51. Development and Assessment of a Process to Describe the Timing of Antibiotic Changes in Adult Inpatients

Background

Hospital antimicrobial stewardship programs (ASP) perform prospective audit and feedback to optimize use of antimicrobials; however, workflow inefficiency continues to be a distinct challenge. We developed a method to describe the volume and timing of antimicrobial changes to inform decisions on optimal timing of ASP review and intervention.

Methods

This retrospective study was performed at Duke University Hospital using anonymized antibiotic administration records from the DASON central database. Eligible antibiotic courses were administered to inpatients ≥ 18 years of age and had received ≥ 2 antibiotics administrations for ≥ 24 hours of treatment. A 2-month exploratory cohort (September to October 2017) was used to develop an antibiotic spectrum ranking (Table 1) and decision algorithm which was applied to a 1-year cohort (November 2017 to October 2018) for analysis of total change in antibiotic orders by day of the week. For each interval, the sum of antibiotic ranks was calculated and applied using specified definitions (Table 2) to determine the type of change occurring. The primary outcome was the number of total antibiotic changes that occurred on each day of the week. Secondary outcomes included the number and type (initiations, discontinuations, de-escalations, and escalations) of change. Descriptive statistics were used to describe the outcomes by day of the week.

Table 1: Antibiotic Spectrum Ranking

Table 2: Key Definitions

Results

The ranking and decision algorithm were applied to 16,993 unique antibiotic courses. Total changes occurred most on Wednesday (14,971, 16.2% [95% CI 15.7–17.1%]) and Friday (14,349, 15.6% [95% CI 15.0–16.2%]). Compared to intervals on weekdays (0.407 mean changes per patients on antibiotics [95% CI 0.401–0.413]), weekends had a lower number of changes (0.363 mean changes per patients on antibiotics [95% CI 0.349–0.377]). Initiations occurred most frequently on Tuesday (3,078, 18.1% [95% CI 16.3–19.9%]), and discontinuations on Wednesday (3,179, 18.7% [95% CI 17.4–20.5%]) (Figure 1).

Figure 1: Types of Changes per Day

Conclusion

We developed and applied a method to characterize antimicrobial changes. In our institution, the reductions in the number of changes observed on weekends provide an opportunity for ASP involvement to be incorporated and help facilitate appropriate antimicrobial changes.

Disclosures

Rebekah W. Moehring, MD, MPH, Agency for Healthcare Quality and Research (Grant/Research Support)Centers for Disease Control and Prevention (Grant/Research Support)