Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

The value of surgical admissions for malignant uterine cancer. A comparative analysis of robotic, laparoscopic, and laparotomy surgery in a university hospital

Bibliographic Data

ID22070439
AuthorsMaria Lucia Specchia (0000-0002-3859-4591, Università Cattolica del Sacro Cuore), Giovanni Arcuri (0000-0002-4137-7416, Agostino Gemelli University Polyclinic), Andrea Di Pilla (0000-0002-5951-9056, Università Cattolica del Sacro Cuore, corresponding author), Emanuele La Gatta (0000-0002-9761-4425, Università Cattolica del Sacro Cuore), Tommaso Osti (0000-0003-1029-9539, Università Cattolica del Sacro Cuore), Prospero Limongelli (Agostino Gemelli University Polyclinic), Giovanni Scambia (0000-0002-9503-9041, Università Cattolica del Sacro Cuore), Rocco Bellantone (0000-0002-0844-3469, Università Cattolica del Sacro Cuore), Rocco Domenico Alfonso Bellantone
Year2022
Volume10
Pages920578-920578
Publication date2022-10-06
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.920578
PMID36276379
OpenAlexW4302303655
LanguageEN
References cited23

Background Robotic surgery for malignant uterine cancer raises issue of economic sustainability for providers. The objective of this study was to assess the value of surgical admissions for malignant uterine cancer in a University Hospital through an analysis of their costs and outcomes by comparing three different surgical approaches (laparotomy, laparoscopic, and robotic surgery). Methods Hospitalizations between 1 January 2019 and 31 October 2021 for malignant uterine cancer surgery were selected and stratified. For each surgical approach, mean values (with 95% confidence intervals, CI) were calculated for cost items. Moreover, 30-day readmission frequency was calculated for the three approaches compared to each other. ANOVA and Student's t -test and relative risk (RR) were used for statistical analysis. A break-even analysis was carried out by evaluating the volume of robotic and non-robotic surgical admissions. Results A total of 1,336 hospitalizations were included in the study, 366 with robotic, 591 with laparoscopic, and 379 with laparotomy surgery. Robotic surgery, compared to laparoscopic and laparotomy ones, showed a statistically significant difference (p < 0.001) in the economic margin, which was largely negative (−1069.18 €; 95%CI:−1240.44-−897.92 €) mainly due to devices cost, and a lower percentage of 30-day readmissions (1.4%; 95%CI: 0.2–2.6%), with a statistically significant difference only vs. laparotomy (p = 0.029) . Laparoscopic compared to laparotomy surgery showed a significantly (p < 0,001) more profitable economic margin (1692.21 €; 95%CI: 1531.75 €−1852.66 €) without a significant difference for 30-day readmissions. Break-even analysis showed that, on average, for each malignant uterine cancer elective surgery performed laparoscopically, 1.58 elective robotic surgeries are sustainable for the hospital (95% CI: 1.23–2.06). Conclusion Break-even analysis could be a useful tool to support hospital management in planning and governance of malignant uterine cancer surgery. Systematic application of this tool will allow defining over time right distribution of robotic, laparoscopic, and laparotomy surgeries' volumes to perform to ensure both quality and economic-financial balance and therefore value of uterine oncological surgery. Concerning research, this study paves the way for a multicentric study, the extension of outcomes of malignant uterine surgery to be considered and assessed, and the future inclusion of other therapeutic interventions in the analysis

Cancer · Confidence interval · General surgery · Laparoscopic surgery · Laparoscopy · Laparotomy · Robotic surgery · Uterine cancer · Endometrial and Cervical Cancer Treatments · Medicine · Surgical Simulation and Training · Uterine Myomas and Treatments · Internal Medicine · Surgery

  • Defining and Implementing Value-Based Health Care

    Open Access•Elizabeth Teisberg, Scott Wallace et al.•Academic Medicine•2020

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae