Kalvin C Yu1, Elizabeth Moisan2, Sara Y Tartof3, Hien M Nguyen4, Gunter Rieg5, Charulata Ramaprasad6, Jason Jones7. 1. Quality Department, Infectious Diseases, Kaiser Permanente Southern California, Pasadena. 2. Utility for Care Data Analysis Department, Kaiser Foundation Health Plan, Oakland. 3. Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena. 4. Department of Infectious Diseases, Kaiser Permanente Northwest, Portland, Oregon. 5. Department of Infectious Diseases, Kaiser Permanente Southern California, Harbor City. 6. Department of Infectious Diseases, Kaiser Permanente San Jose Medical Center. 7. Information Support for Care Transformation, Kaiser Permanente, Oakland, California.
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.
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.
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