br Results br Discussion Evaluation of antimicrobial usage i

Results
Discussion Evaluation of antimicrobial usage is standardized using the DDD as a recommended strategy for comparison with similar hospitals [13]. The use of risk adjustment is needed to overcome the challenge of benchmarking. Two patient characteristics are associated with clinical outcomes and use of the healthcare system. These factors are: patient mix and severity of illness [19], [20]. Direct comparison of the quantity of antibiotic consumed between hospitals is flawed, due to multiple factors, such as severity of illness, structures, and missions [17]. We reported antibiotic consumption per 100 bed-days for inpatients, to overcome the variation in hospital size and occupancy rate. We also adjusted antibiotic usage using the case mix index (CMI), to reduce the variation of patient morbidity among hospitals. CMI is a tool for comparison and had been shown to have a moderate correlation with antibiotic use [17], [21]. The use of DDD estimates indirectly the actual DOT [19], [20]. The measurement of DOT is insensitive to the actual dosages administered. And DOT measurement favors those situations where broad spectrum monotherapy is used. One of the drawbacks of DDD measurement is related to patients with renal or hepatic dysfunction needing adjustment [22]. In this e mycin report, we observed a discordant findings of antibiotic measurements based on the DDD and DOT and a discordant findings of antibiotic measurements based on DDD/100 bed-days compared to DOT/100 bed-days. Similarly, previous studies showed discordant measurements between DDD and DOT [22], [23], [24], [25], [26]. The DDD method is useful for benchmarking, but not for evaluation of the number of DOTs or relative use for antibacterial agents [27]. And that DOT is more difficult to measure, but is a superior measurement methodology [27]. Reporting DDD data could be misleading and may not reflect the activity of the ASP, because other factors may interfere, such as hospital days and the morbidity of admitted patients. This findings is obvious in this report where DDD increased and the DDD per 100 bed days decreased in 2015 compared to the baseline. The adjusted DDD/100 bed-days showed a decrease in the usage of antibiotics, reflecting activities of the antibiotic stewardship program. Measuring DDDs per 1000 patient-days and DOTs per 1000 patient-days (or 100 patient-days) may be required especially in relation to antimicrobial resistance [27]. Further adjustment of DDD/100 bed-days based on CMI in our study showed a negative correlation with increasing CMI, reflecting the efficacy of ASP activities in our institute. The reduction of 5.13% of DDD adjusted to 100 bed-days, and correlation with CMI, gave us an indicator of the ASP’s success. Similarly, previous studies showed a strong correlation between CMI and antibacterial usage expressed as DDD/100 patient days [17]. However, increasing CMI may lead to increased combination therapy as shown by an increase in the DOT and DOT/100 bed-days. This increase in combination therapy could be also the target of future antimicrobial stewardship program, particularly targeting deescalation from combination therapy to monotherapy.
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Risks Associated with Antibiotic Use The discovery of antibiotics was one of the greatest milestones in the history of medicine. There is no doubt that antibiotics have saved countless lives to date and marked the dawn of a new era in public health (Box 1). However, what could not have been predicted at the time of their discovery is that not only do antibiotics not selectively target pathogens, but they also affect the viability of nonpathogenic species that shape health and physiology [1]. The importance of this has only recently started to be realized, as the impact of the microbiota (see Glossary) on host physiology has begun to be unraveled and the associations between antibiotic use and various diseases have been documented. Other unwitting targets of antibiotics are mitochondria, due to their prokaryotic origin; however, the physiological consequences of these interactions are not clear (Box 2).