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Using medicare claims to estimate risk-adjusted performance of Pennsylvania trauma centers

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  • Alexis M Zebrowski
  • Phillipe Loher
  • David G Buckler
  • Isidore Rigoutsos
  • Brendan G Carr
  • Douglas J Wiebe

Abstract

Trauma centers use registry data to benchmark performance using a standardized risk adjustment model. Our objective was to utilize national claims to develop a risk adjustment model applicable across all hospitals, regardless of designation or registry participation. Patients from 2013–14 Pennsylvania Trauma Outcomes Study (PTOS) registry data were probabilistically matched to Medicare claims using demographic and injury characteristics. Pairwise comparisons established facility linkages and matching was then repeated within facilities to link records. Registry models were estimated using GLM and compared with five claims-based LASSO models: demographics, clinical characteristics, diagnosis codes, procedures codes, and combined demographics/clinical characteristics. Area under the curve and correlation with registry model probability of death were calculated for each linked and out-of-sample cohort. From 29 facilities, a cohort comprising 16,418 patients were linked between datasets. Patients were similarly distributed: median age 82 (PTOS IQR: 74–87 vs. Medicare IQR: 75–88); non-white 6.2% (PTOS) vs. 5.8% (Medicare). The registry model AUC was 0.86 (0.84–0.87). Diagnosis and procedure codes models performed poorest. The demographics/clinical characteristics model achieved an AUC = 0.84 (0.83–0.86) and Spearman = 0.62 with registry data. Claims data can be leveraged to create models that accurately measure the performance of hospitals that treat trauma patients.Author summary: We can leverage claims data to create models that accurately measure the performance of trauma centers while also accounting for patient case mix and injury severity. This represents a new way to benchmark trauma management at hospitals that treat trauma patients but are not accredited as trauma centers. Moreover, this approach can guide the development of regional models of care by using population level outcomes to encourage trauma centers, non-trauma center hospitals, and prehospital systems of care to optimize triage and transfer policies on regional survival.

Suggested Citation

  • Alexis M Zebrowski & Phillipe Loher & David G Buckler & Isidore Rigoutsos & Brendan G Carr & Douglas J Wiebe, 2023. "Using medicare claims to estimate risk-adjusted performance of Pennsylvania trauma centers," PLOS Digital Health, Public Library of Science, vol. 2(6), pages 1-11, June.
  • Handle: RePEc:plo:pdig00:0000263
    DOI: 10.1371/journal.pdig.0000263
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    References listed on IDEAS

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    1. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    2. Finkelstein, Eric A. & Corso, Phaedra S. & Miller, Ted R., 2006. "The Incidence and Economic Burden of Injuries in the United States," OUP Catalogue, Oxford University Press, number 9780195179484, Decembrie.
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