A Clinically Based Discrete-Event Simulation of End-Stage Liver Disease and the Organ Allocation Process

Shechter, Steven M.; Bryce, Cindy L.; Alagöz, Oğuzhan; Kreke, Jennifer E.; Stahl, James E.; Schaefer, Andrew J.; Angus, Derek C.; Roberts, Mark S.

doi:10.1177/0272989x04268956

Cited by 96 publications

(78 citation statements)

References 10 publications

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“…One of the first papers in this vein is by Ruth et al (1985), in which the authors develop a simulation model to study the problem. Shechter et al (2005) also introduce a discrete event simulation model for the evaluation of potential changes to the liver allocation process. In this work, we utilize the simulation model developed by the SRTR, see KPSAM (2008).…”

Section: Literature Reviewmentioning

confidence: 99%

Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation

Bertsimas

Farias

Trichakis³

2013

Operations Research

169

109

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We propose a scalable, data-driven method for designing national policies for the allocation of deceased donor kidneys to patients on a waiting list, in a fair and efficient way. We focus on policies that have the same form as the one currently used in the U.S. In particular, we consider policies that are based on a point system, which ranks patients according to some priority criteria, e.g., waiting time, medical urgency, etc., or a combination thereof. Rather than making specific assumptions about fairness principles or priority criteria, our method offers the designer the flexibility to select his desired criteria and fairness constraints from a broad class of allowable constraints. The method then designs a point system that is based on the selected priority criteria, and approximately maximizes medical efficiency, i.e., life year gains from transplant, while simultaneously enforcing selected fairness constraints.Among the several case studies we present employing our method, one case study designs a point system that has the same form, uses the same criteria and satisfies the same fairness constraints as the point system that was recently proposed by U.S. policymakers. In addition, the point system we design delivers an 8% increase in extra life year gains. We evaluate the performance of all policies under consideration using the same statistical and simulation tools and data as the U.S. policymakers use. Other case studies perform a sensitivity analysis (for instance, demonstrating that the increase in extra life year gains by relaxing certain fairness constraints can be as high as 30%), and also pursue the design of policies targeted specifically at remedying criticisms leveled at the recent point system proposed by U.S. policymakers.We emphasize that our methodology is not a mechanistic replacement for professional medical or ethical judgment but rather serves as a tool to circumvent exhaustive experimentation with point systems given such input.

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Section: Literature Reviewmentioning

confidence: 99%

Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation

Bertsimas

Farias

Trichakis³

2013

Operations Research

169

109

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“…Simulation modeling has been used to study a wide range of problems in health care [13,15,29,35,45]. In recent years, Zenios et al [51], Kreke et al [31], and Shechter et al [44] utilized simulation models even to study organ allocation systems. A comprehensive review of health care simulation models can be found in Klein et al [30] and Jun et al [27].…”

Section: Simulation-optimization Modelsmentioning

confidence: 99%

A data-integrated simulation-based optimization for assigning nurses to patient admissions

Sundaramoorthi

Chen

Rosenberger

et al. 2010

Health Care Manag Sci

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The health care system in the United States has a shortage of nurses. A careful planning of nurse resources is needed to ease the health care system from the burden of the nurse shortage and standardize nurse workload. An earlier research study developed a data-integrated simulation to evaluate nurse-patient assignments (SIMNA) at the beginning of a shift based on a real data set provided by a northeast Texas hospital. In this research, with the aid of the same SIMNA model, two policies are developed to make nurse-to-patient assignments when new patients are admitted during a shift. A heuristic (HEU) policy assigns a newly-admitted patient to the nurse who has performed the least assigned direct care among all the nurses. A partially-optimized (OPT) policy seeks to minimize the difference in workload among nurses for the entire shift by estimating the assigned direct care from SIMNA. Results comparing HEU and OPT policies are presented.

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“…Simulation modeling has been used to study a wide range of problems in health care [15,17,28,34,46]. In recent years, Zenios et al [52], Kreke et al [31], and Shechter et al [41] utilized simulation models to study organ allocation systems. A comprehensive review of health care simulation models can be found in Klein et al [30] and Jun et al [27].…”

Section: Simulation Modeling In Health Carementioning

confidence: 99%

A data-integrated simulation model to evaluate nurse–patient assignments

Sundaramoorthi

Chen

Rosenberger

et al. 2008

Health Care Manag Sci

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This research develops a novel data-integrated simulation to evaluate nurse-patient assignments (SIMNA) based on a real data set provided by a northeast Texas hospital. Tree-based models and kernel density estimation (KDE) were utilized to extract important knowledge from the data for the simulation. Classification and Regression Tree models, data mining tools for prediction and classification, were used to develop five tree structures: (a) four classification trees from which transition probabilities for nurse movements are determined, and (b) a regression tree from which the amount of time a nurse spends in a location is predicted based on factors such as the primary diagnosis of a patient and the type of nurse. Kernel density estimation is used to estimate the continuous distribution for the amount of time a nurse spends in a location. Results obtained from SIMNA to evaluate nurse-patient assignments in Medical/Surgical unit I of the northeast Texas hospital are discussed.

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A Clinically Based Discrete-Event Simulation of End-Stage Liver Disease and the Organ Allocation Process

Abstract: The authors created a discrete-event simulation model that represents the biology of end-stage liver disease and the health care organization of transplantation in the United States.

Cited by 96 publications

References 10 publications

Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation

Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation

A data-integrated simulation-based optimization for assigning nurses to patient admissions

A data-integrated simulation model to evaluate nurse–patient assignments

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