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Resource allocation decision making in the military health system

IIE Transactions on Healthcare systems engineering 2014年第2期4卷 80-87页

作者： Bastian, Nathaniel D. Fulton, Lawrence V. Shah, Vivek P. Ekin, Tahir The Pennsylvania State University Center for Integrated Healthcare Delivery Systems Department of Industrial and Manufacturing Engineering University Park PA 16802 355 Leonhard Building United States U.S. Army - Baylor University Graduate Program in Health and Business Administration U.S. Army Medical Department Center and School Fort Sam Houston TX 78234-6100 3630 Stanley Road United States Texas State University McCoy College of Business Administration Department of Computer Information Systems and Quantitative Methods San Marcos TX 78666 611 University Drive United States

The necessity to efficiently balance and re-allocate system resources among hospitals in a hospital network is paramount, especially as health systems experience increasing demand and costs for health services. In this paper, we proffer a resource allocation-based optimization model that adjusts resources (system inputs) automatically, which provides decision makers (such as health care managers and policy-makers) with a decision-support tool for re-allocating resources in large health systems that are centrally controlled and funded, such as the Military Health System. In these systems, inputs are fixed at certain levels and may only be adjusted within medical treatment facilities, while outputs must be maintained. We provide a mathematical formulation and example solutions from a case study using real-world data from sixteen U.S. Army hospitals. We also find utility in the use of multi-start evolutionary algorithms to store multiple optimal solutions for consideration by decision makers. © 2014 "IIE".

关键词： decision analysis healthcare management military medicine multi-criteria optimization Resource allocation

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Designing American Government

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Design Management Review 2016年第1期27卷

作者： John Paul Farmer Ryan Panchadsaram Director of technology and civic innovation at Microsoft and founder/CEO of The Innovation Project a 501(c)3 dedicated to spreading best practices in institutional innovation. He served as senior advisor for innovation in the White House where he spearheaded government innovation initiatives that infused lean startup and agile methods as well as design thinking into the public sector. In this role Farmer co‐founded and directed the Presidential Innovation Fellows program. Earlier in his career he worked in healthcare and finance creating and building new business units from the ground up. Farmer also played professional baseball as a shortstop in the Los Angeles Dodgers and Atlanta Braves minor league systems. He holds an MBA with honors from the Graduate School of Business at Columbia University and an AB with honors from Harvard University. Currently an entrepreneur in residence at venture capital firm Kleiner Perkins Caufield Byers. Formerly he was the deputy chief technology officer for the United States at the White House. Panchadsaram helped shape how an $80 billion budget can be used by federal agencies to deliver on their missions in a more effective design‐centric and data‐driven way. In 2014 Time magazine featured him on its cover as part of the crisis response team tasked with rescuing the rollout of Healthcare.gov. In response to that experience he helped found the US Digital Service—a “startup” within the White House that recruits the country's top technical talent to work on the government's most critical citizen‐facing services. Panchadsaram is an active designer and coder and held various product roles at Microsoft and ***. He holds a degree from the University of California Berkeley in industrial engineering and operations research.

Design is making inroads into the workings of government agencies within the DC Beltway and beyond. Civic‐minded designers take note. An overview of the design/government ecosystem in Washington, DC.

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Classification of power quality considering voltage sags occurred in feeders

Classification of power quality considering voltage sags occ...

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5th International Joint Conference on Computational Intelligence, IJCCI 2013

作者： Góes, Anderson Roges Teixeira Steiner, Maria Teresinha Arns Neto, Pedro José Steiner Graduate Programs in Numerical Methods in Engineering Federal University of Paraná Centro Politécnico CP: 19081 CEP: 81531-990 Curitiba PR Brazil Graduate Program in Industrial and Systems Engineering Pontifical Catholic University of Paraná Rua Imaculada Conceição 1155 Prado Velho CEP: 80.215-901 Curitiba PR Brazil Numerical Methods in Engineering and Industrial Engineering Federal University of Paraná Centro Politécnico CP: 1908 CEP: 81531-990 Curitiba PR Brazil Graduate Programs in Business Administration Federal University of Paraná Av. Pref. Lothario Meissner 632 CEP: 80210-170 Curitiba PR Brazil

