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Background: As a minimally invasive technique, robot-assisted hysterectomy (RAH) offers surgical advantages and significant reduction in morbidity compared to open surgery. Despite the increasing use of RAH in benign gynaecology, there is limited data on its cost-effectiveness, especially in a European context. Our goal is to assess the costs of the different hysterectomy approaches, to describe their clinical outcomes, and to evaluate the impact of introduction of RAH on the rates of different types of hysterectomy., Methods: A retrospective single-centre cost-analysis was performed for patients undergoing a hysterectomy for benign indications. Abdominal hysterectomy (AH), vaginal hysterectomy (VH), laparoscopic hysterectomy (LH), laparoscopically assisted vaginal hysterectomy (LAVH) and RAH were included. We considered the costs of operating room and hospital stay for the different hysterectomy techniques using the "Activity Centre-Care program model". We report on intra- and postoperative complications for the different approaches as well as their cost relationship., Results: Between January 2014 and December 2021, 830 patients were operated; 67 underwent VH (8%), 108 LAVH (13%), 351 LH (42%), 148 RAH (18%) and 156 AH (19%). After the implementation and learning curve of a dedicated program for RAH in 2018, AH declined from 27.3% in 2014-2017, to 22.1% in 2018 and 6.9 % in 2019-2021. The reintervention rate was 3-4% for all surgical techniques. Pharmacological interventions and blood transfusions were performed after AH in 28%, and in 17-22% of the other approaches. AH had the highest hospital stay cost with an average of €2236.40. Mean cost of the hospital stay ranged from €1136.77-€1560.66 for minimally invasive techniques. The average total costs for RAH were €6528.10 compared to €4400.95 for AH., Conclusion: Implementation of RAH resulted in a substantial decrease of open surgery rate. However, RAH remains the most expensive technique in our cohort, mainly due to high material and depreciation costs. Therefore, RAH should not be considered for every patient, but for those who would otherwise need more invasive surgery, with higher risk of complications. Future prospective studies should focus on the societal costs and patient reported outcomes, in order to do cost-benefit analysis and further evaluate the exact value of RAH in the current healthcare setting., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Wouter Froyman has received speaker fees from Intuitive Surgical, unrelated to the submitted work., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In hospitals, the efficient planning of the operating rooms (ORs) is difficult due to the uncertainty inherent to surgical services. This is especially true for the inpatient surgical department where complex and long surgeries are often performed along with surgeries on emergency patients. This paper aims to improve the scheduling of the inpatient department by partitioning the elective surgeries into the more predictable surgeries (MPS) group and the less predictable surgeries (LPS) group, based on surgery duration variability, and by scheduling each of the two surgery groups in different ORs. Through a simulation study that comprehensively investigates the impact of the partitioning on different performance measures under various environmental settings, we report important findings and insights. First, partitioning can effectively shorten the waiting times of elective patients for both MPS and LPS groups, but the option should be allowed to reassign patients from the MPS or LPS ORs to the other ORs when needed. Meanwhile, partitioning sometimes slightly increases the elective cancellation rate. Second, the ability to use the available capacity of the ORs as much as possible is key to reducing elective waiting times. Third, partitioning might slightly worsen the waiting times of emergency patients, while the slightly negative impact on emergency patients decreases when the number of ORs is higher. Fourth, the beneficial impact of partitioning on elective patients increases with an increased patient demand. Last, for the settings considered in this study there was no benefit in partitioning the elective patients into more than two groups., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Study Design: Retrospective, single-center analysis., Objective: To calculate the total clinical hospital cost of the Adult Spinal Deformity (ASD) care trajectory, to explain cost variability by patient and surgery characteristics, and to identify areas of process improvement opportunities., Summary of Background Data: ASD is associated with a high financial and clinical burden on society. ASD care thus requires improved insights in costs and its drivers as a critical step toward the improvement of value, i.e., the ratio between delivered health outcome and associated costs., Methods: Patient characteristics and surgical variables were collected following ethical approval in a cohort of 139 ASD patients, treated between December, 2014 and January, 2018. Clinical hospital costs were calculated, including all care activities, from initial consultation to 1 year after initial surgery (excl. overhead) in a university hospital setting. Multiple linear regression analysis was performed to analyze the impact of patient and surgical characteristics on clinical costs., Results: 75.5% of the total clinical hospital cost (&OV0556;27,865) was incurred during initial surgery with costs related to the operating theatre (80.3%), nursing units (11.9%), and intensive care (2.9%) being the largest contributors. 57.5% of the variation in total cost could be explained in order of importance by surgical invasiveness, age, coronary disease, single or multiple-staged surgery, and mobility status. Revision surgery, unplanned surgery due to complications, was found to increase average costs by 87.6% compared with elective surgeries (&OV0556; 44,907 (± &OV0556; 23,429) vs. &OV0556; 23,944 (± &OV0556; 7302))., Conclusion: This study identified opportunities for process improvement by calculating the total clinical hospital costs. In addition, it identified patient and treatment characteristics that predict 57.5% of cost variation, which could be taken into account when developing a payment system. Future research should include outcome data to assess variation in value., Level of Evidence: 4.

In many hospitals there are patients who receive surgery later than what is medically indicated. In one of Europe's largest hospitals, the University Hospital Leuven, this is the case for approximately every third patient. Serving patients late cannot always be avoided as a highly utilized OR department will sometimes suffer capacity shortage, occasionally leading to unavoidable delays in patient care. Nevertheless, serving patients late is a problem as it exposes them to an increased health risk and hence should be avoided whenever possible. In order to improve the current situation, the delay in patient scheduling had to be quantified and the responsible mechanism, the scheduling process, had to be better understood. Drawing from this understanding, we implemented and tested realistic patient scheduling methods in a discrete event simulation model. We found that it is important to model non-elective arrivals and to include elective rescheduling decisions made on surgery day itself. Rescheduling ensures that OR related performance measures, such as overtime, will only loosely depend on the chosen patient scheduling method. We also found that capacity considerations should guide actions performed before the surgery day such as patient scheduling and patient replanning. This is the case as those scheduling strategies that ensure that OR capacity is efficiently used will also result in a high number of patients served within their medically indicated time limit. An efficient use of OR capacity can be achieved, for instance, by serving patients first come, first served. As applying first come, first served might not always be possible in a real setting, we found it is important to allow for patient replanning.