Managerial Analysis and Decision-Making in Outpatient Health Clinics

This paper discusses a generalized model of an outpatient clinic which duplicates many real-life complexities, e.g. different facilities, the patient routes through the clinic, number of observers in each facility, etc. The validation tests proved that the output generates distributions which are not statistically different from the observed distributions for The Pennsylvania State Outpatient Clinic. The model is relatively fast and efficient, and one typical day can be simulated in less than one second of the computer processing time on IBM System 370/168. With slight modifications, it is capable of being transferred to many different types of health care delivery systems, e.g. hospitals, health maintenance organizations and to prehospital emergency care systems.The paper describes some basic measures of effectiveness for outpatient clinics, and using these measures evaluates various operating procedures and policies.     

Primary care network development: the regulator’s perspective

Our research is motivated by the proliferation of primary care models in Ontario, Canada. Currently, primary care is mainly provided by facilities belonging to six models of care. These models are remunerated by various schemes—a mixture of fee-for-service, capitation and salary. In addition, they provide different levels of care and several are better adjusted than others to treat complex health needs. The proposed mixed integer programming model allows the regulator to test the outcomes of locating different types of primary care facilities on the overall cost, accessibility and appropriateness of provided care. The network design is fitted to the heterogeneity of the population residing in a defined geographical area, directly using an index (deprivation index) that was found to correlate with increased health needs and barriers to care. The model capabilities are illustrated on the geographical area of Kingston, Ontario.     

Practical aspects associated with location planning for maternal and perinatal assistance in Brazil

A study has been carried out aimed at reducing perinatal mortality in the municipality of Rio de Janeiro through a better distribution of health care facilities. The algorithmic aspects are detailed elsewhere and here the emphasis is on practical issues and difficulties encountered. A 3-level hierarchical model was developed. Both uncapacitated and capacitated versions are briefly described together with some results based on actual data. The project brought to light many contradictions between OR theory and practice in developing countries and, unfortunately, the models developed were not implemented by the municipality health authorities. Possible reasons for this outcome are analysed.     

Matching patient and physician preferences in designing a primary care facility network

This paper introduces an integer programming model for planning primary care facility networks, which accounts for the interests of different stakeholders while maximizing access to health care. Physician allocation to health-care facilities is explicitly modelled, which allows consideration of physician incentives in the planning phase. An illustrative case study in the Turkish primary care system is presented to show the implications of focusing on patient or physician preferences in the planning phase. A discussion of trade-offs between the different stakeholder preferences and some recommendations for modelling choices to match these preferences are provided. In the context of this case, we found that using an access measure that decays with distance, and incorporating nearest allocation constraints improves performance for all stakeholders. We also show that increasing the number of physicians may have adverse affects on access measures when physician preferences are addressed.     

A hierarchical model for the location of perinatal facilities in the municipality of Rio de Janeiro

We present a 3-level hierarchical model for the location of maternal and perinatal health care facilities in Rio de Janeiro. Relaxations and heuristics are developed for this model and computational results are given for problems available in the literature, for networks ranging from 10 to 400 vertices. The quality of the solutions produced by the procedures we developed do not differ significantly among themselves. The model is also applied to a case study corresponding to real 1995 data of the municipality of Rio de Janeiro.     

Deployment of rural health facilities in a developing country

This study describes the problem of finding suitable sites for additional health facilities in a rural area in Bangladesh. The objective is to improve the accessibility of people to the health care system given the existing set of facilities. As is frequently the case in developing countries, activities designed to develop and improve differing sectors of the infrastructure are poorly integrated and ill-coordinated. As a result, decision-makers may make independent and individual decisions about locating new service facilities. Often, as has been the case in Bangladesh, these decisions are taken at a relatively low level, by officers of local government or by elected leaders in a region, or by a combination of these. In the absence of any formal analysis and generation of alternatives, the final decision may be made on political or pragmatic considerations. As a result the decisions are often far from optimal. Ultimately, better health care will enhance many sectors of a regional economy, and so the decision about where to invest in new or better resources is important for reasons over and above that of providing health care for the population. In this paper, the role of location-allocation modelling in developing countries is considered, and the specific Bangladeshi problem is considered as a maximal covering location problem which is solved by an efficient heuristic method.     

