Background Although integrated, electronic sepsis screening and treatment protocols are thought to improve patient outcomes, less is known about their unintended consequences. We aimed to determine if the introduction of a sepsis initiative coincided with increases in broad-spectrum antibiotic use and health care facility-onset (HCFO) Clostridium difficile infection (CDI) rates. Methods We used interrupted time series data from a large, tertiary, urban academic medical center including all adult inpatients on 4 medicine wards (June 2011-July 2014). The main exposure was implementation of the sepsis screening program; the main outcomes were the use of broad-spectrum antibiotics (including 3 that were part of an order set designed for the sepsis initiative) and HCFO CDI rates. Segmented regression analyses compared outcomes in 3 time segments: before (11 months), during (14 months), and after (12 months) implementation of a sepsis initiative. Results Antibiotic use and HFCO CDI rates increased during the period of implementation and the period after implementation compared with baseline; these increases were highest in the period after implementation (level change, 50.4 days of therapy per 1,000 patient days for overall antibiotic use and 10.8 HCFO CDIs per 10,000 patient days; P Conclusions The implementation of an electronic sepsis screening and treatment protocol coincided with increased broad-spectrum antibiotic use and HCFO CDIs. Because these protocols are increasingly us…
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The high sensitivity of the SIRS criteria could lead to over diagnosis of sepsis resulting in inappropriate antibiotics use.
“The high sensitivity of the SIRS criteria, on the other hand, could lead to over diagnosis of sepsis resulting in inappropriate antibiotics use [41].”
From Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy (2020) · cites this paper as [41]
Cites
Segmented regression analysis of interrupted time series studies in medication use research
Wagner, A. K., Soumerai, S. B., Zhang, F., & Ross-Degnan, D. (2002) · Journal of Clinical Pharmacy and Therapeutics · doi:10.1046/j.1365-2710.2002.00430.x · Cited by 3,279 · see citing works
A randomized trial of protocol-based care for early septic shock.
The ProCESS Investigators (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1401602 · Cited by 2,414 · see citing works
Damiani, E., Donati, A., Serafini, G., Rinaldi, L., Adrario, E., Pelaia, P., Busani, S., & Girardis, M. (2015) · PLOS ONE · doi:10.1371/journal.pone.0125827 · Cited by 275 · see citing works
Computerized Physician Order Entry and Online Decision Support
Handler, J. A., Feied, C. F., Coonan, K., Vozenilek, J., Gillam, M., Peacock, P. R., Sinert, R., & Smith, M. S. (2004) · Academic Emergency Medicine · doi:10.1197/j.aem.2004.08.007 · Cited by 58 · see citing works
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Fleuren, L. M., Klausch, T. L. T., Zwager, C. L., Schoonmade, L. J., Guo, T., Roggeveen, L. F., Swart, E. L., Girbes, A. R. J., Thoral, P., Ercole, A., et al. (2020) · Intensive Care Medicine · doi:10.1007/s00134-019-05872-y · Cited by 755 · see citing works
Rhee, C., Kadri, S. S., Dekker, J. P., Danner, R. L., Chen, H.-C., Fram, D., Zhang, F., Wang, R., Klompas, M., & Program, F. T. C. P. E. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.2899 · Cited by 397 · see citing works
Serafim, R., Gomes, J. A., Salluh, J., & Póvoa, P. (2018) · Chest · doi:10.1016/j.chest.2017.12.015 · Cited by 274 · see citing works
Rhee, C., Chiotos, K., Cosgrove, S. E., Heil, E. L., Kadri, S. S., Kalil, A. C., Gilbert, D. N., Masur, H., Septimus, E. J., Sweeney, D. A., et al. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa059 · Cited by 191 · see citing works
Rello, J., van Engelen, T. S. R., Alp, E., Calandra, T., Cattoir, V., Kern, W. V., Netea, M. G., Nseir, S., Opal, S. M., van de Veerdonk, F. L., et al. (2018) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2018.03.011 · Cited by 143 · see citing works
Rhee, C., Yu, T., Wang, R., Kadri, S. S., Fram, D., Chen, H.-C., Klompas, M., & Program, C. P. E. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.38596 · Cited by 81 · see citing works
Rothrock, S. G., Cassidy, D. D., Barneck, M., Schinkel, M., Guetschow, B., Myburgh, C., Nguyen, L., Earwood, R., Nanayakkara, P. W. B., Nannan Panday, R. S., et al. (2020) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2020.04.042 · Cited by 57 · see citing works
Madaline, T., Wadskier Montagne, F., Eisenberg, R., Mowrey, W., Kaur, J., Malik, M., Gendlina, I., Guo, Y., White, D., Pirofski, L.-A., et al. (2019) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofz408 · Cited by 43 · see citing works
Impact of the Centers for Medicare and Medicaid Services sepsis core measure on antibiotic use.
Pakyz, A. L., Orndahl, C. M., Johns, A., Harless, D. W., Morgan, D. J., Bearman, G., Hohmann, S. F., & Stevens, M. P. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa456 · Cited by 28 · see citing works
Anderson, D. J., Moehring, R. W., Parish, A., David, M. Z., Hsueh, K., Cressman, L., Tolomeo, P., Habrock-Bach, T., Hill, C. L., Ryan, M., et al. (2022) · Clinical Infectious Diseases · doi:10.1093/cid/ciab937 · Cited by 19 · see citing works
- Authors
- Hiensch, R., Poeran, J., Saunders-Hao, P., Adams, V., Powell, C. A., Glasser, A., Mazumdar, M., & Patel, G.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Mount Sinai Hospital (US)
- Corresponding author
- Hiensch, Robert
- ORCID
- Venue
- American Journal of Infection Control
- Publisher
- Elsevier BV
- Published
- 2017-10
- Volume
- 45
- Issue
- 10
- Pages
- 1091-1100
- ISSN
- 0196-6553 (ISSN-L)
- OpenAlex
- W2623328783
- Cited by
- 44
- References
- 4
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 5 · 2022: 6 · 2021: 8 · 2020: 10 · 2019: 3 · 2018: 5 · 2017: 1
- FWCI
- 4.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Infection Control (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › Clostridium difficile and Clostridium perfringens research
- Life Sciences › Immunology and Microbiology › Applied Microbiology and Biotechnology › Antibiotic Use and Resistance
- Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
- Keywords
- sepsis screening, electronic health records, broad-spectrum antibiotics, Clostridium difficile infection, antibiotic stewardship, inpatient antibiotic use
- MeSH terms
- Academic Medical Centers, Antimicrobial Stewardship, Adult, Aged, Aged, 80 and over, Anti-Bacterial Agents, Clostridium Infections, Drug Utilization, Female, Humans, Male, Mass Screening, Middle Aged, Sepsis, Young Adult, Interrupted Time Series Analysis
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