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A Framework for Assessing Disruptions in a Clinical Supply Chain Using Bayesian Belief Networks

  • Mark RodgersEmail author
  • Dashi Singham
Original Article
  • 27 Downloads

Abstract

Purpose

Clinical trial study failures cause significant disruptions to supply chain operations, which lead to operational inefficiencies and financial losses.

Methods

In this paper, a framework to construct a Bayesian belief network (BBN) by leveraging subject matter expertise and probabilistic elicitation methods to quantify the probability of a disruption to a clinical supply chain is presented.

Results

The effect of varying input factors on a disruption probability is studied, and new metrics are developed to evaluate the significance of a disruption.

Conclusions

This framework allows practitioners to assess the probability of disruptions to their network, thus enabling targeted strategies to be developed and implemented.

Keywords

Bayesian belief networks Clinical trials Disruption Risk analysis Supply chain management Probabilistic elicitation 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

For this type of study, formal consent is not required.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Supply Chain ManagementRutgers Business SchoolNewarkUSA
  2. 2.Department of Operations ResearchNaval Postgraduate SchoolMontereyUSA

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