Optimal scheduling of logistical support for medical resources order and shipment in community health service centers

Purpose: This paper aims to propose an optimal scheduling for medical resources order and shipment in community health service centers (CHSCs). Design/methodology/approach: This paper presents two logistical support models for scheduling medical resources in CHSCs. The first model is a deterministic planning model (DM), which systematically considers the demands for various kinds of medical resources, the lead time of supplier, the storage capacity and other constraints, as well as the integrated shipment planning in the dimensions of time and space. The problem is a multi-commodities flow problem and is formulated as a mixed 0-1 integer programming model. Considering the demand for medical resources is always stochastic in practice, the second model is constructed as a stochastic programming model (SM). A solution procedure is developed to solve the proposed two models and a simulation-based evaluation method is proposed to compare the performances of the proposed models. Findings and Findings: The main contributions of this paper includes the following two aspects: (1) While most research on medical resources optimization studies a static problem taking no consideration of the time evolution and especially the dynamic demand for such resources, the proposed models in our paper integrate time-space network technique, which can find the optimal scheduling of logistical support for medical resources order and shipment in CHSCs effectively. (2) The logistics plans in response to the deterministic demand and the time-varying demand are constructed as 0-1 mixed integer programming model and stochastic integer programming model, respectively. The optimal solutions not only minimize the operation cost of the logistics system, but also can improve the order and shipment operation in practice. Originality/value: Currently, medical resources in CHSCs are purchased by telephone or e-mail. The important parameters in decision making, i.e. order/shipment frequency and order quantity, are manually determined by the staff with experience according to the average demand in the past years/months. The planned schedules may not be efficient, or may not be at all feasible to satisfy all demands since a large portion of customer service requests in CHSCs are uncertain and tine-varying. The proposed methods in this paper could be effective ways in solving the problems in practice.Peer Reviewe

Aplicação de apoio ao agendamento cirúrgico

Mestrado em Decisão Económica e EmpresarialUm dos problemas que surge dentro do bloco operatório é o agendamento de cirurgias eletivas, ou seja, as cirurgias cuja realização tenha data previamente marcada. Na maioria dos hospitais portugueses, esta continua ainda a ser uma tarefa manual, difícil, e que exige muito tempo ao planeador cirúrgico. Este trabalho desenvolve uma ferramenta informática que permite apoiar o planeador cirúrgico, nas suas decisões, ao nível do agendamento dos casos cirúrgicos. Esta ferramenta permite, ao planeador cirúrgico, visualizar soluções obtidas através de procedimentos heurísticos ou métodos exatos, utilizados para otimizar o planeamento de cirurgias eletivas, e que foram anteriormente desenvolvidos. O programa informático foi desenvolvido em Microsoft Excel, utilizando uma linguagem de programação em Visual Basic for Applications. Esta ferramenta apresenta uma visualização intuitiva do horário do bloco operatório, permitindo segmentá-lo por prioridade cirúrgica, especialidade cirúrgica ou por cirurgião. Permite ainda realizar trocas de cirurgias agendadas e responder adequadamente a ocorrências inesperadas (ao nível do planeamento cirúrgico), validando automaticamente o novo plano, de acordo com as restrições relevantes nos recursos hospitalares. Informação visual e relatórios quantitativos estão facilmente disponíveis para o planeador cirúrgico, bem como para os profissionais clínicos e administradores hospitalares. A ferramenta desenvolvida não só facilita o processo de agendamento, mas também contribui para melhorar o controlo interno do hospital no que se refere ao bloco operatório. Trata-se de um programa para os hospitais, de fácil utilização (user-friendly), que não requer encargos adicionais com licenças de produtos e cuja necessidade de formação é mínima.It is well known that the surgical suite represents one of the major cost and profit units of the hospital. A difficult problem arising in the surgical suite is the scheduling of elective patients. In most Portuguese hospitals this is still a hard and time consuming handmade task by the surgical planner. Considering these issues, a software tool was developed in order to support the surgical planner in his decisions about elective case scheduling. This tool works as an interface between the solutions obtained by some heuristic or exact procedure previously developed to optimize the elective surgery scheduling previously developed and the surgical planner. The software was developed in Microsoft Excel using a Visual Basic for Applications programming language. This tool presents an intuitive visualization of the operating rooms schedule, which can also be segmented by surgical priority by specialty or by surgeon. Moreover it allows to exchange planned surgeries and to respond correctly to unexpected occurrences (in terms of surgery planning), automatically validating the new plan according to the relevant constraints on hospital resources. Visual information and quantitative reports are easily available to the surgical planner as well as to clinicians and administrators. This tool not only facilitates the planning process but also improves the hospital internal control regarding the surgical suite. It is a user-friendly software for hospitals not requiring costs with additional software licenses and minimizing the training need

A Robust Optimization Approach for Advance Scheduling in Health Care Systems with Demand Uncertainty: Policy Insights

Patient wait times have increased significantly over the past few decades. According to the Canadian Institute for Health Information (CIHI), 40% of Canadians have experienced difficulties in receiving diagnostics tests. MRI wait times have increased by 26% from 2012 to 2016. The lengthy wait times for the health care systems are translated to economic losses and risks to the lives of Canadians. These inefficiencies in health care systems are an indication that health care infrastructure investment has not been able to keep pace with the increased demands. While building new health care infrastructure to create capacity may be the first solution that comes to mind, it is often not feasible due to budget limitations. Optimizing the use of the existing capacity is a more feasible and cost-effective solution to healthcare system inefficiencies. This research builds on previous literature and proposes a robust optimization method for a multi-priority multi-period advance scheduling problem with wait time target which is solved using a proposed adversarial-based algorithm. A sensitivity analysis is conducted to calibrate the model parameters. Several numerical examples are used to extract practical policy insights. The advantages of the robust model in comparison with the deterministic model are highlighted. It is shown that the robust modelling leads to policies that are easier to execute and are more suitable for policy planning purposes when compared to deterministic modelling

