1,721,029 research outputs found
The real time management of operating rooms
No full textAt the operational decision level, the problem arising in the Operating Room (OR) planning is also called “surgery process scheduling”, which usually consists in selecting elective patients from a waiting list and assigning them to a specific operating room on a specific day, and determining the sequence of surgical procedures and the allocation of resources for each OR session. The Real Time Management (RTM) of operating rooms is the decision problem arising during the fulfillment of the surgery process scheduling, that is the problem of supervising the execution of such a schedule and, in case of delays, to take the more rational decision regarding the surgery cancellation or the overtime assignment. The RTM is characterized by the uncertainty of its main parameters, that is, for instance, the duration of a surgery and the arrivals of non-elective patients. In this chapter we propose online optimization approaches for the RTM capable to deal with (1) the elective and non-elective patient flows within a single surgical pathway (Non-Elective Worst Fit algorithm), and with (2) the resource sharing among different surgical pathways of elective patients (Flexible Overtime Allocation and Flexible Scheduling policies). We assess the effectiveness of the proposed solutions on simulated surgical clinical pathways under several scenarios. From a methodological point of view, our analysis suggested that online optimization can be a suitable methodology to deal with the inherent stochastic aspects arising in the majority of the health care problems
Mining the patient flow through an emergency department to deal with overcrowding
No full textThe Emergency Department (ED) management presents a really high complexity due to the admissions of patients with a wide variety of diseases and different urgency, which require the execution of different activities involving human and medical resources. This have an impact on ED overcrowding that may affect the quality and access of health care. In this paper we apply Process Mining techniques to a real case study: from the ED database, discovery techniques identify the possible paths of a patient on the basis of the information available at the triage. Our purpose is to obtain precise process models for replicating and predicting the patient paths
An ad hoc process mining approach to discover patient paths of an Emergency Department
No full textThe Emergency Department (ED) management presents a really high complexity due to the admissions of patients with a wide variety of diseases and different urgency, which require the execution of different activities involving human and medical resources. This can have an impact on ED overcrowding that may affect the quality and access of health care. In this paper we propose an ad hoc process mining approach to discover the paths of the patients served by an ED. Our aim is to obtain a process model capable (1) to replicate properly the possible patient paths, and (2) to predict the next activities in the view of a possible application to online optimisation. To prove its effectiveness, we apply our ad hoc approach to a real case study
The management of non-elective patients: shared vs. dedicated policies
No full textThe approaches for the management of elective and non-elective surgery can be classified with respect to the choice of sharing or not the operating theater. The dedicated operating room policy consists in reserving, each day, one or more operating rooms to perform only non-elective surgeries. Conversely, the shared operating room policy allows to perform elective and non-elective surgeries in the same operating room session. Furthermore, hybrid policies are defined providing, each day, both dedicated and shared operating rooms. The issue of adopting one of these policies is debated in the literature and they all could be the best policy depending on the scenario and the operative conditions. In this paper we propose a hybrid and flexible model to deal with the surgery process scheduling of both elective and non-elective patients, in which new online and offline optimization algorithms are introduced, taking into account both patient- and facility-centered objectives. The aim of this paper is to provide a detailed comparison among different policies taking into account several scenarios and operative conditions in such a way to consider the characteristics of the operating theater and those of the patients it serves
A hybrid model for the analysis of a surgical pathway
No full textIn this paper we focus our attention on the analysis of a surgical pathway from a patient-centred point of view. The main concern of this work is the introduction of some optimization modules in the management of the most critical resources in a surgical pathway, that is the stay beds and the operating rooms, and to evaluate their impact with respect to a set of patient- and facility- centred indices. We propose a hybrid simulation and optimization model: simulation is used in order to generate a real situation with respect to the inherent stochasticity of the problem while optimization is used to take the best decisions in different points of the surgical pathway
The optimization of a surgical clinical pathway
No full textA Clinical Pathway (CP) can be conceived as an algorithm based on a flow chart that details all decisions and treatments related to a patient with a given pathology. CPs can be considered an operational tool in the clinical treatment of diseases, from a patient-focused point of view. Although it has been shown their benefits in clinical practices, little attention has been dedicated to study how CP can optimize the use of resources.We focus our attention on the analysis of a surgical CP from a patient-centred point of view in order to optimize the most critical resources of a surgical CP, and to evaluate the impact of the optimization with respect to a set of patient- and facility-centred indices
