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Objective Intracranial meningiomas are the most commonly diagnosed brain tumor in the United States. With increasing incidence, efficient allocation of limited health care resources is a critical component of emerging value-based models of care. The purpose of this study was to evaluate the effect of patient and hospital variables on metrics of value-based care. Methods The Statewide Planning and Research Cooperative System database was queried for records of patients undergoing intracranial meningioma surgery in New York State from 1995 to 2015. Multivariate logistic regression was used to investigate the effect of hospital volume and patient demographics on 30-day readmissions, 30-day mortality, prolonged length of stay (pLOS), and excess hospital charges. Results Among the 14,239 patients included, 10,252 (72%) cases were performed at high-volume centers (HVC) (>75th percentile). HVC were associated with lower rates of readmissions, mortality, and pLOS, but higher hospital charges. In the multivariate analysis, HVC had reduced odds of pLOS (odds ratio, 0.56; P < 0.0001) and 30-day mortality (odds ratio, 0.39; P < 0.0001). Patient variables associated with adverse outcomes in the multivariate model included advanced age, male gender, higher Charlson Comorbidity Index, lower socioeconomic status (low income, Medicaid, and Medicare insurance), black race, and Hispanic ethnicity. These populations were more likely to undergo treatment at lower-volume centers. Conclusions This statewide population analysis of readmissions, mortality, length of stay, and hospital charges after intracranial meningioma surgery identified patient predictors of adverse outcomes. These determinants may be used by hospitals to develop improved systems of care in at-risk populations. Highlights • Rates of meningioma surgery are increasing, particularly at high-volume centers. • High-volume centers are associated with better outcomes but higher hospital charges. • Patient-level factors were significant determinants for 30-day readmissions. • Racial, ethnic, and socioeconomic factors influence access to high-quality care. [ABSTRACT FROM AUTHOR]