Clostridioides difficile surveillance: 9-year comparison between automated surveillance and conventional surveillance in acute care hospitals
Abstract Objective: To develop and validate an automated surveillance system for healthcare-associated Clostridioides difficile infections (HA-CDI). Design: Multicenter cohort study. Setting: 16 acute care hospitals. Patients: Patients admitted to participating hospitals between 2013 and 202...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Antimicrobial Stewardship & Healthcare Epidemiology |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2732494X25000051/type/journal_article |
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| Summary: | Abstract
Objective:
To develop and validate an automated surveillance system for healthcare-associated Clostridioides difficile infections (HA-CDI).
Design:
Multicenter cohort study.
Setting:
16 acute care hospitals.
Patients:
Patients admitted to participating hospitals between 2013 and 2022.
Methods:
An automated surveillance system was developed with retrospective extraction from admission/discharge/transfer and laboratory databases and compared with conventional surveillance based on clinical definitions collected prospectively by infection control professionals. Comparison of HA-CDI incidence rates calculated by automated vs conventional surveillances were performed with χ2, incidence rate ratios, and linear regression. A subset of discordant cases was further investigated by reviewing medical records.
Results:
Overall, conventional surveillance reported 3,211 cases of HA-CDI for an incidence rate of 4.94 per 10,000 patient-days. Automated surveillance detected 4,708 cases, for an incidence rate of 7.24 per 10,000 patient-days (incidence rate ratio, 1.47; 95% CI, 1.40–1.53). Full concordance between both surveillance methods was observed in 62% of cases, while 34% of cases were detected only by automated surveillance, and 4% were detected by conventional surveillance only. Between 2013 and 2022, an identical declining trend in HA-CDI incidence rates of –0.54 cases per 10,000 patient-days was observed with both surveillance methods. A subset of 49 cases detected only by automated surveillance were reviewed; the main reasons for discrepancy were delayed testing (39%), colonization (24%), misclassifications (14%), and interinstitutional transfers (12%).
Conclusions:
HA-CDI incidence rates calculated by automated surveillance were higher than those of conventional surveillance, but the overestimation was consistent over time, suggesting that a correction factor could improve precision.
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| ISSN: | 2732-494X |