WSC 2004 Final Abstracts

Sunday 1:00:00 PM 2:30:00 PM
Scheduling Issues
Chair: David Ferrin (Business Prototyping)

Abstract:
A discrete event simulation model has been set up in order to analyze the renal transplant waiting list in the País Valencià, one of the autonomous regions in which Spain is divided. The model combines the information of the arrival of the patients onto the list and the process of donations, which also depend on the number of kidneys provided by each donor. Bayesian inference has been used to take into account the uncertainty about the parameters of the input distributions (acceptance, donation and transplantation rates). After validating the model, predictions about the future behaviour of the waiting list have been done. Results indicate a decrease in the size of the waiting list in a short and middle term. Comparison with other strategies of simulation has been done in order to confirm the problem of underestimation of the variance of the expected simulation output.

Analyzing Incentives and Scheduling in a Major Metropolitan Hospital Operating Room through Simulation
David M. Ferrin and Martin J. Miller (Business Prototyping, Inc.) and Sherry Wininger and Michael S. Neuendorf (St. Vincent's Hospital)

Abstract:
This paper discusses the application of simulation to analyze the value proposition and construction of an incentive program in an Operating Room (OR) environment. The model was further used to evaluate operational changes including scheduling processes within the OR and utilization rates in areas such as Post Anesthesia Care Unit (PACU) and the Ambulatory Surgery Department (ASD). Lessons learned are presented on developing multiple simulation models from one application as well as issues regarding model transition to a client.

Outpatient Clinic Scheduling – A Simulation Approach
Ming Guo, Michael Wagner, and Constance E. West (Cincinnati Children's Hospital Medical Center)

Abstract:
The process by which outpatients are scheduled for a doctor’s visit is a crucial determinant of the overall efficiency of the patient flow. The problem at hand consists of determining prioritization (triage) rules so that adequate patient care is guaranteed, resources (provider schedules) are utilized efficiently and a service guarantee can be ensured. We present a simulation framework for the evaluation and optimization of scheduling rules. We outline the basic ingredients of our model, illustrate the kinds of analyses it has enabled us to perform and summarize our experience with a preliminary implementation for the Division of Pediatric Ophthalmology at Cincinnati Children’s Hospital Medical Center. Challenges for adaptations to other settings are also outlined.

Predicting the Behaviour of the Renal Transplant Waiting List in the Pais Valencia (Spain) Using Simulation Modeling
Juan J. Abellán (Imperial College), Carmen Armero and David V. Conesa (Universitat de València), Jordi Pérez-Panadés (Institut Valencià d’Investigacions Agràries) and Miguel A. Martínez-Beneito, Oscar Zurriaga, María J. García-Blasco, and Herme Vanaclocha (Generalitat Valenciana)

Abstract:
Hospitals today are investing time and money to expand and improve their Emergency Departments (ED). Using simulation to test their many improvement ideas can necessitate running numerous scenarios. Model changes such as the number of ED beds, inpatient beds and process improvements will yield an exponentially growing list of permutations in alternative ED designs. This paper uses recent project experience to describes where to begin and which steps to take to go from an As-Is ED configuration to the best To-Be configuration.

A Simple and Intuitve Simulation Tool for Analyzing the performance of Emergency Departments
David Sinreich (Technion - Israel Instiute of Technology) and Yariv Marmor (Technion - Israel Institute of Technology)

Abstract:
In recent years hospitals have been vigorously searching for ways to reduce costs and improve productivity. One tool, simulation, is now widely accepted as an effective method for assisting management in evaluating different operational alternatives. It can help improve existing Emergency Departments (EDs) and assist in planning and designing new EDs. In order to increase the acceptance of simulation in healthcare systems in general and EDs in par-ticular, hospital management should be directly involved in the development of these projects. Such involvement will also bolster the model's credibility. In addition, it is impor-tant to simplify simulation processes as much as is rea-sonably possible and use visual aids or animation that will heighten users' confidence in the model’s ability. This study lays the foundation for the development of a simula-tion tool which is general, flexible, intuitive, simple to use and contains default values for most of the system’s parameters.

Functional Analysis for Operating Emergency Department of a General Hospital
Soemon Takakuwa and Hiroko Shiozaki (Nagoya University)

Abstract:
An entire emergency department of a general hospital is simulated to examine patient flows. First, times needed for both outpatients and patients arriving via ambulance to be processed in the emergency department are examined. A special-purpose data-generator is designed and developed to create experimental data for executing a simulation. It is found that the patients spend the longer part of their time waiting, depending on the number of patients to be processed. In addition, it is found that the waiting time for available emergency-treatment beds, doctors, drips, and stretchers accounts for the major part of all the waiting time in the emergency department. A stepwise procedure of operations planning is proposed to minimize the patient waiting times, and numerical examples are shown to illustrate the procedure.

Fixing the Emergency Department: A Transformational Journey with EDsim
Martin J. Miller and David M. Ferrin (Business Prototyping, Inc.) and Marcia Messer (Ascension Health)

Monday 10:30:00 AM 12:00:00 PM
What-if Analysis
Chair: Peter Bosch (Highpoint Software Systems)

Abstract:
The Telemedicine Program was created to provide medical assistance to people living in extreme poverty conditions in Mexico. Through a satellite connection, a physician located in Mexico City can diagnose the patient who is physically inspected on a mobile unit, equipped with telecommunications gear. The program’s performance has brought positive results, and is starting to expand to farther regions. This paper explains how the program’s processes were simulated on a specially designed logical-mathematical computer model in order to observe, and analyze the possible results generated when specific information of the model’s parameters is introduced. The results shown by the model when different scenarios are being run, can be used as a powerful tool in the decision making process in order to optimize the program’s performance by maximizing its utilization and efficiency, looking forward to incrementing its productivity.

