ArticleHealthcare (Amsterdam, Netherlands)2019
Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare.
Article in Healthcare (Amsterdam, Netherlands), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Development and evaluation of the electronic frailty index+ (eFI+) tool for older people: prognostic prediction modelling with integrated decision curve and health economic analysis.Health technology assessment (Winchester, England) · 2026Observational
- Prompt access to outpatient care post-incarceration among adults with a history of substance use: Predisposing, enabling, and need-based factors.Journal of substance use and addiction treatment · 2024Article
- Comparison of Claims-Based Frailty Indices in U.S. Veterans 65 and Older for Prediction of Long-Term Institutionalization and Mortality.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023Article
- Differences In Use Of Services And Quality Of Care In Medicare Advantage And Traditional Medicare, 2010 And 2017.Health affairs (Project Hope) · 2023Article
- Association Between Early Hypertension Control and Cardiovascular Disease Incidence in Veterans With Diabetes.Diabetes care · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundThere 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.
methodsWe 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.
resultsIn 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 < 0.001). Combining RxRisk-VM with claims-based indices enhanced its accuracy over each index alone (all models C ≥ 0.81). Relative model performance was similar for 3-year mortality.
conclusionsThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.