Gestão de filas de espera para cirurgia

Mestrado em Gestão e Estratégia IndustrialNos últimos anos o sistema de saúde tem atravessado significativas alterações, nomeadamente, o envelhecimento da população, o aumento da esperança média de vida, o surgimento de novas técnicas de cuidados de saúde e ainda as fortes restrições orçamentais neste setor. A grande procura pelos serviços de saúde e a estagnação destes têm conduzido a listas de espera. A existência de listas de espera é um dos aspetos mais controversos no funcionamento de um sistema de saúde e de elevada sensibilidade política. O fenómeno tem-se, aliás, agravado nos últimos anos. Este estudo teve como principal objetivo entender, através de um questionário, quais as principais falhas e défices no BO (Bloco Operatório), que provocam o constrangimento das listas de espera para cirurgia, tendo em conta a opinião dos profissionais de saúde que nele exercem funções, e através desta análise propor recomendações de melhoria. Os resultados obtidos permitem concluir que o hospital em estudo tem alguns pontos bem estruturados, designadamente, o bom funcionamento dos Sistemas de Informação (SI) e da estrutura do BO. Outros aspetos apresentam debilidades, nomeadamente, verificam-se como grandes problemas a falta de recursos humanos, os défices nos recursos físicos e ainda constrangimentos referentes aos tempos de espera.In recent years the health system has undergone significant changes, including the aging population, increased life expectancy, the emergence of new techniques of health care and still strong budgetary constraints in this sector. The high demand for health services and stagnation of these have led to waiting lists. The existence of waiting lists is one of the most controversial aspects of the functioning of a health system and high political sensitivity. The phenomenon has, in fact, been aggravated in recent years. The main objective of this study was to understand, by means of a questionnaire, which are the main failures and deficits in the OR (Operating Room), which that cause the waiting lists for surgery to be constrained, taking into account the opinion of the health professionals who exercise and through this analysis, how it should be possible to improve this problem. The results obtained allow us to conclude that the hospital under study has some well structured points, namely, the good functioning of the information systems (IS) and the OR structure. Other aspects are related to physical and human resources problems and constraints related to waiting times.info:eu-repo/semantics/publishedVersio

Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment

Arrangement of surgical activities can be classified as a three-level process that directly impacts the overall performance of a healthcare system. The goal of this dissertation is to study hierarchical planning and scheduling problems of operating room (OR) departments that arise in a publicly funded hospital. Uncertainty in surgery durations and patient arrivals, the existence of multiple resources and competing performance measures are among the important aspect of OR problems in practice. While planning can be viewed as the compromise of supply and demand within the strategic and tactical stages, scheduling is referred to the development of a detailed timetable that determines operational daily assignment of individual cases. Therefore, it is worthwhile to put effort in optimization of OR planning and surgical scheduling. We have considered several extensions of previous models and described several real-world applications. Firstly, we have developed a novel transformation framework for the robust optimization (RO) method to be used as a generalized approach to overcome the drawback of conventional RO approach owing to its difficulty in obtaining information regarding numerous control variable terms as well as added extra variables and constraints into the model in transforming deterministic models into the robust form. We have determined an optimal case mix planning for a given set of specialties for a single operating room department using the proposed standard RO framework. In this case-mix planning problem, demands for elective and emergency surgery are considered to be random variables realized over a set of probabilistic scenarios. A deterministic and a two-stage stochastic recourse programming model is also developed for the uncertain surgery case mix planning to demonstrate the applicability of the proposed RO models. The objective is to minimize the expected total loss incurred due to postponed and unmet demand as well as the underutilization costs. We have shown that the optimum solution can be found in polynomial time. Secondly, the tactical and operational level decision of OR block scheduling and advance scheduling problems are considered simultaneously to overcome the drawback of current literature in addressing these problems in isolation. We have focused on a hybrid master surgery scheduling (MSS) and surgical case assignment (SCA) problem under the assumption that both surgery durations and emergency arrivals follow probability distributions defined over a discrete set of scenarios. We have developed an integrated robust MSS and SCA model using the proposed standard transformation framework and determined the allocation of surgical specialties to the ORs as well as the assignment of surgeries within each specialty to the corresponding ORs in a coordinated way to minimize the costs associated with patients waiting time and hospital resource utilization. To demonstrate the usefulness and applicability of the two proposed models, a simulation study is carried utilizing data provided by Windsor Regional Hospital (WRH). The simulation results demonstrate that the two proposed models can mitigate the existing variability in parameter uncertainty. This provides a more reliable decision tool for the OR managers while limiting the negative impact of waiting time to the patients as well as welfare loss to the hospital

The implementor/adversary algorithm for the cyclic and robust scheduling problem in health-care

A general problem in health-care consists in allocating some scarce medical resource, such as operating rooms or medical staff, to medical specialties in order to keep the queue of patients as short as possible. A major difficulty stems from the fact that such an allocation must be established several months in advance, and the exact number of patients for each specialty is an uncertain parameter. Another problem arises for cyclic schedules, where the allocation is defined over a short period, e.g. a week, and then repeated during the time horizon. However, the demand typically varies from week to week: even if we know in advance the exact demand for each week, the weekly schedule cannot be adapted accordingly. We model both the uncertain and the cyclic allocation problem as adjustable robust scheduling problems. We develop a row and column generation algorithm to solve this problem and show that it corresponds to the implementor/adversary algorithm for robust optimization recently introduced by Bienstock for portfolio selection. We apply our general model to compute master surgery schedules for a real-life instance from a large hospital in Oslo. © 2012 Elsevier B.V. All rights reserved