Chan, Andrew K. and Shahrestani, Shane and Ballatori, Alexander M. and Orrico, Katie O. and Manley, Geoffrey T. and Tarapore, Phiroz E. and Huang, Michael and Dhall, Sanjay S. and Chou, Dean and Mummaneni, Praveen V. and DiGiorgio, Anthony M. (2022) Is the Centers for Medicare and Medicaid Services Hierarchical Condition Category Risk Adjustment Model Satisfactory for Quantifying Risk After Spine Surgery? Neurosurgery . ISSN 0148-396X. doi:10.1227/neu.0000000000001980. (In Press) https://resolver.caltech.edu/CaltechAUTHORS:20220518-829183000
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Abstract
Background: The Centers for Medicare and Medicaid Services (CMS) hierarchical condition category (HCC) coding is a risk adjustment model that allows for the estimation of risk—and cost—associated with health care provision. Current models may not include key factors that fully delineate the risk associated with spine surgery. Objective: To augment CMS HCC risk adjustment methodology with socioeconomic data to improve its predictive capabilities for spine surgery. Methods: The National Inpatient Sample was queried for spinal fusion, and the data was merged with county-level coverage and socioeconomic status variables obtained from the Brookings Institute. We predicted outcomes (death, nonroutine discharge, length of stay [LOS], total charges, and perioperative complication) with pairs of hierarchical, mixed effects logistic regression models—one using CMS HCC score alone and another augmenting CMS HCC scores with demographic and socioeconomic status variables. Models were compared using receiver operating characteristic curves. Variable importance was assessed in conjunction with Wald testing for model optimization. Results: We analyzed 653 815 patients. Expanded models outperformed models using CMS HCC score alone for mortality, nonroutine discharge, LOS, total charges, and complications. For expanded models, variable importance analyses demonstrated that CMS HCC score was of chief importance for models of mortality, LOS, total charges, and complications. For the model of nonroutine discharge, age was the most important variable. For the model of total charges, unemployment rate was nearly as important as HCC score. Conclusion: The addition of key demographic and socioeconomic characteristics substantially improves the CMS HCC risk-adjustment models when modeling spinal fusion outcomes. This finding may have important implications for payers, hospitals, and policymakers.
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Additional Information: | © 2022 Congress of Neurological Surgeons. | ||||||||||||||||||
DOI: | 10.1227/neu.0000000000001980 | ||||||||||||||||||
Record Number: | CaltechAUTHORS:20220518-829183000 | ||||||||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20220518-829183000 | ||||||||||||||||||
Official Citation: | Chan, Andrew K.; Shahrestani, Shane; Ballatori, Alexander M.; Orrico, Katie O.; Manley, Geoffrey T.; Tarapore, Phiroz E.; Huang, Michael; Dhall, Sanjay S.; Chou, Dean; Mummaneni, Praveen V.; DiGiorgio, Anthony M. Is the Centers for Medicare and Medicaid Services Hierarchical Condition Category Risk Adjustment Model Satisfactory for Quantifying Risk After Spine Surgery?, Neurosurgery: May 16, 2022; DOI: 10.1227/neu.0000000000001980 | ||||||||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||||||
ID Code: | 114794 | ||||||||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||||||||
Deposited By: | Tony Diaz | ||||||||||||||||||
Deposited On: | 19 May 2022 16:33 | ||||||||||||||||||
Last Modified: | 19 May 2022 16:33 |
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