Impact of Risk Adjustment Using Clinical vs Administrative Data on Hospital Sepsis Mortality Comparisons

Author:

Rhee Chanu12,Li Zhonghe1,Wang Rui1,Song Yue13,Kadri Sameer S4,Septimus Edward J15,Chen Huai-Chun6,Fram David6,Jin Robert1,Poland Russell17,Sands Kenneth17,Klompas Michael12

Affiliation:

1. Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA

2. Division of Infectious Diseases, Brigham and Women’s Hospital, Boston, Massachusetts, USA

3. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

4. Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Massachusetts, USA

5. Texas A&M Health Science Center College of Medicine, Houston, Texas, USA

6. Commonwealth Informatics, Waltham, Massachusetts, USA

7. Clinical Services Group, HCA Healthcare, Nashville, Tennessee, USA

Abstract

Abstract Background A reliable risk-adjusted sepsis outcome measure could complement current national process metrics by identifying outlier hospitals and catalyzing additional improvements in care. However, it is unclear whether integrating clinical data into risk adjustment models identifies similar high- and low-performing hospitals compared with administrative data alone, which are simpler to acquire and analyze. Methods We ranked 200 US hospitals by their Centers for Disease Control and Prevention Adult Sepsis Event (ASE) mortality rates and assessed how rankings changed after applying (1) an administrative risk adjustment model incorporating demographics, comorbidities, and codes for severe illness and (2) an integrated clinical and administrative model replacing severity-of-illness codes with laboratory results, vasopressors, and mechanical ventilation. We assessed agreement between hospitals’ risk-adjusted ASE mortality rates when ranked into quartiles using weighted kappa statistics (к). Results The cohort included 4 009 631 hospitalizations, of which 245 808 met ASE criteria. Risk-adjustment had a large effect on rankings: 22/50 hospitals (44%) in the worst quartile using crude mortality rates shifted into better quartiles after administrative risk adjustment, and a further 21/50 (42%) of hospitals in the worst quartile using administrative risk adjustment shifted to better quartiles after incorporating clinical data. Conversely, 14/50 (28%) hospitals in the best quartile using administrative risk adjustment shifted to worse quartiles with clinical data. Overall agreement between hospital quartile rankings when risk-adjusted using administrative vs clinical data was moderate (к = 0.55). Conclusions Incorporating clinical data into risk adjustment substantially changes rankings of hospitals’ sepsis mortality rates compared with using administrative data alone. Comprehensive risk adjustment using both administrative and clinical data is necessary before comparing hospitals by sepsis mortality rates.

Funder

Centers for Disease Control and Prevention

Agency for Healthcare Research and Quality

National Institutes of Health

National Institute of Allergy and Infectious Diseases

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Oncology

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