Hospital management games: a taxonomy and extensive review

Hospital management games have gained importance in better planning for scarce resources in times of growing health care demand and increasing technology costs. We classify and investigate the main characteristics of these games from an Operations Research (OR) perspective. Hospital management games model the complex decision making process of internal resource, process, and financial management all influenced by the external hospital environment (e.g., purchasing markets, job markets, legal/political conditions, competition) and simulate situations of the real world. We also highlight the potential of these games for teaching OR in the classroom. Experiencing the advantages of OR may reduce the reservations policy makers have and could make them increasingly open to promoting OR applications in practice. We also disclose potential for new applications.     

Evaluating focused factory benefits with queuing theory

In this paper, we study the benefits of a focused factory using lead-time as a performance measure. Specifically, we model a production process, using multi-class (multiple product types), general interarrival and processing time distributions with multiple machines (GI/G/c) queuing models for deriving each product’s mean lead-time. We also perform simulations for estimating the standard deviation of lead times. There are two product types: a standard and a customized product. The customized product has a more variable demand pattern than the standard product, and also requires additional processing time (setup and run time) in its production process. We assume that management is willing to sacrifice the lead-time performance of the customized product in favor of improved performance for the standard product. The paper shows that focusing the factory is more attractive for plants operating at higher utilization, and manufacturing products that have higher processing time and demand variability differentials between product types.     

An analysis of generalised heuristics for vehicle routing and personnel rostering problems

The present study investigates the performance of heuristics while solving problems with routing and rostering characteristics. The target problems include scheduling and routing home care, security and maintenance personnel. In analysing the behaviour of the heuristics and determining the requirements for solving the aforementioned problems, the winning hyper-heuristic from the first International Cross-domain Heuristic Search Challenge (CHeSC 2011) is employed. The completely new application of a hyper-heuristic as an analysis tool offers promising perspectives for supporting dedicated heuristic development. The experimental results reveal that different low-level heuristics perform better on different problems and that their performance varies during a search process. The following characteristics affect the performance of the heuristics: the planning horizon, the number of activities and lastly the number of resources. The body of this paper details both these characteristics and also discusses the required features for embedding in an algorithm to solve problems particularly with a vehicle routing component.     

Performance evaluation of a distributed application

Analysing the performance of an application performed on a distributed system is discussed in this paper. An analogy between a distributed system and a production process is portrayed, particularly for an application running on several computers. Consequently, theories of management of production processes are employed to help analyse and manage distributed systems, specifically, the Theory of Constraints (TOC). Using TOC combined with the cost/utilization model, which was initially developed to evaluate the utilization of a single processor and is extended here to handle a distributed system, it is demonstrated how the performance of a distributed system can be examined. The methodology presented here is based on a simple graphic display aimed to allow managers of information systems to locate constrained resources, to optimize the distribution of the computer application, and to examine and pinpoint improper imbalances and fluctuations in the system workload. The model develops into a management decision support tool that may be applied in areas such as buffer policy, assessment of protective capacity, investment in computer resources, and identification of areas for improvement.     

The analytic hierarchy process in medical and health care decision making: A literature review

This paper presents a literature review of the application of the analytic hierarchy process (AHP) to important problems in medical and health care decision making. The literature is classified by year of publication, health care category, journal, method of analyzing alternatives, participants, and application type. Very few articles were published prior to 1988 and the level of activity has increased to about three articles per year since 1997. The 50 articles reviewed were classified in seven categories: diagnosis, patient participation, therapy/treatment, organ transplantation, project and technology evaluation and selection, human resource planning, and health care evaluation and policy. The largest number of articles was found in the project and technology evaluation and selection category (14) with substantial activity in patient participation (9), therapy/treatment (8), and health care evaluation and policy (8). The AHP appears to be a promising support tool for shared decision making between patient and doctor, evaluation and selection of therapies and treatments, and the evaluation of health care technologies and policies. We expect that AHP research will continue to be an important component of health care and medical research.     

