This paper addresses the design problem of outpatient chemotherapy oncology departments. The objective is to identify the most effective resource configuration (e.g. number of chairs, number of oncologists) to reduce the patient waiting time and increase the average number of daily treatments. A stochastic simulation model was developed to emulate the patient flow in different oncology unit configurations. Then, it was used to generate the expected results of an extended design of experiments. To evaluate the impact of the different resources on the performance of the oncology departments the ANOVA analysis was employed. Besides, a Pareto multi-objective analysis was carried out to further support any decision-maker in the selection of the most suitable resource configuration. Particularly, to make easier the decision-making process, a comprehensive table chart was elaborated. Finally, a multiple non-linear regression model was generated in order to empower the health managers in easily assessing the performance of any real ward configuration. The analysis of results pointed out that the two mentioned objectives are rather conflicting. Furthermore, it proved that a higher number of resources not necessarily implies a significant improvement in the performance measures.
System design of outpatient chemotherapy oncology departments through simulation and design of experiments
	
	
	
		
		
		
		
		
	
	
	
	
	
	
	
	
		
		
		
		
		
			
			
			
		
		
		
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
		
		
		
	
Corsini R. R.
						
						
							Primo
						
						
							Methodology
;Costa A.;Fichera S.;Pluchino A.;Parrinello V.
			2024-01-01
Abstract
This paper addresses the design problem of outpatient chemotherapy oncology departments. The objective is to identify the most effective resource configuration (e.g. number of chairs, number of oncologists) to reduce the patient waiting time and increase the average number of daily treatments. A stochastic simulation model was developed to emulate the patient flow in different oncology unit configurations. Then, it was used to generate the expected results of an extended design of experiments. To evaluate the impact of the different resources on the performance of the oncology departments the ANOVA analysis was employed. Besides, a Pareto multi-objective analysis was carried out to further support any decision-maker in the selection of the most suitable resource configuration. Particularly, to make easier the decision-making process, a comprehensive table chart was elaborated. Finally, a multiple non-linear regression model was generated in order to empower the health managers in easily assessing the performance of any real ward configuration. The analysis of results pointed out that the two mentioned objectives are rather conflicting. Furthermore, it proved that a higher number of resources not necessarily implies a significant improvement in the performance measures.| File | Dimensione | Formato | |
|---|---|---|---|
| 
									
										
										
										
										
											
												
												
												    
												
											
										
									
									
										
										
											Corsini et al._IJMSEM_2022.pdf
										
																				
									
										
											 solo gestori archivio 
											Descrizione: Original paper
										 
									
									
									
										
											Tipologia:
											Versione Editoriale (PDF)
										 
									
									
									
									
										
											Licenza:
											
											
												NON PUBBLICO - Accesso privato/ristretto
												
												
												
											
										 
									
									
										Dimensione
										2.91 MB
									 
									
										Formato
										Adobe PDF
									 
										
										
								 | 
								2.91 MB | Adobe PDF | Visualizza/Apri | 
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


