• Gary S Phillips, Tiffany M Osborn, Kathleen M Terry, Foster Gesten, Mitchell M Levy, and Stanley Lemeshow.
• Center for Biostatistics, Department of Biomedical Informatics, Ohio State University, Columbus, OH.
• Crit. Care Med. 2018 May 1; 46 (5): 674-683.

ObjectivesIn accordance with Rory's Regulations, hospitals across New York State developed and implemented protocols for sepsis recognition and treatment to reduce variations in evidence informed care and preventable mortality. The New York Department of Health sought to develop a risk assessment model for accurate and standardized hospital mortality comparisons of adult septic patients across institutions using case-mix adjustment.DesignRetrospective evaluation of prospectively collected data.PatientsData from 43,204 severe sepsis and septic shock patients from 179 hospitals across New York State were evaluated.SettingsProspective data were submitted to a database from January 1, 2015, to December 31, 2015.InterventionsNone.Measurement And Main ResultsMaximum likelihood logistic regression was used to estimate model coefficients used in the New York State risk model. The mortality probability was estimated using a logistic regression model. Variables to be included in the model were determined as part of the model-building process. Interactions between variables were included if they made clinical sense and if their p values were less than 0.05. Model development used a random sample of 90% of available patients and was validated using the remaining 10%. Hosmer-Lemeshow goodness of fit p values were considerably greater than 0.05, suggesting good calibration. Areas under the receiver operator curve in the developmental and validation subsets were 0.770 (95% CI, 0.765-0.775) and 0.773 (95% CI, 0.758-0.787), respectively, indicating good discrimination. Development and validation datasets had similar distributions of estimated mortality probabilities. Mortality increased with rising age, comorbidities, and lactate.ConclusionsThe New York Sepsis Severity Score accurately estimated the probability of hospital mortality in severe sepsis and septic shock patients. It performed well with respect to calibration and discrimination. This sepsis-specific model provides an accurate, comprehensive method for standardized mortality comparison of adult patients with severe sepsis and septic shock.

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