Dataset Information

Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare.

ABSTRACT: Background:There is systemic undercoding of medical comorbidities within administrative claims in the Department of Veterans Affairs (VA). This leads to bias when applying claims-based risk adjustment indices to compare outcomes between VA and non-VA settings. Our objective was to compare the accuracy of a medication-based risk adjustment index (RxRisk-VM) to diagnostic claims-based indices for predicting mortality.

Methods:We modified the RxRisk-V index (RxRisk-VM) by incorporating VA and Medicare pharmacy and durable medical equipment claims in Veterans dually-enrolled in VA and Medicare in 2012. Using the concordance (C) statistic, we compared its accuracy in predicting 1 and 3-year all-cause mortality to the following models: demographics only, demographics plus prescription count, or demographics plus a diagnostic claims-based risk index (e.g., Charlson, Elixhauser, or Gagne). We also compared models containing demographics, RxRisk-VM, and a claims-based index.

Results:In our cohort of 271,184 dually-enrolled Veterans (mean age?=?70.5 years, 96.1% male, 81.7% non-Hispanic white), RxRisk-VM (C?=?0.773) exhibited greater accuracy in predicting 1-year mortality than demographics only (C?=?0.716) or prescription counts (C?=?0.744), but was less accurate than the Charlson (C?=?0.794), Elixhauser (C?=?0.80), or Gagne (C?=?0.810) indices (all P?
Conclusions:The RxRisk-VM index exhibited a high level of, but slightly less, accuracy in predicting mortality in comparison to claims-based risk indices.

Implications:Its application may enhance the accuracy of studies examining VA and non-VA care and enable risk adjustment when diagnostic claims are not available or biased.

Level of evidence:Level 3.

SUBMITTER: Radomski TR

PROVIDER: S-EPMC6814520 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare.

Radomski Thomas R TR Zhao Xinhua X Hanlon Joseph T JT Thorpe Joshua M JM Thorpe Carolyn T CT Naples Jennifer G JG Sileanu Florentina E FE Cashy John P JP Hale Jennifer A JA Mor Maria K MK Hausmann Leslie R M LRM Donohue Julie M JM Suda Katie J KJ Stroupe Kevin T KT Good Chester B CB Fine Michael J MJ Gellad Walid F WF

Healthcare (Amsterdam, Netherlands) 20190426 4

<h4>Background</h4>There is systemic undercoding of medical comorbidities within administrative claims in the Department of Veterans Affairs (VA). This leads to bias when applying claims-based risk adjustment indices to compare outcomes between VA and non-VA settings. Our objective was to compare the accuracy of a medication-based risk adjustment index (RxRisk-VM) to diagnostic claims-based indices for predicting mortality.<h4>Methods</h4>We modified the RxRisk-V index (RxRisk-VM) by incorporati ...[more]

PMID: 31031120

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Dataset Information

Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare.

Publications

Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare.

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