Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study

Abstract

Background: The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variability), provides a ripe opportunity for AI-based clinical decision support (CDS). However, AI-CDS for transplant applications must consider important concerns regarding fairness (ie, health equity). The objective of this study was to use human-centered design methods to elicit providers’ perceptions of AI-CDS for liver transplant listing decisions. Methods: In this multicenter qualitative study conducted from December 2020 to July 2021, we performed semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. We used inductive coding and constant comparison analysis of interview data. Results: Analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient’s role in the AI-CDS. Conclusions: Overall, providers interviewed were cautiously optimistic about the potential for AI-CDS to improve clinical and equitable outcomes for patients. These findings can guide multidisciplinary developers in the design and implementation of AI-CDS that deliberately considers health equity.

Should AI allocate livers for transplant? Public attitudes and ethical considerations

“…Empathy was rated as the least important characteristic by our participants. This appears to be consistent with some clinicians’ views that AI’s lack of emotion may be beneficial for the liver transplant evaluation process [ 44 ].…”

“…Further work assessing clinician perceptions of AI in liver allocation would also provide valuable information for the implementation of this technology (for example, it may indicate whether clinicians are likely to follow the allocation indicated by an AI). One recent study suggests US transplant centre clinicians are relatively optimistic about this use of AI [ 44 ].…”

“…Participants were told that decision-makers could possess different characteristics: interpretability, empathy, accuracy, consistency, and impartiality (which were chosen based on discussions amongst authors and are consistent with themes present in the relevant literature [ 44 , 61 , 62 ]). These terms were explained, and respondents were asked to divide a total of 100 points amongst these to indicate their relative importance.…”

“…The ethical status of using AI for medical purposes remains controversial. Some have argued that, as well as improving accuracy, the use of algorithms will also lead to more impartial, consistent, and efficient decision-making [ 4 , 5 , 41 – 44 ]. On the other hand, there is ethical concern about AI bias [ 4 , 45 , 46 ] and that some (non-rule-based) types of AI are a “black box”, i.e., the decision-making process is uninterpretable to the user [ 45 , 47 , 48 ].…”

“…Specific concerns relating to AI in liver allocation have not been systematically explored, nor are the views of the public about this development known. However, a qualitative study of US transplant centre clinicians’ attitudes towards AI in liver allocation identified several key ethical themes in this context, relating to explainability, transparency, fairness, and trustworthiness [ 44 ]. Overall, the study found that clinicians were “cautiously optimistic” about the use of AI in this space.…”