An algorithm to locate perinatal facilities in the municipality of Rio de Janeiro

In order to reduce infant mortality in the municipality of Rio de Janeiro it is desired to encourage all mothers-to-be to attend the appropriate health care facilities. A 3-level hierarchical prenatal–neonatal health care system is described together with a basic model for optimising accessibility to facilities. A genetic algorithm to solve the basic model is developed and some numerical experience reported. Extensions to the basic model and planned future research are briefly indicated.     

Load balancing and capacity constraints in a hierarchical location model

Recent work on the location of perinatal facilities in the municipality of Rio de Janeiro resulted in the development of an uncapacitated, three-level hierarchical model. An important issue that arose during the course of the research was the need to include some form of capacity constraints into the model, especially in the higher, resource intensive level of the hierarchy. This need was felt from technical discussions related to the research work and from contacts with municipality health officials.A capacitated model is presented and solved using a Lagrangean heuristic. For smaller problems optimal solutions are found using CPLEX; it is found that the heuristic usually gives high quality solutions. Next a bi-criterion model is formulated in which the additional objective measure is the imbalance in facility loading. This is solved exactly for a small problem and approximately for the 152-vertex Rio de Janeiro data.     

Water supply and consumption uncertainty: a conflict-equilibrium

This paper addresses the economic efficiency of water production and distribution in a vertical supply chain consisting of a water-provider and a consumer (municipality). The inherent conflicts over stocks and supply costs that emerge among the parties in the water supply chain are modeled as a zero-sum stochastic differential game. Consequently, the effects of collaboration and competition are contrasted as well as the application of block pricing and subsidies in overcoming potential conflicts between the water-provider and the municipality subject to political risks of not meeting demands for water. The effect of uncertainty is elaborated as well. In particular, we show that when the supply variance depends on the mean supply, the effect of uncertainty depends on the intensity of the conflict between the municipality and the water-provider.     

A Planning Model for the Development of Waste Material Recycling Programmes

Material recycling is quickly becoming the most visible component of municipal solid waste management systems, and optimization models could play a prominent role in the long-term cost-effective planning of these systems. In this paper, we develop a mixed integer programming model for the recycling of various by-product materials within the overall waste system. This model is solvable on a microcomputer for reasonable problem dimensions, and the planning methodology is applied to a hypothetical municipality to illustrate the potential utility of the developed modelling approach.     

Flexible waste management under uncertainty

In this paper, we use stochastic dynamic programming to model the choice of a municipality which has to design an optimal waste management program under uncertainty about the price of recyclables in the secondary market. The municipality can, by undertaking an irreversible investment, adopt a flexible program which integrates the existing landfill strategy with recycling, keeping the option to switch back to landfilling, if profitable. We determine the optimal share of waste to be recycled and the optimal timing for the investment in such a flexible program. We find that adopting a flexible program rather than a non-flexible one, the municipality: (i) invests in recycling capacity under circumstances where it would not do so otherwise; (ii) invests earlier; and (iii) benefits from a higher expected net present value.     

Residential location and school planning in a tightening urban economy

Facing worse fiscal plight, many municipalities in Sweden must today carefully reexamine their activities. In urban planning, this has resulted in a growing interest in how the urban development could be designed to support and facilitate the efficient use of existing public investments. This paper focuses on the school sector as being one of the most costly. A location-allocation model of the capacitated facility location type is formulated. A set of potential schools consisting of existing and new ones are considered. The school-age children are assigned to a subset of these schools so as to minimize the sum of the capital costs of this subset and the transportation costs of the children. The model is applied to the municipality of Uppsala in Sweden. Different future settlement structures proposed by the planners as well as different housing allocations generated by a separate optimization model are evaluated.     

A matheuristic algorithm for stochastic home health care planning

Efficient human resource planning is the cornerstone of designing an effective home health care system. Human resource planning in home health care system consists of decisions on districting/zoning, staff dimensioning, resource assignment, scheduling, and routing. In this study, a two-stage stochastic mixed integer model is proposed that considers these decisions simultaneously. In the planning phase of a home health care system, the main uncertain parameters are travel and service times. Hence, the proposed model takes into account the uncertainty in travel and service times. Districting and staff dimensioning are defined as the first stage decisions, and assignment, scheduling, and routing are considered as the second stage decisions. A novel algorithm is developed for solving the proposed model. The algorithm consists of four phases and relies on a matheuristic-based method that calls on various mixed integer models. In addition, an algorithm based on the progressive hedging and Frank and Wolf algorithms is developed to reduce the computational time of the second phase of the proposed matheuristic algorithm. The efficiency and accuracy of the proposed algorithm are tested through several numerical experiments. The results prove the ability of the algorithm to solve large instances.     

