Perioperative Medicine  |   January 2018
Comparison of an Updated Risk Stratification Index to Hierarchical Condition Categories
Author Notes
  • The Lown Institute, Boston, Massachusetts (G.F.C., N.G.C., V.S.); Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (L.L.); and Department of Outcomes Research, Cleveland Clinic, Cleveland, Ohio (D.I.S.).
  • Submitted for publication April 17, 2017. Accepted for publication August 24, 2017.
    Submitted for publication April 17, 2017. Accepted for publication August 24, 2017.×
  • Address correspondence to Dr. Sessler: Cleveland Clinic, 9500 Euclid Ave., P77, Cleveland, Ohio 44195. DS@OR.org. Information on purchasing reprints may be found at www.anesthesiology.org or on the masthead page at the beginning of this issue. Anesthesiology’s articles are made freely accessible to all readers, for personal use only, 6 months from the cover date of the issue.
Article Information
Perioperative Medicine / Clinical Science / Practice Management / Quality Improvement
Perioperative Medicine   |   January 2018
Comparison of an Updated Risk Stratification Index to Hierarchical Condition Categories
Anesthesiology 1 2018, Vol.128, 109-116. doi:10.1097/ALN.0000000000001897
Anesthesiology 1 2018, Vol.128, 109-116. doi:10.1097/ALN.0000000000001897
Abstract

Background: The Risk Stratification Index and the Hierarchical Condition Categories model baseline risk using comorbidities and procedures. The Hierarchical Condition categories are rederived yearly, whereas the Risk Stratification Index has not been rederived since 2010. The two models have yet to be directly compared. The authors thus rederived the Risk Stratification Index using recent data and compared their results to contemporaneous Hierarchical Condition Categories.

Methods: The authors reimplemented procedures used to derive the original Risk Stratification Index derivation using the 2007 to 2011 Medicare Analysis and Provider review file. The Hierarchical Condition Categories were constructed on the entire data set using software provided by the Center for Medicare and Medicaid Services. C-Statistics were used to compare discrimination between the models. After calibration, accuracy for each model was evaluated by plotting observed against predicted event rates.

Results: Discrimination of the Risk Stratification Index improved after rederivation. The Risk Stratification Index discriminated considerably better than the Hierarchical Condition Categories for in-hospital, 30-day, and 1-yr mortality and for hospital length-of-stay. Calibration plots for both models demonstrated linear predictive accuracy, but the Risk Stratification Index predictions had less variance.

Conclusions: Risk Stratification discrimination and minimum-variance predictions make it superior to Hierarchical Condition Categories. The Risk Stratification Index provides a solid basis for care-quality metrics and for provider comparisons.