A stochastic programming approach for chemotherapy appointment scheduling

Chemotherapy appointment scheduling is a challenging problem due to the uncertainty in pre-medication and infusion durations. In this paper, we formulate a two-stage stochastic mixed integer programming model for the chemotherapy appointment scheduling problem under limited availability and number of nurses and infusion chairs. The objective is to minimize the expected weighted sum of nurse overtime, chair idle time, and patient waiting time. The computational burden to solve real-life instances of this problem to optimality is significantly high, even in the deterministic case. To overcome this burden, we incorporate valid bounds and symmetry breaking constraints. Progressive hedging algorithm is implemented in order to solve the improved formulation heuristically. We enhance the algorithm through a penalty update method, cycle detection and variable fixing mechanisms, and a linear approximation of the objective function. Using numerical experiments based on real data from a major oncology hospital, we compare our solution approach with several scheduling heuristics from the relevant literature, generate managerial insights related to the impact of the number of nurses and chairs on appointment schedules, and estimate the value of stochastic solution to assess the significance of considering uncertainty

Renal complications of lipodystrophy: A closer look at the natural history of kidney disease

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144612/1/cen13732_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144612/2/cen13732.pd

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Belirsiz süreler altında kemoterapi randevularının çizelgelenmesi.

Chemotherapy appointment scheduling is a challenging problem due to uncertainty in pre-medication and infusion durations. We formulate a two-stage stochastic mixed integer programming model for chemotherapy appointment scheduling problem under the limited availability and number of nurses, and infusion chairs. The objective is to minimize the expected weighted sum of nurse overtime and patient waiting time. We sampled the pre-medication and infusion durations based on real data of a major oncology hospital. The computation times for the problem are significantly long even for the case of single-scenario problems. In order to strengthen the formulation, valid bounds and symmetry breaking constraints are incorporated. A Progressive Hedging Algorithm is implemented in order to solve the improved formulation. We enhance the algorithm through a penalty update method, cycle detection and variable fixing mechanisms, and linearization of the model objective function. We conduct numerical experiments to compare the progressive hedging algorithm with several scheduling heuristics from the relevant literature. We generate managerial insights related to the impact of the number of nurses and chairs on appointment schedules. Finally, we estimate the value of stochastic solution to assess the significance of considering uncertainty.M.S. - Master of Scienc

Superoxide Dismutase 2 protein levels in blood may act as a prognostic marker for high-risk neuroblastoma patients.

Purpose: Determination of proteomic differences plays an important role in biomarker investigations. Dueto its heterogenic molecular background, identification of certain biomarkers is still a demand both fordiagnosis and prognosis of neuroblastoma. In this study, it is aimed to identify markerproteins/mechanisms that may play role in neuroblastoma prognosis.Material and Methods: Real-time PCR analyses were performed for 2p24.3, 11q23, 1p36 and 17q25status from tumor samples of the patients to determine the risk groups. A proteomic approach was usedfor different risk groups of the disease by using matrix-assisted laser desorption ionization–time of flight(MALDI-TOF/TOF) approach. Mononuclear cell pools from blood samples of patients for different riskgroups were constructed and protein expression changes for different groups were identified.Results: Manganese-superoxide dismutase (SOD2) protein was found to significantly increase in highrisk group of neuroblastoma patients.Conclusion: Our results showed that SOD2 may play an important role in neuroblastoma progressionand be a candidate prognostic peripheral blood marker for neuroblastoma patients.</p