# Clostridioides difficile surveillance: 9-year comparison between automated surveillance and conventional surveillance in acute care hospitals

## TL;DR

This study compares automated and conventional methods for tracking Clostridioides difficile infections in hospitals over nine years, finding automated systems detect more cases but with consistent overestimation.

## Contribution

The study introduces and validates an automated surveillance system for HA-CDI, revealing its higher detection rate compared to conventional methods.

## Key findings

- Automated surveillance detected 4,708 HA-CDI cases versus 3,211 by conventional methods.
- 34% of cases were detected only by automated surveillance, mainly due to delayed testing and colonization.
- Both methods showed a consistent declining trend in HA-CDI incidence rates over time.

## Abstract

To develop and validate an automated surveillance system for healthcare-associated Clostridioides difficile infections (HA-CDI).

Multicenter cohort study.

16 acute care hospitals.

Patients admitted to participating hospitals between 2013 and 2022.

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.

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%).

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.