Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals

Area of Science:

• Infectious Disease Epidemiology
• Health Informatics
• Clinical Decision Support Systems

Background:

• Inappropriate Clostridioides difficile testing poses risks to patients, healthcare systems, and public health.
• Computerized Clinical Decision Support (CCDS) integrated into Electronic Health Records (EHRs) shows potential for reducing unnecessary C. difficile testing.
• Understanding the effectiveness, usability, and workflow integration of different CCDS approaches is crucial.

Purpose of the Study:

• To evaluate the impact of CCDS interventions on Clostridioides difficile testing rates across diverse hospital settings.
• To assess healthcare providers' (HCPs) experiences and perceptions of CCDS systems.
• To identify factors influencing the successful adoption and integration of CCDS in clinical practice.

Main Methods:

• A 2-year cohort study involving 15 US hospitals (9 academic, 6 community).
• Implementation of CCDS interventions (hard-stop or soft-stop) within EHRs to flag inappropriate C. difficile test orders.
• Qualitative evaluation using human factors methods (contextual inquiry, interviews, focus groups) to assess HCP experiences.

Main Results:

• CCDS interventions led to significant reductions in C. difficile testing rates: 33% with hard-stop and 23% with soft-stop systems.
• A non-EHR-based human intervention also reduced testing by 21%.
• HCPs reported positive experiences, noting workflow efficiencies and the value of patient-specific information provided by CCDS.

Conclusions:

• CCDS systems are effective in reducing unnecessary Clostridioides difficile testing.
• Positive HCP perception and successful integration are linked to seamless workflow incorporation and relevant data presentation.
• Organizational culture and inter-provider communication influence CCDS acceptance and effectiveness.