ISBN: (纸本)9789898565778

In this paper we propose a methodology to classify Power Quality for feeders, based on sags and by the use of KDD technique, establishing a quality level printed in labels. To support the methodology, it was applied to feeders on a substation located in Curitiba, Paraná, Brazil, based on attributes such as sag length, duration and frequency (number of occurrences on a given period of time). In the search for feeders quality classification, on the Data Mining stage, the main stage on KDD process, three different techniques were used in a comparatively way for pattern recognition: Artificial Neural Networks, Support Vector Machines an Genetic Algorithms. Those techniques presented acceptable results in classification feeders with no possible classification using a simplified method based on maximum number of sags. Thus, by printing the label with information and Quality level, utilities companies can get better organized for mitigation procedures, by establishing clear targets.

关键词： Pattern recognition

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Firefly approach optimized wavenets applied to multivariable identification of a thermal process

Firefly approach optimized wavenets applied to multivariable...

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IEEE EUROCON

作者： Leandro dos Santos Coelho Carlos Eduardo Klein Luiz Guilherme J. Luvizotto Viviana Cocco Mariani Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana Volvo do Brasil Veiculos Ltda Department of Mechanical Engineering (PPGEM) Pontifical Catholic University of Parana

ISBN: (纸本)9781467322331

The combination of wavelet theory and feedforward artificial neural networks has resulted in wavelet neural networks or wavenets (WNNs). In these networks, the activation functions are described by discrete wavelet functions. Due to the promising properties of time-frequency localization and multi-resolution signal processing of the wavelet transform combined with the approximation capability of artificial neural networks, WNNs have found applications in dynamic system identification field during the past years. The paper aims at the development of the WNN based on traditional firefly algorithm (FA). The proposed FA is based on Tinkerbell map to tune the spread of wavelets and number of selected wavelet bases. The FA is a stochastic metaheuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. In FA, the flashing light can be formulated in such a way that it is associated with the objective function to be optimized, which makes it possible to formulate the firefly algorithm. The efficacy of WNN with FA tuning is tested on the identification of a multivariable thermal process.

关键词： Wavelet neural network System identification Firefly optimization Chaotic sequences Metaheuristics

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Swim velocity profile identification by using a modified differential evolution method associated with RBF Neural Network

Swim velocity profile identification by using a modified dif...

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International Conference on Innovative Computing Technology (INTECH)

作者： Leandro dos Santos Coelho Luciano Ferreira da Cruz Roberto Zanetti Freire Graduate Program - PPGEPS Federal University of Parana - UFPR Curitiba PR Brazil Industrial and Systems Engineering Pontifical Catholic University of Parana - PUCPR Curitiba PR Brazil

ISBN: (纸本)9781479900466

High level sports require a steady intensification of training in order to raise the athletes' performance. With the purpose of support swimmers and coaches new biomechanical analysis are been performed, becoming one of the most studied areas in swimming. By using technology resources, significant results related to performance improvements are being achieved. Specific analysis of the movements, strength, velocity and projection allow identifying relevant points that directly impact athletes' results. In this context, this work uses a Radial Basis Function Neural Network (RBF-NN) with training combining the Gustafson-Kessel clustering method and the proposed Modified Differential Evolution (MDE) in order to perform the swimmer velocity profile identification. The main idea is to obtain the dynamic of the velocity profile and to use it to improve the athletes' swim style. Differential Evolution (DE) is an evolutionary algorithm that uses a rather greedy and less stochastic approach to solve problems when compared to other evolutionary methods [1]. However, to achieve good performance with DE, the tuning of control parameters is essential as its performance is sensitive to the choice of the mutation and crossover settings. On the other hand, the RBF-NN is a powerful approach for nonlinear identification. This paper combines the two strategies described above proposing a modified DE algorithm based on the association of a sinusoidal signal and chaotic sequences generated by logistic map for the mutation factor tuning. By using data collected from breaststroke and crawl swim style of an elite female swimmer, the validity and the accuracy of the RBF-NN model have been tested by simulations. Results reveal that it is feasible to establish a good model to represent data experimental related to swimming field. Identification results show that MDE outperforms both other tested classical DE approaches for training RBF-NNs in terms of solution quality.

