Abstract
Inappropriate antibiotic use contributes to antimicrobial resistance. The SpectrumTM app provides antibiotic decision support, based on local antimicrobial resistance rates. We determined the impact of regional implementation of the app on inpatient antimicrobial appropriateness, inpatient antimicrobial usage (AMU), population-based Clostridioides difficile infection (CDI) rates and cost, using a retrospective, before and after quasi-experimental design, including a one-year study period. The SpectrumTM app was released to prescribers in February, 2019. We performed two one-day inpatient point prevalence surveys using the National Antimicrobial Prescribing Survey tool, six months before (June 25, 2018) and six months after (June 25, 2019) app dissemination. Inpatient AMU in Defined Daily Dose/1000 patient days and CDI incidence were compared, before and after app dissemination. The pre-survey included 184 prescriptions, and the post-survey included 197 prescriptions. Appropriateness was 97/176 (55.1%) pre, and 126/192 (65.6%) post (+10.5%, p = 0.051). Inpatient AMU declined by 6.6 DDD/1000 patient days per month, and CDI declined by 0.3 cases per month. Cost savings associated with reduced AMU were $403.98/bed/year and associated with reduced CDI were $82,078/year. We observed improvement in antimicrobial stewardship indicators following SpectrumTM implementation. We cannot determine the cause of these improvements.
Highlights
The inappropriate use of antimicrobials results in unnecessary exposure of pathogens to antimicrobial agents, resulting in the development of antimicrobial resistance (AMR) over time
Inpatient antimicrobial use (AMU) declined by 6.6 Defined daily dose (DDD)/1000 patient days per month, and Clostridioides difficile infection (CDI) declined by 0.3 cases per month
Cost savings associated with reduced AMU were $403.98/bed/year and associated with reduced CDI were $82,078/year
Summary
Inappropriate antibiotic use contributes to antimicrobial resistance. The SpectrumTM app provides antibiotic decision support, based on local antimicrobial resistance rates. We determined the impact of regional implementation of the app on inpatient antimicrobial appropriateness, inpatient antimicrobial usage (AMU), population-based Clostridioides difficile infection (CDI) rates and cost, using a retrospective, before and after quasi-experimental design, including a one-year study period
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