# Impact of a multi-step testing algorithm on hospital-onset Clostridioides difficile rates and clinical outcomes

## TL;DR

A multi-step testing approach for Clostridioides difficile significantly reduced hospital-onset infections without affecting patient outcomes.

## Contribution

Demonstrates that a multi-step CDI testing algorithm reduces infection rates without worsening clinical outcomes.

## Key findings

- HO-CDI cases per 10,000 patient days dropped from 5.92 to 2.36 after implementing the algorithm.
- No significant differences in hospital length of stay or ICU admissions were observed.
- All-cause 30-day readmissions decreased significantly in the post-intervention period.

## Abstract

To evaluate the impact of implementing a multi-step Clostridioides difficile infection (CDI) testing algorithm on hospital-onset (HO)-CDI rates and clinical outcomes.

Retrospective pre-intervention/post-intervention study.

Two academic hospitals in Pittsburgh, Pennsylvania.

In the pre-intervention period, a standalone polymerase chain reaction (PCR) assay was used for diagnosing CDI. In the post-intervention period, positive PCR assays were reflexed to a glutamate dehydrogenase antigen test and an enzyme immunoassay for toxin A/B.

The implementation of a multi-step testing algorithm resulted in a significant reduction in HO-CDI cases per 10,000 patient days from 5.92 to 2.36 (P < 0.001). Despite the decrease in reportable HO-CDI cases, there were no significant differences in clinical outcomes such as hospital length of stay, intensive care unit admissions, and treatment courses. In addition, there was a significant reduction in all-cause 30-day readmissions in the post-intervention group, though CDI-related readmissions remained similar.

The multi-step testing algorithm significantly reduced HO-CDI rates without compromising clinical outcomes. The study supports the use of a multi-step CDI testing algorithm to assist healthcare providers with CDI management decisions and potentially to reduce financial penalties burdened on healthcare systems.