Simulation based analysis of patient arrival to health care systems and evaluation of an operations improvement scheme

Various demands of different patients over both medical resource and time domains in health care systems raise requests of strategies for balanced system capacity from an operations perspective. In this paper, a quantitative modeling technique with both patient arrival and associated treatment process integrated are used to characterize health care system performance and evaluate system efficiency. The patient arrival process is described as a dynamic random Poisson process and patient treatments are characterized as consumption processes of various health care resources over time with a view of the “product line” used. The waiting time of patients and usage of health care resources are proposed as system performance measures based on their means, variances, and confidence intervals. A simulation considering patients with several various diseases is given to find a mechanism of conflicting factors in decisions of balanced system capacity, and an operation scheme of “evenly balanced load for bottlenecks” is obtained based on analysis of simulation outputs. Simul8 provides the software environment for the simulation.     

Optimal patient and personnel scheduling policies for care-at-home service facilities

In this paper we study the problem of personnel planning in care-at-home facilities. We model the system as a Markov decision process, which leads to a high-dimensional control problem. We study monotonicity properties of the system and derive structural results for the optimal policy. Based on these insights, we propose a trunk reservation heuristic to control the system. We provide numerical evidence that the heuristic yields close to optimal performance, and scales well for large problem instances.     

基于FMEA的企业研发活动风险评估研究

企业研发是一项复杂的系统化活动,实施过程中往往面临着多种风险因素.在对企业研发活动进行管理的过程中,不仅要识别、分析这些因素,还要对研发风险水平进行评估,从而把有限的资源投入到关键风险因素的管理中去,提高研发活动效率.应用了FMEA对研发风险进行评估,设计出FMEA在研发风险管理中应用的具体流程.通过对企业研发活动进行分析,找出研发活动潜在失效模式及后果.然后在定义潜在失效模式严重度(S)、发生度(O)和检测度(D)等级的基础上,对各失效模式的风险优先度(RPN)进行计算,进而通过柏拉图分析确定重要的失效模式,并采取相应的防范措施,降低研发风险.     

Simulation-based framework to improve patient experience in an emergency department

The global economic crisis has a significant impact on healthcare resource provision worldwide. The management of limited healthcare resources is further challenged by the high level of uncertainty in demand, which can lead to unbalanced utilization of the available resources and a potential deterioration of patient satisfaction in terms of longer waiting times and perceived reduced quality of services. Therefore, healthcare managers require timely and accurate tools to optimize resource utility in a complex and ever-changing patient care process. An interactive simulation-based decision support framework is presented in this paper for healthcare process improvement. Complexity and different levels of variability within the process are incorporated into the process modeling phase, followed by developing a simulation model to examine the impact of potential alternatives. As a performance management tool, balanced scorecard (BSC) is incorporated within the framework to support continual and sustainable improvement by using strategic-linked performance measures and actions. These actions are evaluated by the simulation model developed, whilst the trade-off between objectives, though somewhat conflicting, is analysed by a preference model. The preference model is designed in an interactive and iterative process considering decision makers preferences regarding the selected key performance indicators (KPIs). A detailed implementation of the framework is demonstrated on an emergency department (ED) of an adult teaching hospital in north Dublin, Ireland. The results show that the unblocking of ED outflows by in-patient bed management is more effective than increasing only the ED physical capacity or the ED workforce.     

Timing order fulfillment of capital goods under a constrained capacity

This paper studies the order-fulfillment process of a supplier producing multiple customized capital goods. The times when orders are confirmed by customers are random. The supplier can only work on one product at any time due to capacity constraints. The supplier must determine the optimal time to start the process for each order so that the total expected cost of having the goods ready before or after their orders are confirmed is minimized. We formulate this problem as a discrete time Markov decision process. The optimal policy is complex in general. It has a threshold-type structure and can be fully characterized only for some special cases. Based on our formulation, we compute the optimal policy and quantify the value of jointly managing the order fulfillment processes of multiple orders and the value of taking into account demand arrival time uncertainty.     

Sensitivity Analysis of Promotion Opportunities in Graded Organizations

This paper extends earlier work on manpower mobility in hierarchical organizations and is concerned especially with the effects of changes in hiring and separation on opportunities for internal advancement. We make use of a fractional flow model of personnel to highlight the links between personnel flows and vacancy flows, and then derive formulae that can be used to simulate the impact of changes in grade-size targets, hiring policy and attrition rates on promotion opportunities for staff. The model is then illustrated by application to data on faculty staffing in a large university.     

