Incorporating biology into discrete event simulation models of organ allocation

Kreke, Jennifer E.; Schaefer, Andrew J.; Angus, Derek C.; Bryce, Cindy L.; Roberts, Mark S.

doi:10.1109/wsc.2002.1172927

Cited by 15 publications

(15 citation statements)

References 3 publications

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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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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

View full text Add to dashboard Cite

show abstract

“…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 discrete event simulation model of the USA liver allocation system is proposed in [9]; the model has been validated with data from patients of the University of Pittsburgh Medical Center; different selection and organ allocation rules are compared in terms of life expectancy, size of waiting list, and other relevant outcomes characteristics of the transplantation process.…”

Section: The Transplant Systemmentioning

confidence: 99%

A new organ transplantation location–allocation policy: a case study of Italy

Bruni

Conforti

Sicilia

et al. 2006

Health Care Manage Sci

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In this paper, we propose a location model for the optimal organization of transplant system. Instead of simulation approach, which is typical when facing many health care applications, our approach is distinctively based on a mathematical programming formulation of the relevant problem. In particular, we focus on the critical role of time in transplantation process as well as on a spatial distribution of transplant centers. The allocation of transplantable organs across regions with the objective of attaining regional equity in health care, is the aim of this paper. Our model differs from previous modeling approaches in that it considers the nationwide reorganization of the transplant system, identifying system barriers that may impair equity and efficiency. The demolition of these barriers may leads on a reduction of waiting lists and of wasted organs. We provide the basic structure and the properties of the model, and validate it on a real case study. The experimental validation of the model demonstrates the effectiveness and robustness of our proposal.

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Incorporating biology into discrete event simulation models of organ allocation

Cited by 15 publications

References 3 publications

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

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

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

A new organ transplantation location–allocation policy: a case study of Italy

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