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The New York Sepsis Severity Score: Development of a Risk-Adjusted Severity Model for Sepsis

Phillips, Gary, S., MAS1; Osborn, Tiffany, M., MD, MPH2; Terry, Kathleen, M., PhD, BCC3; Gesten, Foster, MD4; Levy, Mitchell, M., MD5; Lemeshow, Stanley, PhD6

doi: 10.1097/CCM.0000000000002824
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Objectives: In accordance with Rorys 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.

Design: Retrospective evaluation of prospectively collected data.

Patients: Data from 43,204 severe sepsis and septic shock patients from 179 hospitals across New York State were evaluated.

Settings: Prospective data were submitted to a database from January 1, 2015, to December 31, 2015.

Interventions: None.

Measurement and Main Results: Maximum 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, 0.7650.775) and 0.773 (95% CI, 0.7580.787), respectively, indicating good discrimination. Development and validation datasets had similar distributions of estimated mortality probabilities. Mortality increased with rising age, comorbidities, and lactate.

Conclusions: The 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.

1Center for Biostatistics, Department of Biomedical Informatics, Ohio State University, Columbus, OH.

2Division of Emergency Medicine, Department of Surgery, Washington University, St. Louis, MO.

3IPRO, Lake Success, NY.

4Quality and Health Care Delivery, Greater New York Hospital Association, New York, NY.

5Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Alpert Medical School at Brown University, Providence, RI.

6The Ohio State University College of Public Health, Columbus, OH.

Mr. Phillips and Dr. Osborn contributed equally as cofirst authors.

Mr. Phillips is retired from the Center for Biostatistics, Department of Biomedical Infomatics, Ohio State University, Columbus, OH.

Dr. Gesten is retired from the Office of Quality and Patient Safety, New York State Department of Health, New York State Department of Health, Albany, NY.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journals website (http://journals.lww.com/ccmjournal).

Mr. Phillips and Dr. Lemeshow received funding from IPRO. Dr. Gesten disclosed government work, and he disclosed that the New York State Department of Health (NYSDOH) has an existing contract with IPRO for an extensive scope of work which includes, but is not limited to, the implementation of the statewide sepsis initiative. This initiative is the source for the data used in the development of the model, and the contract with IPRO paid statistical consultant services. The remaining authors have disclosed that they do not have any potential conflicts of interest.

For information regarding this article, E-mail: osbornt@wustl.edu

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