
Beyond utilitarianism: a method for analyzing competing ethical principles in a decision analysis of liver transplantation.
The utilitarian foundation of decision analysis limits its usefulness for many social policy decisions. In this study, the authors examine a method to incorporate competing ethical principles in a decision analysis of liver transplantation for a patient with acute liver failure (ALF).A Markov model was constructed to compare the benefit of transplantation for a patient with ALF versus the harm caused to other patients on the waiting list and to determine the lowest acceptable 5-y posttransplant survival for the ALF patient. The weighting of the ALF patient and other patients was then adjusted using a multiattribute variable incorporating utilitarianism, urgency, and other principles such as fair chances.In the base-case analysis, the strategy of transplanting the ALF patient resulted in a 0.8% increase in the risk of death and a utility loss of 7.8 quality-adjusted days of life for each of the other patients on the waiting list. These harms cumulatively outweighed the benefit of transplantation for an ALF patient having a posttransplant survival of less than 48% at 5 y. However, the threshold for an acceptable posttransplant survival for the ALF patient ranged from 25% to 56% at 5 y, depending on the ethical principles involved.The results of the decision analysis vary depending on the ethical perspective. This study demonstrates how competing ethical principles can be numerically incorporated in a decision analysis.
Duke Scholars
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Related Subject Headings
- Waiting Lists
- Tissue and Organ Procurement
- Survival Analysis
- Markov Chains
- Liver Transplantation
- Humans
- Health Policy & Services
- Decision Support Techniques
- Acute Disease
- 4206 Public health
Citation

Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Waiting Lists
- Tissue and Organ Procurement
- Survival Analysis
- Markov Chains
- Liver Transplantation
- Humans
- Health Policy & Services
- Decision Support Techniques
- Acute Disease
- 4206 Public health