Patients With Low Socioeconomic Status More Likely to Present for Non-Elective Ovarian Cancer Surgery [34H

Abstract

INTRODUCTION: Non-elective surgery, performed less than 24 hours after presentation, is not well described in patients with gynecologic malignancy. Using the National Readmissions Database (NRD), we characterized non-elective hospital admissions for patients undergoing ovarian cancer surgery. METHODS: We evaluated the NRD for patients undergoing ovarian cancer surgery between 2010 and September 2015. Primary outcome was characterizing demographics and comorbidities of patients presenting non-electively. Secondary outcomes were mortality, length of stay (LOS), and adjusted costs at index hospitalization, as well as 30-day readmission rates. Multivariable analysis identified predictors and outcomes of non-elective presentation. RESULTS: Of 45,572 patients undergoing ovarian cancer surgery, 9,136 (20.1%) were classified as non-elective. Non-elective patients had a higher average Elixhauser comorbidity index (3.6 vs. 3.2, P<.001), greater Medicaid coverage (14.0 vs. 6.5%, P<.001), and reduced private insurance coverage (37.5 vs. 47.3%, P<.001) relative to elective patients. Multivariable analysis revealed that patients presenting non-electively had higher mortality (OR 3.00 [95% Confidence Interval (CI) 2.37-3.81]) and 30-day readmission rates (OR 1.30 [1.20-1.41]) than elective patients. After adjustment, non-elective patients spent 3.3 more days in the hospital [95% CI 3.1-3.6]) with $6,396 more in adjusted costs [95% CI $5,667-7,125]. Significant predictors of non-elective admission included lowest income quartile relative to highest (OR 1.43 [1.28-1.61]) and age less than 50 relative to age 50-69 (OR 1.52 [1.41-1.64]). CONCLUSION: The rate of non-elective ovarian cancer surgery remains high, with increased patient mortality and resource utilization. An independent association between lower income and higher rates of non-elective surgery was observed, highlighting the need to address low socioeconomic populations to prevent emergent hospitalization.