https://repositorio.inesctec.pt/bitstream/123456789/3167/1/PS-06772.pdf

Operations Research in Healthcare: a survey

/pdf/proceedings-of-the-1997-winter-simulation-conference-4cfat1wn9s.pdf

Proceedings of the 1997 winter simulation conference

This paper provides an overview of, and guidance as to when, why and how to choose and use, different simulation modelling methods as applied to healthcare. What simulation is and why it is necessary in addressing healthcare problems are discussed. In addition, key criteria for choosing an appropriate method (project type, population resolution, interactivity, treatment of time and space, resource constraints, autonomy and how knowledge is embedded) are covered. Key concepts for each method, moving from the simplest to most complex methods, are reviewed in some detail.

/pdf/modelling-methods-for-pharmacoeconomics-and-health-34bvqeml00.pdf

Modelling methods for pharmacoeconomics and health technology assessment: an overview and guide.

This article aims to present examples of computer simulation models that support decision-making processes in the health care sector. The objective of this review is to propose a system of classification of health care topic areas examined with the assistance of simulation methods. The categories described in literature were expanded and a detailed taxonomy for sub-groups was formulated. Usefulness of simulation modeling techniques was investigated and an attempt was made to correlate the simulation approach with a corresponding health care application group from the suggested classification.

Application of computer simulation modeling in the health care sector: a survey

We present a model for representing stationary multivariate time-series input processes with marginal distributions from the Johnson translation system and an autocorrelation structure specified through some finite lag. We then describe how to generate data accurately to drive computer simulations. The central idea is to transform a Gaussian vector autoregressive process into the desired multivariate time-series input process that we presume as having a VARTA (Vector-Autoregressive-To-Anything) distribution. We manipulate the autocorrelation structure of the Gaussian vector autoregressive process so that we achieve the desired autocorrelation structure for the simulation input process. We call this the correlation-matching problem and solve it by an algorithm that incorporates a numerical-search procedure and a numerical-integration technique. An illustrative example is included.

Modeling and generating multivariate time-series input processes using a vector autoregressive technique

The paper on the UNOS Liver Allocation Model (ULAM) describes the building of a simulation model that supports policy evaluation for a national medical problem. The modeling and simulation techniques used in building ULAM include: fitting donor and patient arrival processes having trend and cyclic rate components using non-homogeneous Poisson processes (NHPPs) having exponential rate functions which may include both a polynomial and some trigonometric components, fitting distributions to data on transition times between states of medical urgency; application of variance reduction techniques using common random-number streams and prior information; organizing data structures for efficient file searching and ranking capabilities; the use of bootstrapping techniques for attribute sampling; the building of submodels employing biostatistical procedures such as Kaplan-Meier and logistic regression; and the characterization of performance measures within a complex political, economic and social environment. ULAM provides a means for producing quantitative information to support the selection of a liver allocation policy.

/pdf/organ-transplantation-policy-evaluation-4c7b9749qx.pdf

Organ transplantation policy evaluation

The UNOS Kidney Allocation Model (UKAM) is a software tool for the simulation and analysis of national cadaveric kidney and kidney-pancreas allocation policies for transplantation. UKAM is modular and is designed to enable easy updating of the various components as new data become available. UKAM's flexibility gives the user the ability to create and evaluate an almost infinite number of detailed allocation policies. This will enable the United Network for Organ Sharing (UNOS) to make decisions based on quantitative data when considering changes in organ allocation policies.

/pdf/developing-a-national-allocation-model-for-cadaveric-kidneys-3pbjcotsus.pdf

Developing a national allocation model for cadaveric kidneys

The UNOS Liver Allocation Model (ULAM) is a simulation of the cadaveric liver allocation system in the United States. ULAM was created by the United Network for Organ Sharing (UNOS) in collaboration with Pritsker Corporation/Symix Systems, to permit comparison of multiple liver allocation policy proposals so that policies can be tested prior to implementation. ULAM is extremely adaptable, and with it UNOS has been able to respond to varied and complex requests for policy analysis. ULAM has aided UNOS throughout the highly publicized national liver allocation debate, and its use is anticipated for the foreseeable future. The authors believe that ULAM is an excellent example of simulation technology used to resolve national medical policy issues. The success of ULAM, in terms of its ease of use, flexibility of design, and acceptance by the transplant community, has reinforced UNOS' desire to create other organ allocation models. This paper provides a brief description of ULAM's structure, and summarizes the evolution of ULAM from 1995 to 2000.

O.P. Daily

Papers

Organ transplantation policy evaluation

Developing a national allocation model for cadaveric kidneys

An update on a successful simulation project: the UNOS Liver Allocation Model

The impact of improvements in procurement and utilization on US liver recipients