Abstract

Purpose of ReviewA transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard.Recent FindingsKidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and transplant healthcare. A systems approach leverages techniques for visualizing the system architecture to support solution design from multiple perspectives.SummaryDeveloping a systems-based approach to AI decision support involves engaging in a cycle of documenting the system architecture, identifying pain points, developing prototypes, and validating the system. Early efforts have focused on describing process issues to prioritize tasks that would benefit from AI support.

Highlights

  • The demand for kidneys far outpaces supply

  • We are currently engaged in ongoing work to apply a transdisciplinary systems approach to the design and implementation of an Artificial intelligence (AI) decision support system to reduce kidney discard

  • An AI decision support system could support efforts to better leverage real-time data-driven decision-making during this transition toward increased kidney utilization

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Summary

Introduction

The demand for kidneys far outpaces supply. In the USA, nearly 150,000 people are on the waiting list for kidney transplants, but only 24,273 kidneys were transplanted in 2019 [1]. Artificial intelligence (AI) decision support may improve kidney utilization, if effectively designed to support clinician decision-making and provide better real-time access to data-driven predictions. To effectively integrate AI into transplant healthcare, a transdisciplinary systems approach is needed to design and evaluate the use of AI decision support systems in a participatory research framework.

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