BACKGROUND: To compare the quantitative antibiotic use between hospitals or hospital units and to explore differences, adjustment for severity of illness of hospitalized patients is essential. The case mix index (CMI) is an economic surrogate marker (i.e. the total cost weights of all inpatients per a defined time period divided by the number of admissions) to describe the average patients' morbidity of individual hospitals. We aimed to investigate the correlation between CMI and hospital antibiotic use. METHODS: We used weighted linear regression analysis to evaluate the correlation between in-hospital antibiotic use in 2006 and CMI of 18 departments of the tertiary care University Hospital Zurich and of 10 primary and 2 secondary acute care hospitals in the Canton of Zurich in Switzerland. RESULTS: Antibiotic use varied substantially between different departments of the university hospital [defined daily doses (DDD)/100 bed-days, 68.04; range, 20.97-323.37] and between primary and secondary care hospitals (range of DDD/100 bed-days, 15.45-57.05). Antibiotic use of university hospital departments and the different hospitals, respectively, correlated with CMI when calculated in DDD/100 bed-days [coefficient of determination (R(2)), 0.57 (P = 0.0002) and 0.46 (P = 0.0065)], as well as when calculated in DDD/100 admissions [R(2), 0.48 (P = 0.0008) and 0.85 (P < 0.0001), respectively]. CONCLUSIONS: Antibiotic use correlated with CMI across various specialties of a university hospital and across different acute care hospitals. For benchmarking antibiotic use within and across hospitals, adjustment for CMI may be a useful tool in order to take into account the differences in hospital category and patients' morbidities.
BACKGROUND: To compare the quantitative antibiotic use between hospitals or hospital units and to explore differences, adjustment for severity of illness of hospitalized patients is essential. The case mix index (CMI) is an economic surrogate marker (i.e. the total cost weights of all inpatients per a defined time period divided by the number of admissions) to describe the average patients' morbidity of individual hospitals. We aimed to investigate the correlation between CMI and hospital antibiotic use. METHODS: We used weighted linear regression analysis to evaluate the correlation between in-hospital antibiotic use in 2006 and CMI of 18 departments of the tertiary care University Hospital Zurich and of 10 primary and 2 secondary acute care hospitals in the Canton of Zurich in Switzerland. RESULTS: Antibiotic use varied substantially between different departments of the university hospital [defined daily doses (DDD)/100 bed-days, 68.04; range, 20.97-323.37] and between primary and secondary care hospitals (range of DDD/100 bed-days, 15.45-57.05). Antibiotic use of university hospital departments and the different hospitals, respectively, correlated with CMI when calculated in DDD/100 bed-days [coefficient of determination (R(2)), 0.57 (P = 0.0002) and 0.46 (P = 0.0065)], as well as when calculated in DDD/100 admissions [R(2), 0.48 (P = 0.0008) and 0.85 (P < 0.0001), respectively]. CONCLUSIONS: Antibiotic use correlated with CMI across various specialties of a university hospital and across different acute care hospitals. For benchmarking antibiotic use within and across hospitals, adjustment for CMI may be a useful tool in order to take into account the differences in hospital category and patients' morbidities.
Authors: Nicola D Thompson; Jonathan R Edwards; Margaret A Dudeck; Scott K Fridkin; Shelley S Magill Journal: Infect Control Hosp Epidemiol Date: 2015-10-21 Impact factor: 3.254
Authors: Minn M Soe; Jonathan R Edwards; Dawn M Sievert; Philip M Ricks; Shelley S Magill; Scott K Fridkin Journal: Infect Control Hosp Epidemiol Date: 2015-01 Impact factor: 3.254
Authors: Alexia Cusini; Silvana K Rampini; Vineeta Bansal; Bruno Ledergerber; Stefan P Kuster; Christian Ruef; Rainer Weber Journal: PLoS One Date: 2010-11-16 Impact factor: 3.240