Patient–Centred Objectives as an Alternative to Maximum Utilisation: Comparing Surgical Case Solutions
No full textOperating Room (OR) planning and scheduling is a research topic widely discussed in the literature, in which several performance criteria have been proposed to evaluate the OR planning decisions. Although the OR utilisation is the leading objective, from research experiences, long waiting lists lead to a satisfactory filling of ORs even fixing other objectives. In this paper we analyse the impact on OR utilisation of two patient–centred objectives: the waiting time minimisation and the workload balance. In the former the most commonly used patient–centred criterion is taken into account, while the latter leads to a smooth stay bed occupancies determining a smooth workload in the ward and, by consequence, an improved quality of care provided to patients. To the best of our knowledge, a comparison of the planning determined by these criteria is not yet available in literature
An online optimization approach for the Real Time Management of operating rooms
No full textThe Real Time Management (RTM) of operating rooms is the decision problem arising during the fulfilment of the surgery process scheduling of elective patients, that is the problem of supervising the execution of such a schedule and, in case of delays, to take the more rational decision regarding the surgery cancellation or the overtime assignment. The main concern of this paper is to propose a model for the RTM and to evaluate its impact on the OR performance assessed by a set of patient- and facility-centred indices. To this end, we consider a generic surgical clinical pathway for elective patients-inspired to a real case study-in which we evaluate the introduction of an online optimization approach for the RTM and some additional optimization modules to deal with the surgery process scheduling problem. To the best of our knowledge, the RTM is not clearly addressed in the literature and this is the first attempt to propose an online approach in the context of surgery process scheduling. We propose a hybrid simulation and optimization model in which simulation is used to model the inherent stochasticity and to replicate the elective patient flow on which the online approach for the RTM and the additional optimization modules operates. We report an accurate computational analysis proving the effectiveness of the proposed approach to the RTM. Finally, we demonstrate the capability and the flexibility of our approach extending our hybrid model to deal with emergency surgeries and different trained surgery teams
Integrating Mental Health into a Primary Care System: A Hybrid Simulation Model
No full textDepression and anxiety appear to be the most frequently encountered psychiatric problems in primary care patients. It has been also reported that primary care physicians under-diagnose psychiatric illness in their patients. Although collaborative care has been shown to be a cost-effective strategy for treating mental disorders, to the best of our knowledge few attempts of modelling collaborative care interventions in primary care are known in literature. The main purpose of this paper is to propose a hybrid simulation approach to model the integration of the collaborative care for mental health into the primary care pathway in order to allow an accurate cost-effectiveness analysis. Quantitative analysis are reported exploiting different and independent input data sources in order to overcome the problem of the data appropriateness. The analysis demonstrates the capability of the collaborative care to reduce the usual general practitioner overcrowding and to be cost-effective when the psychological treatments have a success rate around the
Modeling the rational behavior of individuals on an e-commerce system
No full textWith the increasing popularity of e-commerce systems, commercial transactions are becoming more and more frequent. Such transactions are not direct but mediated, putting the buyer in a position of weakness with respect to the seller, especially in the case of a failure of a transaction. The literature showed that the reputation can play an important role to reduce the risks of the buyer in the current e-commerce environment. An online reputation management system (RMS) maintains the reputation, made of beliefs and/or opinions, that are generally held about someone or something, and it can guarantee the reliability of the transactions that take place in an e-commerce system. Despite of the fact that the basic element of a RMS – the interaction between the seller and the buyer – is a classical field of application of the Game Theory (GT) methodologies, the use of a GT approach in this context seems quite limited and this is probably due to its solution complexity. A way to deal with such a complexity is by exploiting the capability of the agent based simulation (ABS) approach. In this paper, we propose a hybrid GT and ABS model for the analysis of an e-commerce system in which a centralized reputation system is maintained by a trusted third party. We report an extensive quantitative analysis in order to validate the proposed model, and to evaluate the impact of a set of buyers’ and sellers’ policies on the behavior of the e-commerce system
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