Implementation of Health Facilities in a New City

A new city is under construction in a developing country. The town will be organized in modules, and the population projection is established till the 90s. The ratio of medical personnel to inhabitants is fixed according to health policy criteria. The primary care system should be composed of a set of health centres which are identical with regard to equipment and personnel. The problem is to determine the number--and thus the size--of the health centres, and their location. The solution depends on two opposing factors: the total construction cost, which is increasing with the number of centres, and the walking distance for the patient, which is decreasing with the number of centres. For a given critical distance, we find--using techniques of location theory in network--the smallest number of centres that will ensure that all inhabitants are located within the critical distance. A Fortran program in which the sensitivity of the solution is studied as a function of the given critical distance is developed.     

重庆市不同收入等级的城镇居民消费特征分析

重庆直辖以来,社会经济得到快速发展,城镇居民收入持续稳定增长,其消费水平、消费结构和消费观念发生了较大的变化,为了进一步改善消费结构,提高城镇居民的消费水平和生活质量,有针对性的对建设城乡统筹发展的直辖市提供科学的依据,根据2009年重庆市不同收入等级的城镇居民人均消费结构的数据,运用对应分析方法,分析不同收入等级的城镇居民的消费特征、消费支出结构的特点,并针对不同收入等级的城镇居民提出了分层引导促进消费的建议.     

A heuristic for direct consumer participation in primary health care planning

Recent attempts at consumer participation in the health care planning process have proved weak in their ability to responsively account for consumer health welfare. This can be attributed, in large part, to the mechanisms employed for identifying and utilizing the consumer's health care views and preferences. A heuristic planning procedure designed to overcome these problems by directly incorporating consumer preferences is developed. It identifies that (primary) health care delivery system which maximizes total incremental health benefit to a community subject to a prespecified budget constraint. The model assumes a methodology (previously developed by the author) for measuring, in aggregable units, the benefit, B_ip, from some health care facility p as perceived by some consumer i. Application of the procedure and subsequent sensitivity analyses demonstrate its ability to generate valid solutions that are robust to disturbances in the planning system.     

Deductibles in health insurance

This study is an extension to a simulation study that has been developed to determine ruin probabilities in health insurance. The study concentrates on inpatient and outpatient benefits for customers of varying age bands. Loss distributions are modelled through the Allianz tool pack for different classes of insureds. Premiums at different levels of deductibles are derived in the simulation and ruin probabilities are computed assuming a linear loading on the premium. The increase in the probability of ruin at high levels of the deductible clearly shows the insufficiency of proportional loading in deductible premiums. The PH-transform pricing rule developed by Wang is analyzed as an alternative pricing rule. A simple case, where an insured is assumed to be an exponential utility decision maker while the insurer’s pricing rule is a PH-transform is also treated.     

A Simulation Model for Planning Services for Renal Patients in Europe

A discrete-event simulation model is being developed to provide information for national and regional health planners about the effect of different treatment policies and practices on the increasing numbers of patients with irreversible kidney failure. The simulation program, written in Pascal using Pascal-SIM, describes the activities of individual patients whose progress through treatment depends on their characteristics and treatment history, as well as on treatments availability. Programming techniques have been developed to cope with the multiple scheduling of patient entities and the resultant queue-management problems. In order to provide simulation runs on request, for any population group, appropriate data is selected from the European Dialysis and Transplant Association Registry data base for use in the simulation program. Results are shown on a computer screen while the simulation is running, and are saved for further analysis to provide feedback to the requesting organization.     

Rationalising the use of Twitter by official organisations during risk events: Operationalising the Social Amplification of Risk Framework through causal loop diagrams

Communication of health risk events is a complex and challenging task. The advent of information and communication technology along with the following popularisation and widespread uptake of social media are reshaping the field of risk communication. Guided by key tenets of the Social Amplification of Risk Framework, this study developed a causal loop diagram, capturing the perceptions of professionals in health organisations regarding the role of Twitter during risk events. The aim of this paper is to explore the use of the causal loop diagram and its role with rationalising the use of Twitter in risk communication strategies. A key finding of the model is the central role of trust and its interrelationship with other factors during a risk event. A contribution is made to operational research through the novel use of soft system dynamics in risk communication, to risk communication through the investigation of the new medium Twitter and also to research on the Social Amplification of Risk Framework by providing a means through which to operationalise the framework.     

Efficiency and welfare implications of managed public sector hospital waiting lists

A queuing model for public health service waiting lists is developed, and the implications for patient welfare of different systems for managing the waiting list are analysed. If patients are admitted to hospital on a first-come-first-served basis, a welfare gain is achieved by moving from a system of implicit to one of explicit rationing of access to the waiting list. If individual waiting times and hospital admissions are dependent on clinical priority, a further welfare gain is achievable without the use of explicit rationing, by reallocating the total waiting time from the more towards the less seriously ill. On efficiency and welfare criteria, a maximum waiting time guarantee does not appear to be a desirable development.     

