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Clin Infect Dis ; 67(11): 1677-1685, 2018 11 13.
Article in English | MEDLINE | ID: mdl-29688279

ABSTRACT

Background: Increasing antibiotic resistance has made benchmarking appropriate inpatient antibiotic use a worldwide priority supported by expert societies and regulatory bodies; however, standard risk adjustment for fair interfacility comparison has been elusive. We describe a risk-adjusted antibiotic exposure ratio that may help facilitate assessment of antimicrobial use. Methods: This was a retrospective cohort study of 2.7 million admissions evaluating a wide array of potential explanatory variables for correlation with expected antibiotic consumption in a 2-step approach using recursive partitioning and Poisson regression. Observed-to-expected ratios of risk-adjusted antibiotic use were calculated. Three models of varying complexity were compared: (1) a complex ratio consisting of all available antibiotic use risk factors in a hierarchical model; (2) a simplified antimicrobial stewardship program (ASP) ratio using common facility and encounter factors in a single-level model; and (3) a facility ratio using only broad hospital characteristics. Results: Diagnosis-related groups, infection present on admission, patient class, and unit type were the major predictors of expected antibiotic use. Aside from a history of gram-positive resistance in the prior 12 months for anti-methicillin-resistant Staphylococcus aureus drugs, additional clinical and comorbid history information did not improve the model. The simplified ASP ratio demonstrated higher Pearson correlation (R2 = 0.97-0.99) to the complex ratio than the facility ratio (R2 = 0.57-0.85) and provided clinical explanations when discordant. Conclusions: The simplified ASP ratio is derived from a parsimonious model that incorporates disease burden through patient-level risk adjustment and better informs stewardship assessment. This may allow for improved comparison of antibiotic use between healthcare facilities.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Antimicrobial Stewardship , Benchmarking , Inpatients , Adult , Aged , Data Interpretation, Statistical , Drug Resistance, Microbial , Female , Hospitals , Humans , Male , Middle Aged , Public Health , Retrospective Studies , Risk Adjustment , Risk Factors
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