关键词： Training Mathematical model Estimation Linear programming Standards Time series analysis Vectors

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Wavelet neural network approach applied to biomechanics of swimming

Wavelet neural network approach applied to biomechanics of s...

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UK Workshop on Computational Intelligence (UKCI)

作者： Weslly Puchalski Viviana Cocco Mariani Felipe Fidelis Schauenburg Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana Curitiba Brazil Department of Mechanical Engineering University of Parana Curitiba Brazil Department of Electrical Engineering Federal University of Parana Curitiba Brazil

An artificial neural network (ANN) consists of a number of interconnecting artificial neurons and employs mathematical or computational models for information processing. ANNs are suitable for handling large amounts of dynamic, noisy and nonlinear data. On the other hand, the wavelet theory provides a multi-resolution approximation for discriminate functions. The combination of the wavelet transforms theory with the basic concept of ANNs leads to new mapping networks called wavelet neural networks (WNNs) or wavenets, which are proposed as an alternative to feedforward ANNs for approximating arbitrary nonlinear functions. Generalized from radial basis function ANNs, WNNs are in fact feed-forward neural networks with one hidden layer, radial wavelets as activation functions in the hidden nodes and a linear output layer. The contribution of this paper is to evaluate the WNNs to model a parathlete swimmer behavior. The parathlete swimmer swims the breaststroke style using biomechanics data generated by the software tool called SWUMSUIT, which was developed in Tokyo Technological Institute in Japan. The forecasted results clearly show that WNN has good prediction properties. The proposed WNN modeling approach can benefit disabled swimmers (parathletes) to gain competitive advantage by studying the biomechanics involved in the sport and considering the help of simulations systems.

关键词： Wavelet transforms Biomechanics Mathematical model Modeling Biological system modeling Force Artificial neural networks

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Hardware-based parallel firefly algorithm for embedded applications

Hardware-based parallel firefly algorithm for embedded appli...

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NASA/ESA Conference on Adaptive Hardware and systems (AHS)

作者： Daniel M. Muñoz Carlos H. Llanos Leandro dos Santos Coelho Mauricio Ayala-Rincón Electronics Engineering Graduate Program Faculty of Gama University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Departments of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9781467363822

The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times specifically for embedded optimization problems with computational limitations. For reducing execution times we propose a hardware parallel architecture of the FA algorithm that facilitates the implementation in Field programmable Gate Arrays (FPGAs). In addition, this work proposes the application of the opposition-based learning (OBL) approach to the FA algorithm. The respective hardware implementation (HPOFA) was mapped into a Virtex5 FPGA device and numerical experiments using four well-known benchmark problems demonstrate that the opposition-based approach allows the FA algorithm to improve its functionality, preserving the swarm diversity and avoiding the premature convergence problem. Synthesis results point out that the HPOFA architecture is effectively mapped in hardware and is suitable for embedded applications.

关键词： Hardware Computer architecture Optimization Equations Random access memory Field programmable gate arrays Search problems

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A multi-start procedure for the minimum latency problem

A multi-start procedure for the minimum latency problem

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7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013

作者： Angel-Bello, Francisco Alvarez, Ada García, Irma Tecnológico de Monterrey Campus Monterrey Department of Industrial and Systems Engineering Ave. Eugenio Garza Sada 2501 Monterrey Nuevo León CP 64849 Mexico Universidad Autónoma de Nuevo León Graduate Program in Systems Engineering Ave. Universidad s/n San Nicolás Nuevo León CP 66451 Mexico Universidad Autónoma de Coahuila Research Center on Applied Mathematics Edif. S Campo Redondo Saltillo Coahuila CP 25280 Mexico

