The optimal approach for parameter settings based on adjustable contracting capacity for the hospital supply chain logistics system

Liao, Hung‐Chang; Chang, Hsu-Hwa

doi:10.1016/j.eswa.2010.09.168

Cited by 15 publications

(9 citation statements)

References 37 publications

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“…(2) These studies focus on the design of the network. Procurement logistics [ 27 , 268 , 269 ] SD (1); Misc. (2) Cross-department (1), cross-institutional (2) Qnet2000 (1); iThink (1); Misc.…”

Section: Resultsmentioning

confidence: 99%

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

et al. 2018

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BackgroundResource allocation in patient care relies heavily on individual judgements of healthcare professionals. Such professionals perform coordinating functions by managing the timing and execution of a multitude of care processes for multiple patients. Based on advances in simulation, new technologies that could be used for establishing realistic representations have been developed. These simulations can be used to facilitate understanding of various situations, coordination training and education in logistics, decision-making processes, and design aspects of the healthcare system. However, no study in the literature has synthesized the types of simulations models available for non-technical skills training and coordination of care.MethodsA systematic literature review, following the PRISMA guidelines, was performed to identify simulation models that could be used for training individuals in operative logistical coordination that occurs on a daily basis. This article reviewed papers of simulation in healthcare logistics presented in the Web of Science Core Collections, ACM digital library, and JSTOR databases. We conducted a screening process to gather relevant papers as the knowledge foundation of our literature study. The screening process involved a query-based identification of papers and an assessment of relevance and quality.ResultsTwo hundred ninety-four papers met the inclusion criteria. The review showed that different types of simulation models can be used for constructing scenarios for addressing different types of problems, primarily for training and education sessions. The papers identified were classified according to their utilized paradigm and focus areas. (1) Discrete-event simulation in single-category and single-unit scenarios formed the most dominant approach to developing healthcare simulations and dominated all other categories by a large margin. (2) As we approached a systems perspective (cross-departmental and cross-institutional), discrete-event simulation became less popular and is complemented by system dynamics or hybrid modeling. (3) Agent-based simulations and participatory simulations have increased in absolute terms, but the share of these modeling techniques among all simulations in this field remains low.ConclusionsAn extensive study analyzing the literature on simulation in healthcare logistics indicates a growth in the number of examples demonstrating how simulation can be used in healthcare settings. Results show that the majority of studies create situations in which non-technical skills of managers, coordinators, and decision makers can be trained. However, more system-level and complex system-based approaches are limited and use methods other than discrete-event simulation.

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Section: Resultsmentioning

confidence: 99%

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

et al. 2018

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“…To improve the logistics processes of this warehouse, seven proposal actions were suggested based on best practices retrieved from papers found in the academic literature about healthcare [ 53 ]. Thus, all proposals are well-grounded and had already been proven effective when applied in similar contexts, taking into consideration its particularities [ 31 , 35 , 36 , 37 , 40 , 44 , 47 , 48 ].…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, for the OPSM request, studies suggest that the best process is to keep a minimum stock level in the satellite warehouse and request materials according to the elective surgery schedule. Although hospitals provide essential services and require above-average inventory levels, this format goes according to the just-in-time methodology, which seeks to operate with minimum inventory levels and maximum rationalization of resources [ 37 , 40 , 41 , 42 ].…”

Section: Improvement Proposalsmentioning

confidence: 99%

Lessons from a Surgical Center Satellite Warehouse in a Large Brazilian Public Hospital

et al. 2021

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Brazilian public hospitals face several operational problems not only related to poor public management practices and their complex nature, but also the economic, and social contexts. Considering this scenario and the fact that efforts in supply management might affect a hospital organization’s excellence, this research aims to identify improvements in the logistic operations at the surgical center satellite warehouse of a Public Hospital located in Brazil. A case study based on an exploratory and qualitative approach was conducted by employing document analysis, semi-structured interviews, and on-site observations. Seven major problems concerning lack of surgical material, the non-definition of crucial logistic parameters, low information flow, surgical supply control, and management problems were pointed and addressed by seven independent but complementary actions that considered the Brazilian healthcare system’s particularities. Given the nature of exploratory research, the results are not exhaustive and cannot be generalized to different contexts. However, they help understand that reducing the waste of the logistics processes makes it possible to improve the attention to the local population that uses public health services.

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“…Assuming there was no intercept in the linear ideal function, there came to yij=βMj, where Mj denoted the j th signal factors level and β was the slope. To evaluate the performance in the dynamic EMS systems using the Taguchi method, the equation SN=10log10false(β/MSEfalse) was applied, in which MSE was the mean square error of the distance from the measured response to the best-fitted line [50,51].…”

Section: The Dynamic Taguchi Methods and Neural Network For The Optmentioning

confidence: 99%

The Application of GSCM in Eliminating Healthcare Waste: Hospital EDC as an Example

Chang

Wang

Liao

et al. 2019

IJERPH

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Eliminating unnecessary healthcare waste in hospitals and providing better healthcare quality are the core issues of green supply chain management (GSCM). Hence, this study used a hospital’s emergency department crowding (EDC) problem to illustrate how to establish an emergency medicine service (EMS) simulation system to obtain a robust parameters setting for solving hospitals’ EDC and waste problems, thereby increasing healthcare quality. Inappropriate resource allocation results in more serious EDC; more serious EDC results in increasing operating costs. Therefore, in the healthcare system, waste includes inappropriate costs and inappropriate resource allocation. The EMS of a medical center in central Taiwan was the object of the study. In this study, the dynamic Taguchi method was used to set the signal factor, noise factor, and control factors to simulate the EMS system to obtain the optimal parameters setting. The performance was set to Emergency Department Work Index (EDWINC) and system time (waiting time and service time) per patient. The signal factor was set to the number of physicians; the noise factor was set to patient arrival rate; the control factors included persuading Triage 4 and Triage 5 outpatients, checkup process, bed occupation rate in the emergency department (ED), and medical checkup sequence for Triage 4 and Triage 5 patients. This study makes two significant contributions. First, the study introduces the GSCM concept to the healthcare setting to bring green innovation to hospitals. Hospital administrators may hence design better GSCM activities to facilitate healthcare processes to provide better healthcare outcomes. Second, the study applied the dynamic Taguchi method to the EMS and neural network (NN) to construct a computational model revealing the cause (factors) and effect (performances) relationship. In addition, the genetic algorithm (GA), a solution method, was used to obtain the optimal parameters setting of the EDC in Taiwan. Hence, after obtaining the solutions, the unnecessary waste in EDC—inappropriate costs and inappropriate resource allocation—is reduced.

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The optimal approach for parameter settings based on adjustable contracting capacity for the hospital supply chain logistics system

Cited by 15 publications

References 37 publications

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

Lessons from a Surgical Center Satellite Warehouse in a Large Brazilian Public Hospital

The Application of GSCM in Eliminating Healthcare Waste: Hospital EDC as an Example

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