Risk-Scoring Model for Prediction of Non-Home Discharge in Epithelial Ovarian Cancer Patients

BackgroundIdentification of preoperative factors predictive of non-home discharge after surgery for epithelial ovarian cancer (EOC) may aid counseling and optimize discharge planning. We aimed to determine the association between preoperative risk factors and non-home discharge.Study DesignPatients who underwent primary surgery for EOC at Mayo Clinic between January 2, 2003 and December 29, 2008 were included. Demographic, preoperative, and intraoperative factors were retrospectively abstracted. Logistic regression models were fit to identify preoperative factors associated with non-home discharge. Multivariable models were developed using stepwise and backward variable selection. A risk-scoring system was developed for use in preoperative counseling.ResultsWithin our cohort of 587 EOC patients, 12.8% were not discharged home (61 went to a skilled nursing facility, 1 to a rehabilitation facility, 1 to hospice, and there were 12 in-hospital deaths). Median length of stay was 7 days (interquartile range [IQR] 5, 10 days) for patients dismissed home compared with 11 days (IQR 7, 17 days) for those with non-home dismissals (p < 0.001). In multivariable analyses, patients with advanced age (odds ratio [OR] 3.75 95% CI [2.57, 5.48], p < 0.001), worse Eastern Cooperative Oncology Group (ECOG) performance status (OR 0.92 [95% CI 0.43, 1.97] for ECOG performance status 1 vs 0 and OR 5.40 (95% CI 2.42, 12.03) for score of 2+ vs 0; p < 0.001), greater American Society of Anesthesiologists (ASA) score (OR 2.03 [95% CI 1.02, 4.04] for score ≥3 vs < 3, p = 0.04), and higher CA-125 (OR 1.28 [95% CI 1.12, 1.46], p < 0.001) were less likely to be discharged home. The unbiased estimate of the c-index was excellent at 0.88, and the model had excellent calibration.ConclusionsIdentification of preoperative factors associated with non-home discharge can assist patient counseling and postoperative disposition planning.