Author Interviews, CDC, Health Care Systems, Infections, Outcomes & Safety / 12.10.2015
What Explains Hospital Variation In Antibiotic Usage?
MedicalResearch.com Interview with:
James Baggs, PhD
Division of Healthcare Quality Promotion
Centers for Disease Control and Prevention
Atlanta, GA
Medical Research: What is the background for this study?
Dr. Baggs: The National Action Plan for Combating Antibiotic Resistance Bacteria calls for annual reporting of antibiotic use in inpatient settings as well as the identification of variations at the provider or patient level that can assist in developing interventions. Antibiotic use varies among hospitals, but some portion of that variability is related to the type of patients admitted to the hospital and other hospital characteristics. We evaluated factors in a large cohort of US hospitals that may account for inter-facility variability in antibiotic use, so that we can more appropriately monitor antibiotic use in hospitals.
Medical Research: What are the main findings?
Dr. Baggs: We utilized data from the Truven Health MarketScan Hospital Drug Database (HDD), which contains detailed administrative records, including inpatient drug utilization data based on billing records, for all patients discharged from a convenience sample of over 500 US hospitals. We retrospectively estimated days of therapy (DOT)/1,000 patient days (PDs) by year from 2006-2012, and created a multivariable model that adjusts for hospital-specific location of antibiotic use (ICU vs. other), average patient age, average patient co-morbidity score, number of hospital beds, teaching status, urban or rural location, proportion of discharges with a surgical diagnosis related code, case mix index, and proportion of patient days with an infectious disease primary ICD-9-CM discharge code. We observed that DOT varied significantly between hospitals; the 10th to 90th percentile values for hospital days of therapy ranged from 546 to 998/1,000 PDs. The variables included in our model accounted for 47-53% of the inter-facility variability, depending on year. However, nearly all of this variability was explained by two predictors: proportion of PDs with an infectious disease diagnosis code and hospital location (ICU vs. other).
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