Performance Monitoring and Competence Assessment in Health Services

Health and health service monitoring is among the most promising research area today and the world work towards efficient and cost effective health care. This paper deals with monitoring health service performance using more than one performance outcome variable (multi-attribute processes), which is common in most health services. Although monitoring whether a health service changes or improves over time is important this is well covered in the current literature. Therefore this paper focuses on comparing similar health services in terms of their performance. The proposed procedure is based on an appropriate control chart. The paper deals with firstly the case when no risk adjustment is required because the health services being compared treat the same patient case-mix which does not vary over time. Secondly it deals with comparing health services where risk adjustment is required because the patient case-mix they service do differ because they service either very different geographical locations or service very different demographics of the same population. The technology developed in this paper could be used for example to assess and compare health practitioners’ competence over time, i.e. to decide if two doctors are equivalent in terms of their outcome performances. The waiting time random variable associated with the run length distribution of the control charts (as well as to competence testing) is studied using a Markov Chain embedding technique. Numerical results are provided that exhibit the value of the proposed procedures.     

Combining simulation and goal programming for healthcare planning in a medical assessment unit

This paper describes a detailed simulation model for healthcare planning in a medical assessment unit (MAU) of a general hospital belonging to the national health service (NHS), UK. The MAU is established to improve the quality of care given to acute medical patients on admission, and to provide the organisational means of rapid assessment and investigation in order to avoid unnecessary admissions. The simulation model enables different scenarios to be tested to eliminate bottlenecks in order to achieve optimal clinical workflow. The link between goal programming (GP) and simulation for efficient resource planning is explored. A GP model is developed for trade-off analysis of the results obtained from the simulation. The implications of MAU management preferences to various objectives are presented.     

Development and application of multiscale models of acute viral infections in intervention research

The objective of this study is to advance two frontiers in multiscale modelling of acute viral infections, which are (a) the mathematical technology or technical frontier, where we present a new method for development of multiscale models of acute viral infections using influenza A virus (IAV) as a paradigm in which a new set of metrics to measure both individual level and community level infectiousness are introduced, and (b) the scientific applications frontier, where we demonstrate the implementation of multiscale modelling in evaluating the comparative effectiveness of IAV health interventions from efficacy data. The multiscale model is developed by integrating the within-host scale and the between-host scale. Using the example of IAV as a paradigm, we demonstrate the utility and process by which multiscale modelling can be used to evaluate the comparative effectiveness of health interventions that operate at different scale domains. The multiscale modelling is general enough to be applicable to other acute viral infections.     

Probabilistic models for medical insurance claims

The paper develops two probabilistic models for claim size in health insurance based on the claims of families and individuals covered by the policy. First, general models for the numbers of families and persons covered by a medical insurance are developed. These are then used to construct models for claim size. Applications of these general models are then analysed and discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

Choice of modelling technique for evaluating health care interventions

Economic evaluation, such as cost effectiveness analysis, provides a method for comparing healthcare interventions. These evaluations often use modelling techniques such as decision trees, Markov processes and discrete event simulations (DES). With the aid of examples from coronary heart disease, the use of these techniques in different health care situations is discussed. Guidelines for the choice of modelling technique are developed according to the characteristics of the health care intervention.The choice of modelling technique is shown to depend on the acceptance of the modelling technique, model ‘error’, model appropriateness, dimensionality and ease and speed of model development. Generally decision trees are suitable for acute interventions but they cannot model recursion and Markov models are suitable for simple chronic interventions. It is further recommended that population based models be used in order to provide health care outcomes for the likely cost, health benefits and cost effectiveness of the intervention. The population approach will complicate the construction of the model. DES will allow the modeller to construct more complex, dynamic and accurate systems but these may involve a corresponding increase in development time and expense. The modeller will need to make a judgement on the necessary complexity of the model in terms of interaction of individuals and model size and whether queuing for resources, resource constraints or the interactions between individuals are significant issues in the health care system.     

A first course in biostatistics for health sciences students

The content of a course on introductory biostatistics for health science students is described. The course, first taught in 1998, embodies, among other topics, most of the desirable features discussed by Sahai and Ojeda. The syllabus and associated project work are presented with emphasis placed on ways in which study design and critical evaluation of research are developed in parallel with the statistical methodology. The advantages and disadvantages of such a course are discussed. This includes an analysis of the performance of students with diff erent statistical and mathematical backgrounds.