A blood supply chain (BSC) is a very long and complex sequence of processes heavily sequential. If one of them is executed in an incorrect way and this error is not detected, it leads to an incorrect transfusion outcome, that could seriously affect patients. For this reason, there is a strong need to identify and prevent adverse events along the entire BSC, in order to reduce their probability of occurrence. This also helps improving BSC sustainability from both the environmental and the social perspectives. The paper extends an existing healthcare supply chain risk management framework already applied to the blood transfusion process to address multiple BSC echelons and identify the cause and effect relationships among the adverse events that might occur. To this end, Fault Tree Analysis is added to the risk management tools part of the original framework as well as Key Performance Indicators are applied to detect risky event manifestation. The first application of the proposed approach to a blood bank and a hospital ward revealed its effectiveness in identifying the BSC activities most subjected to risk. Also, connections between adverse events and causal relationships among their sources were found, leading to understanding whether an adverse event is caused by a risk source in the same echelon where it occurs or by the concurrent manifestation of several adverse events upstream in the BSC. Future research will be devoted to numerically evaluate probability of occurrence and impact of risky events as well as integrating the framework with a classification of criticalities based on their severity.

An enhanced framework for blood supply chain risk management / Cagliano, Anna Corinna; Grimaldi, Sabrina; Rafele, Carlo; Campanale, Chiara. - In: SUSTAINABLE FUTURES. - ISSN 2666-1888. - ELETTRONICO. - 4:(2022), pp. 1-10. [10.1016/j.sftr.2022.100091]

An enhanced framework for blood supply chain risk management

Cagliano, Anna Corinna;Grimaldi, Sabrina;Rafele, Carlo;Campanale, Chiara
2022

Abstract

A blood supply chain (BSC) is a very long and complex sequence of processes heavily sequential. If one of them is executed in an incorrect way and this error is not detected, it leads to an incorrect transfusion outcome, that could seriously affect patients. For this reason, there is a strong need to identify and prevent adverse events along the entire BSC, in order to reduce their probability of occurrence. This also helps improving BSC sustainability from both the environmental and the social perspectives. The paper extends an existing healthcare supply chain risk management framework already applied to the blood transfusion process to address multiple BSC echelons and identify the cause and effect relationships among the adverse events that might occur. To this end, Fault Tree Analysis is added to the risk management tools part of the original framework as well as Key Performance Indicators are applied to detect risky event manifestation. The first application of the proposed approach to a blood bank and a hospital ward revealed its effectiveness in identifying the BSC activities most subjected to risk. Also, connections between adverse events and causal relationships among their sources were found, leading to understanding whether an adverse event is caused by a risk source in the same echelon where it occurs or by the concurrent manifestation of several adverse events upstream in the BSC. Future research will be devoted to numerically evaluate probability of occurrence and impact of risky events as well as integrating the framework with a classification of criticalities based on their severity.
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S2666188822000259-main.pdf

accesso aperto

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Creative commons
Dimensione 737.6 kB
Formato Adobe PDF
737.6 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2970845