DEA model with shared resources and efficiency decomposition

Data envelopment analysis (DEA) has proved to be an excellent approach for measuring performance of decision making units (DMUs) that use multiple inputs to generate multiple outputs. In many real world scenarios, DMUs have a two-stage network process with shared input resources used in both stages of operations. For example, in hospital operations, some of the input resources such as equipment, personnel, and information technology are used in the first stage to generate medical record to track treatments, tests, drug dosages, and costs. The same set of resources used by first stage activities are used to generate the second-stage patient services. Patient services also use the services generated by the first stage operations of housekeeping, medical records, and laundry. These DMUs have not only inputs and outputs, but also intermediate measures that exist in-between the two-stage operations. The distinguishing characteristic is that some of the inputs to the first stage are shared by both the first and second stage, but some of the shared inputs cannot be conveniently split up and allocated to the operations of the two stages. Recognizing this distinction is critical for these types of DEA applications because measuring the efficiency of the production for first-stage outputs can be misleading and can understate the efficiency if DEA fails to consider that some of the inputs generate other second-stage outputs. The current paper develops a set of DEA models for measuring the performance of two-stage network processes with non splittable shared inputs. An additive efficiency decomposition for the two-stage network process is presented. The models are developed under the assumption of variable returns to scale (VRS), but can be readily applied under the assumption of constant returns to scale (CRS). An application is provided.     

A formal modelling of control processes

This study concerns the performance management of manufacturing processes. Such processes are decomposed into two types: the operating processes and the control ones. While an operating process has to realise the deliverable products, a control one is designed to plan, control and supervise the execution of the activity of the operating processes. In this sense, one approach of control is discussed. The proposed model is based on the exchange relation concept between a customer and a supplier. The different control parameters are defined from this point of view, such as the activities assigned objectives and the performance indicators associated with them, the control activities and their functions, the control means... this for both the technical and economical levels of control. These ideas are applied to some problems encountered in manufacturing processes. In particular, aluminium metallurgy processes are considered. The performance of these processes are driven by many parameters such as the quality of the raw materials, the conformity of the tools used, the elements to assemble, the know-how of the operators.     

Modelling toolkit to assist with introducing a stepped care system design in mental health care

We describe a modelling toolkit that was developed with the aim of assisting those responsible for introducing stepped care systems to local mental health services in the UK. The toolkit was pre-populated with real patient flow data collected from four sites that piloted the stepped care system design. Two analytical models were developed and coded as part of the toolkit to provide insights concerning workload, patient throughput, and changes in waiting times and waiting list size. An interface was built to allow users to specify their own stepped care system and input their own estimates or data of service demands and capacities at different steps. Despite the challenges and limitations, the use of modelling to inform the design of new service configurations is an important step in the right direction and we would recommend this as a reasonable way forward.     

Markov链在人力资源供给预测中的应用

本文利用Ｍａｒｋｏｖ链建立模型,对组织各类人员的供给作出定量预测,为组织的人事部门或人力资源管理部门根据职位人员需求安排合适的人选提供决策的依据。文中介绍的模型不仅可以预测组织中各类人员的供给人数,而且可以预测组织中各类人员的分布。对于人力资源管理部门如何用人和用好人有一定的指导意义和应用价值     

Integrated Fuzzy AHP–TOPSIS for selecting the best plastic recycling method: A case study

Due to the rapid depletion of natural resources and undesired environmental changes in a global scale, it is necessary to conserve the natural resources and protect the environment. Industries which manufacture plastic based products have the necessity to recycle plastics. There are number of methods to recycle plastics. Since the selection of the best recycling method involves complex decision variables, it is considered to be a multiple criteria decision-making (MCDM) problem. This article develops an evaluation model based on the fuzzy Analytic Hierarchy Process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS) to enable the industry practitioners to perform performance evaluation in a fuzzy environment. The purpose of the study is to determine the best method for recycling plastics among the various plastic recycling processes. By observing the results, it is identified that mechanical recycling process is found to be the best plastic recycling process using the integrated approach.     

高校教师绩效工资管理系统的设计与实现

高校教师绩效工资管理系统的设计得益于管理科学与信息技术的有机结合,并基于高校教师的职业与人事管理特征有效实现管理自动化、信息透明化、公平效率化的设计初衷。系统通过几个主要功能模块的分工与流程,结合系统的参数设置与运算,可以自动生成教师的绩效津贴。从而实现高校有限资源的优化配置与绩效工资的合理分配,在激励教职员工爱岗敬业、自我实现的同时,实现教师个人与高校优势互补、和谐共进的多赢局面。