Application of discrete-event simulation in health care clinics: A survey

In recent decades, health care costs have dramatically increased, while health care organisations have been under severe pressure to provide improved quality health care for their patients. Several health care administrators have used discrete-event simulation as an effective tool for allocating scarce resources to improve patient flow, while minimising health care delivery costs and increasing patient satisfaction. The rapid growth in simulation software technology has created numerous new application opportunities, including more sophisticated implementations, as well as combining optimisation and simulation for complex integrated facilities. This paper surveys the application of discrete-event simulation modeling to health care clinics and systems of clinics (for example, hospitals, outpatient clinics, emergency departments, and pharmacies). Future directions of research and applications are also discussed.     

Location of Preventive Health Care Facilities

This paper is focused on the problem of locating preventive health care facilities. The aim is to maximize participation to prevention programs. We assume that distance is a major determinant of participation and people would go to the closest facility for preventive health care. Each facility is required to have more than a predetermined number of clients because of the direct relationship between volume and quality of preventive services. We provide a mathematical formulation and present alternative solution approaches for this new location problem. We report on computational performance of the proposed methods in locating public health centers in Fulton County, Georgia and mammography screening centers in Montreal, Quebec.     

Location and sizing of facilities on a line

The location-allocation problem in its basic form assumes that the number of new facilities to be located is known and the capacities are unlimited. When the locations of the facilities and demand points (or customers) are restricted to the real line, the basic model may be solved efficiently by dynamic programming. In this note, we show that when the number of facilities and their capacities are included in the decision process, the problem may actually be easier to solve.     

Fairness versus efficiency in charging for the use of common facilities

The problem of efficiency vs fairness is considered in relation to the splitting of costs for shared facilities between users. This is considered as a result of a problem of sharing the cost of the provision of central computing facilities between different faculties in a large university, but the basic problem is widespread. A linear programming model is considered in order to minimise cost. The dual of this model is shown to correspond to an efficient allocation of costs. An alternative optimal dual solution is shown to give a ‘fair’ solution according to criteria resulting from cooperative game theory.     

Sensitivity analysis of a continuous multifacility competitive location and design problem

A continuous location problem in which a firm wants to set up two or more new facilities in a competitive environment is considered. Other facilities offering the same product or service already exist in the area. Both the locations and the qualities of the new facilities are to be found so as to maximize the profit obtained by the firm. This is a global optimization problem, with many parameters to be estimated, and whose behavior is not really well understood. Using random problems and a robust evolutionary algorithm recently proposed for solving this problem, the behavior of optimal solutions in various environments and changes in the basic model parameters are researched. These comprise the quality of existing and new facilities, cost function and presence of the chain. Some economic implications are derived.     

Location–Allocation of Multiple-Server Service Centers with Constrained Queues or Waiting Times

Recently, the authors have formulated new models for the location of congested facilities, so to maximize population covered by service with short queues or waiting time. In this paper, we present an extension of these models, which seeks to cover all population and includes server allocation to the facilities. This new model is intended for the design of service networks, including health and EMS services, banking or distributed ticket-selling services. As opposed to the previous Maximal Covering model, the model presented here is a Set Covering formulation, which locates the least number of facilities and allocates the minimum number of servers (clerks, tellers, machines) to them, so to minimize queuing effects. For a better understanding, a first model is presented, in which the number of servers allocated to each facility is fixed. We then formulate a Location Set Covering model with a variable (optimal) number of servers per service center (or facility). A new heuristic, with good performance on a 55-node network, is developed and tested.     

Utilizing buffer management to improve performance in a healthcare environment

For over 50 years, the United Kingdom’s National Health Service has aspired to provide universal access to quality health care. However, as evidenced by huge backlogs and lengthy waiting times for many services, the NHS is showing the strain of accommodating rising contemporary expectations within a constrained budget. This paper describes the concept of buffer management, its origins in manufacturing applications, and how it can be applied to generate improvements in health care systems. The successful implementation of buffer management is illustrated with recent applications in the Accident and Emergency departments and the hospital admissions process of three NHS facilities.     

