A few antibiotics can represent the total hospital antibiotic consumption

Abstract

Background: Appropriate antibiotic use has become an important issue. However, collecting data on the use of all antibiotics in a hospital is difficult without an advanced computerized system and dedicated staff. This paper examines if 1-3 antibiotics can satisfactorily represent the total antibiotic consumption at the hospital level. Methods: We collected antibiotic data from six large university hospitals in Korea for some years between 2004 and 2012. Since the total antibiotics consist of a few chosen representative antibiotics and the rest, we used those chosen antibiotics along with additional variables constructed only with t (time) such as t, t(2), and t(3) to capture the time trend and whether t belongs to each month or not to capture the monthly variations. The ordinary least squares method was used to explain the total antibiotic amount with these variables, and then the estimated model was employed to predict the use for 2013. To determine which antibiotics were the most representative in tracking general trends in antibiotic use over time, we tried various combinations of antibiotics to find the combination that best minimized the 2013 prediction error. Results: We found that fluoroquinolones and aminoglycosides were the most representative, followed by beta-lactam/beta-lactamase inhibitors and 4th-generation and 3rd-generation cephalosporins. The mean prediction error over 12 months in 2013 with these few antibiotics was only 1-3% of the monthly antibiotic consumption amount. Conclusions: The total antibiotic consumption amount at the hospital level can be represented sufficiently by a few antibiotics, such as fluoroquinolones and aminoglycosides, which means that hospitals can save resources by tracing only the usage of those few antibiotics instead of the entire inventory. Since the choice of fluoroquinolones and aminoglycosides is based solely on our Korean data, other hospitals may follow the same modelling methodology to find their own representative antibiotics.