Abstract

To assess the potential effects of implementing minimum hospital volume standards for ovarian cancer on survival and access to care. We used the National Cancer Database to identify hospitals treating women with ovarian cancer from 2005 to 2015. We estimated the number of patients treated by each hospital during the prior year. Multivariable models were used to estimate the ratio of observed/expected 60-day, and 1-, 2- and 5-year mortalities. The mean predicted observed/expected ratio of hospitals was plotted based on prior year volume. The number of hospitals that would be restricted if minimum-volume standards were implemented was modeled. A total of 136,196 patients treated at 1,321 hospitals were identified. Increasing hospital volume was associated with decreased 60-day (P=.004), 1-year (P<.001), 2-year (P<.001) and 5-year (P=.008) mortality. In 2015, using a minimum-volume cutpoint of one case in the prior year would eliminate 144 (13.6%) hospitals (treated 2.6% of all patients); a cutpoint of three would eliminate 364 (34.5%) hospitals (treated 7.7% of the patients). The mean observed/expected ratios for hospitals with a prior year volume of 1 was 1.14 for 60-day mortality, 1.06 for 1-year mortality, 1.12 for 2-year mortality, and 1.08 for 5-year mortality. Among hospitals with a prior year volume of one, 49.2% had an observed/expected ratio for 2-year mortality of at least 1 (indicating worse than expected performance), and 50.8% had an observed/expected ratio of less than 1 (indicating better than expected performance). The mean observed/expected ratios for hospitals with a prior year volume of two or less were 1.11 for 60-day mortality, 1.09 for 1-year mortality, 1.08 for 2-year mortality, and 1.07 for 5-year mortality. Implementing a minimum-volume standard of one case in the prior year would result in one fewer death for every 198 patients at 60 days, for every 613 patients at 1 year, and for every 62 patients at 5 years. Implementation of minimum hospital volume standards could restrict care at a significant number of hospitals, including many centers with better-than-predicted outcomes.

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