• Application of a Clostridium difficile Diagnostic Algorithm to Decrease Hospital-Occurring Infections

      Harrison, Laura B.; Callender, Kimberly (2021-05)
      Problem: A geriatric specialty unit within a community hospital has an average monthly rate of two per 1000 patient days of hospital-occurring Clostridium difficile infections. A knowledge deficit among nursing staff regarding Clostridium difficile was identified as a potential cause of inappropriate testing. Purpose: To implement a Clostridium difficile diagnostic algorithm to eliminate overuse of Clostridium difficile testing and obtain more accurate rate of infections. Methods: An evidence-based Clostridium difficile diagnostic algorithm was implemented and evaluated over 14-weeks to increase the nursing staff’s ability to identify the appropriate patients for obtaining diagnostic samples. Algorithm education was provided to registered nurses and patient care technicians and measured by rate of completion. Weekly chart reviews on collected tests, measured the rate of appropriate Clostridium difficile tests and the rate of intensive care unit transfers related to Clostridium difficile. The rates of positive and hospital-occurring Clostridium difficile were measured by weekly extraction of lab data. Results: There was an 82% (n=62) education completion rate among staff. Appropriate Clostridium difficile testing increased from 14% (n=7) to 76% (n=18) (p=.02). The rate of hospital-occurring Clostridium difficile infections increased from 0% (n=7) to 14% (n=21), and positive infections decreased from 29% (n=7) to 14% (n=21); neither were statistically significant. There were zero critical care transfers. Conclusion: A Clostridium difficile diagnostic algorithm increased the number of appropriate tests performed. The algorithm was found to be feasible to use with low cost. To maintain these results, a continuation of unit feedback on Clostridium difficile results and additional training is necessary.