Autonomous Predictive-Adaptive Simulation for Operations Support
Peter Bosch (Highpoint Software Systems, LLC) and Majdi Rajab (M-Solutions)

Abstract:
This paper describes a simulation system that integrates with existing control & sensing systems to monitor operations on a production floor, periodically creating models of those operations, and running a simulation that predicts the next several shifts’ events. As procedures are executed in the real world, deviations are introduced between the expected activities and the actual occurrences. More deviations arise from explicit adaptations undertaken by operations staff in response to already-observed anomalies. With each new cycle, those deviations are automatically integrated into the model, heuristics are applied to estimate the likely future course of events, and a new simulation is run. A new set of predictions is generated from that simulation, and the system’s new predictions are compared with its older predictions. Differences between the pre-loop prediction and the post-loop prediction serve to indicate whether the situation is improving or degrading, providing operators with new predictive analysis and planning capabilities.

A Study of the CT Scan Area of a Healthcare Provider
Sreekanth Ramakrishnan (State University of New York- Binghamton), Kaustubh Nagarkar, Monice DeGennaro, and Krishnaswami Srihari (State University of New York-Binghamton) and Andrea K. Courtney and Frank Emick (Wilson Memorial Regional Medical Center)

Abstract:
Ancillary departments, which include radiology services, are among the important factors that affect the efficiency of patient care in a hospital. This paper presents results from a collaborative research effort with a healthcare provider that is in the process of implementing a digital image archiving system within its radiology services. The objective of this study was to identify the changes to the existing workflow at the CT Scan area with the implementation of the digitized archiving system to maximize patient throughput and minimize report generation time. Process mapping was used to identify the initial flow of operations. A simulation model was then built to evaluate the different what-if scenarios that were expected to ‘optimize’ the aforementioned response variables. Several key suggestions were also presented and validated using simulation. These include increasing the number of reading radiologists, re-allocation of CT Scan machine resources and the addition of a patient holding area.

Simulation Model of the Telemedicine Program
Juan Mauricio Lach and Ricardo Manuel Vázquez (Universidad Anáhuac)

Abstract:
We present a model to explain the effects of the long time between blood stem cell divisions and rapid cascades of progenitor cell divisions on the mitochondrial DNA drift. We allow four stochastic events in the system namely, mtDNA replication and degradation, cell division and death. To implement the conceptual model, we design two simulation models; one for a limited number of stem cells (20,000) over very long time scale (100 years) and another for the cell divisions of a progenitor cell resulting in a large number of blood cells (~10 million) over a shorter time span (25 days). Iterative enhancement with incremental builds constitutes the modeling methodology. We adopt the activity scanning conceptual framework for the model im-plementation. Initial transient and memory issues are re-solved. By output data analysis, we conclude that the varia-tion in mutation level occurs significantly due to time and less so due to cell divisions.

Modeling the Progression and Treatment of HIV
Steven M. Shechter, Andrew J. Schaefer, R. Scott Braithwaite, and Mark S. Roberts (University of Pittsburgh)

Abstract:
Current treatment of HIV patients is based on various guidelines that have changed with the advent of newer antiretroviral therapies and the emergence of resistance to them. However, there remains uncertainty over the best time to initiate HIV therapy or when to switch. Observational cohort studies or clinical trials are limited in the number of scenarios they can examine, whereas simulation modeling is well suited for considering various treatment policies. We describe a Monte Carlo simulation of a cohort of HIV positive patients that explicitly models two key components of HIV progression: adherence and the acquisition of resistance. Simulation results closely match cohort statistics such as survival time and length of time on the first three treatment regimens. We also describe sensitivity analyses and experiments such as testing the effects of starting therapy at different levels.

The Role of Process Simulation and Scheduling Tools in the Development and Manufacturing of Biopharmaceuticals
Demetri Petrides and Charles Siletti (INTELLIGEN, INC.)

Abstract:
Pharmaceutical manufacturers generally employ either or-ganic synthesis or biotechnology. Each of these technolo-gies has unique challenges, but batch process simulation and scheduling tools can facilitate process development in both. Batch process simulation is distinct from both tradi-tional chemical process simulation and dynamic simulation and is uniquely suited to pharmaceutical processes. Fur-thermore, there is a close relationship between the data re-quired for batch simulation and the data required for batch process scheduling. An example biopharmaceutical process illustrates how batch simulation can help improve a proc-ess. A scheduling example illustrates the relationship be-tween batch simulation and scheduling.

A Simulation Methodology in Modeling Cell Divisions with Stochastic Effects
Harsha Karur Rajasimha and David C. Samuels (Virginia Tech) and Richard E. Nance (Virginia Polytechnic Institute and State University)

Future of Simulation in Biotechnology Industry
Prasad V Saraph (Bayer HealthCare)

Abstract:
In the 21st century, the Biotechnology industry has the po-tential to inspire a number of management tools and theo-ries, just as the Automobile industry did in the 20th century. This paper explores the opportunities for simulation in Biotechnology over the next few years and provides struc-ture for the panel discussion in Biotechnology and HealthCare track. We detail the structure for Biotechnol-ogy industry, review status and opportunities for simula-tion and present gap analysis of opportunities and tools available. The purpose of the panel discussion is to discuss the role for simulation community in Biotechnology in-dustry over the next few years and identify key areas where simulation can add value.