ArticleJAMA network open2018
Assessment of the Medicare Advantage Risk Adjustment Model for Measuring Veterans Affairs Hospital Performance.
Article in JAMA network open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- Machine-learning-based cost prediction models for inpatients with mental disorders in China.BMC psychiatry · 2025Article
- Association Between Self-Reported Health and Reliance on Veterans Affairs for Health Care Among Veterans Affairs Enrollees.JAMA network open · 2023Article
- Clinical Validity of the PROMIS Healthcare Engagement 8-Item Short Form.Journal of general internal medicine · 2023Article
- Long-term care service mix in the Veterans Health Administration after home care expansion.Health services research · 2021Article
- Comparing Complication Rates After Elective Total Knee Arthroplasty Delivered Or Purchased By The VA.Health affairs (Project Hope) · 2021Article
- Psychometric evaluation of a patient-reported item bank for healthcare engagement.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021Article
- Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.BMC public health · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Policymakers and consumers are eager to compare hospitals on performance metrics, such as surgical complications or unplanned readmissions, measured from administrative data. Fair comparisons depend on risk adjustment algorithms that control for differences in case mix. Objective: To examine whether the Medicare Advantage risk adjustment system version 21 (V21) adequately risk adjusts performance metrics for Veterans Affairs (VA) hospitals. Design, Setting, and Participants: This cohort analysis of administrative data from all 5.5 million veterans who received VA care or VA-purchased care in 2012 was performed from September 8, 2015, to October 22, 2018. Data analysis was performed from January 22, 2016, to October 22, 2018. Exposures: A patient's risk as measured by the V21 model. Main Outcomes and Measures: The main outcome was total cost, and the key independent variable was the V21 risk score. Results: Of the 5 472 629 VA patients (mean [SD] age, 63.0 [16.1] years; 5 118 908 [93.5%] male), the V21 model identified 694 706 as having a mental health or substance use condition. In contrast, a separate classification system for psychiatric comorbidities identified another 1 266 938 patients with a mental health condition. The V21 model missed depression not otherwise specified (396 062 [31.3%]), posttraumatic stress disorder (345 338 [27.3%]), and anxiety (129 808 [10.2%]). Overall, the V21 model underestimated the cost of care by $2314 (6.7%) for every person with a mental health diagnosis. Conclusions and Relevance: The findings suggest that current aspirations to engender competition by comparing hospital systems may not be appropriate or fair for safety-net hospitals, including the VA hospitals, which treat patients with complex psychiatric illness. Without better risk scores, which is technically possible, outcome comparisons may potentially mislead consumers and policymakers and possibly aggravate inequities in access for such vulnerable populations.
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