An initiative to improve mortality index in gynecologic oncology.

Abstract

256 Background: The mortality index (MI) is a quality metric that measures the ratio of actual mortality to expected mortality among inpatients. Expected mortality is a probability calculation based on patient risks and comorbidities. A MI of < 1.0 represents that fewer patients die while admitted to the hospital than expected. Methods: We formed a multidisciplinary team that included Gynecologic Oncology (GO), Health Information Management, Clinical Informatics, Revenue Operations, Coding and Institutional Compliance experts. Our aim was to decrease the GO MI by 10% within a year. Quality Improvement Assessment Board approval was obtained. GO clinical providers were educated on proper documentation of patient comorbidities and severity of illness. Audits of the documentation were performed by the multidisciplinary team. GO patients perceived at high-risk of inpatient mortality were identified for additional review. All GO inpatient deaths were reviewed at the monthly GO Morbidity and Mortality conference and opportunities for avoidance of inpatient death were discussed. Plan-Do-Study-Act (PDSA) cycles were repeated with adjustments made to the review and education processes. Baseline (BL) 8/2017-7/2018 and interim post-intervention (PI) 11/2018-2/2019 outcomes were compared using the Mann Whitney U test. Results: The BL median number of inpatient deaths per month was 2 (range 0-7), with a median expected mortality of 2.96 (range 1.46-5.11), and a median MI of 0.84 (range 0-1.37). The PI median number of inpatient deaths per month was 2.5 (range 2-5), with a median expected mortality of 4.24 (range 3.77-5.06), and a median MI of 0.56 (range 0.53-1.27). The number of inpatient deaths per month was similar between groups (2 vs 2.5; p = 0.49) but the expected mortality increased from to 2.96 to 4.24 (p = 0.03). MI decreased by 33% between BL and PI (0.84 vs 0.56). Conclusions: Inpatient mortality is an important quality metric. Accurate measurement of expected mortality is critical and requires proper documentation. This can be improved through education, review and frequent assessment by PDSA cycles. Our preliminary results show improvement in accurate documentation and measurement of expected mortality resulting in a decrease in MI.

CKS1B promotes the growth of ovarian cancer cells by regulating the expression of PD-L1

“…Ovarian cancer is the third most common malignancy in the female reproductive system [1][2][3]. Ovarian cancer is the fifth leading cause of death among gynecological cancers, as reported by the American Cancer Society [4].…”