Bicriteria efficiency/equity hierarchical location models for public service application

As is often the case in healthcare provision, public services may offer facilities at a hierarchy of levels in different locations, ranging from basic to specialised levels of care. In addition to efficiency objectives, with public services there is the concern of equity of provision when locating new facilities. We present, as a tool-kit for decision makers, a range of discrete hierarchical location models with bicriteria efficiency/equity objectives. These models are for use in location of facilities within hierarchical systems where a fair but efficient hierarchical service is sought. The hierarchical models have as efficiency criteria both p-median and maximal-covering types. These components are combined in a novel manner with appropriate equity objectives to give decision makers a range of choices of scenarios. We illustrate use of the models in a healthcare setting.     

求解应急医疗设施分层递进式选址问题的改进免疫算法

针对应急医疗设施的特点,提出分层递进式选址方法,对应急医疗设施进行合理选址.首先,通过熵权法对选址所需要考虑的因素进行权重计算,并进行初步选址;其次,考虑设施点的服务容量、重大公共卫生事件下轻重症患者的治疗与转移的实际情况,建立双层级整数规划模型;再次,根据模型的具体特点,设计改进的免疫优化算法对其进行求解;最后,以湖...     

Incorporating health outcomes in Pennsylvania hospital efficiency: an additive super-efficiency DEA approach

The health care sector is one of the fastest growing sectors in the United States. Researchers are interested in conducting studies in the area of health economics in order to propose solutions to curb the rapid increase in health care spending and to improve the efficiency of the health care system in the United States. Specifically, hospital efficiency is one important research area in health economics. In this paper, data envelopment analysis (DEA) is used to assess hospital efficiency. An additive super-efficiency model is presented and applied to a sample of general acute care hospitals in Pennsylvania. In addition to the conventional choice of input and output variables, we include the survival rate as a quality measure of health outcome in the set of output variables. Thus our model takes both the quantity and the quality of the output into account. With the results obtained from our proposed DEA model, inefficiencies can be identified for hospitals to address without sacrificing the quality of care.     

A microsimulation model of the health care system: the role of the hospital sector

A microeconometric model of the health care system of the United States was estimated by applying econometric techniques to extensive data. The model treats the microanalytic behavior of individuals and institutions comprising the health care system, and is structured in terms of five submodels pertaining to consumers, hospital and physician services, physician and nonphysician manpower. In each submodel there is an economic market on which demands and supplies from the individuals and institutions interact and on which the allocation of resources is determined. A detailed treatment of participant attributes facilitates study of the distributional impacts of alternative policies. This paper presents an overview of the complete system, and summarizes the relationships used for the hospital sector.     

Facility location for large-scale emergencies

In the p-center problem, it is assumed that the facility located at a node responds to demands originating from the node. This assumption is suitable for emergency and health care services. However, it is not valid for large-scale emergencies where most of facilities in a whole city may become functionless. Consequently, residents in some areas cannot rely on their nearest facilities. These observations lead to the development of a variation of the p-center problem with an additional assumption that the facility at a node fails to respond to demands from the node. We use dynamic programming approach for the location on a path network and further develop an efficient algorithm for optimal locations on a general network.     

First,do no harm? A framework for evaluating new <Emphasis Type="Italic">versus</Emphasis> reprocessed medical devices

More than ever before, health care providers are under intense pressure to control costs. Medical devices represent a significant ‘hard’ cost, with worldwide spending exceeding USD 235 billion. A growing number of health care providers are engaging in the practice of reprocessing—sterilizing and reusing medical devices labelled only for a single use. The ethical and technical dimensions of this practice have received much attention, but its economic aspects remain largely unexamined. This paper presents a Markov decision process framework that a health care provider can use to decide whether to use new or reprocessed devices in a given context. Two cases are studied: completely observable device condition and partially observable device condition. After briefly discussing structural results for the two cases, several examples are presented to illustrate how the model can be applied in practice. Useful results can be computed quickly with minimal data. A key insight of the model is that perfect information regarding the device condition is often not required to make a sound decision.