ISBN: (纸本)9783902823359

In this paper we address a minimum latency problem and propose a multi-start strategy for solving it. For constructing initial solutions two procedures are designed, which are based on metaheuristic GRASP. We also develop a post-processing procedure based on Path Relinking to improve the obtained solutions. We carry up an extensive experimentation with 225 symmetrical instances to evaluate our procedures. In addition, using instances from literature, we compare our best procedure with previously reported methods, showing that the proposed procedure outperforms them in terms of solution quality and in elapsed CPU time to reach the solution. © IFAC.

关键词： Supply chains

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Simulation-based analysis of scheduling decisions in an outpatient clinic

Simulation-based analysis of scheduling decisions in an outp...

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IIE Annual Conference and Expo 2013

作者： Akin, Gokce Ivy, Julie S. Huschka, Todd R. Rohleder, Thomas R. Graduate Program in Operations Research North Carolina State University Raleigh NC 27695 United States Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University Raleigh NC 27695 United States Department of Health Care Policy and Research Mayo Clinic 200 1st ST SW Rochester MN 55905 United States

ISBN: (纸本)9780983762423

In an outpatient clinic, in which multiple classes of patients are given appointments, capacity management and scheduling decisions are particularly important. Once an appointment is scheduled;it is not uncommon for the appointment to be rescheduled or cancelled prior to the appointment day, or a patient may simply not show-up on his/her appointment day. Thus it is crucial to consider all of these patient behaviors when assigning an appointment. In this study we consider multiple classes of patients with different demand rates, service times, and different delay-dependent reschedule, cancellation, and no-show rates. We develop a simulation model to analyze the effects of reducing the appointment planning horizon. In our experimental analysis we also evaluate different calendar structures: traditional slots, standardized 20 or 30 minute slots, and slotless designs. We use capacity utilization and "seen" patient proportions as the performance indicators in our model. Our results indicate that we can significantly increase physician utilizations and the percentage of seen patients by reducing the appointment planning horizon. We also observe improvements in the performance indicators if we use a slotless design or standardized appointments with shorter slot lengths.

关键词： Scheduling

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A scoring model to detect abusive billing patterns in health insurance claims

A scoring model to detect abusive billing patterns in health...

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第二届(2013)老年人口与健康产业国际会议

作者： Hyunjung Shin Hayoung Park Junwoo Lee Won Chul Jhee Department of Industrial and Information Systems Engineering Ajou UniversitySan 5 Woncheon-dongYeo Technology Management Economicsand Policy Graduate ProgramSeoul National University599 Gwanak-ro Department of Industrial and Information Engineering Hongik University72-1 Sangsu-dongMapo-gu Seou

We propose a scoring model that detects outpatient clinics with abusive utilization patterns based on profiling information extracted from electronic insurance *** model consists of (1) scoring to quantify the degree of abusiveness and (2) segmentation to categorize the problematic providers with similar utilization *** performed the modeling for 3705 Korean internal medicine *** applied data from practitioner claims submitted to the National Health Insurance Corporation for outpatient care during the 3rd quarter of 2007 and used 4th quarter data to validate the *** considered the Health Insurance Review and Assessment Services decisions on interventions to be accurate for model *** compared the conditional probability distributions of the composite degree of anomaly (CDA) score formulated for intervention and non-intervention *** assess the validity of the model,we examined confusion matrices by intervention history and group as defined by the CDA *** CDA aggregated 38 indicators of abusiveness for individual clinics,which were grouped based on the CDAs,and we used the decision tree to further segment them into homogeneous clusters based on their utilization *** validation indicated that the proposed model was largely consistent with the manual detection techniques currently used to identify potential *** proposed model,which can be used to automate abuse detection,is flexible and easy to *** may present an opportunity to fight escalating healthcare costs in the era of increasing availability of electronic healthcare information.

关键词： Health insurance claims Medical abuse detection Fraud detection Degrees of anomaly Data mining

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