Towards machine learning for moral choice analysis in health economics

Towards machine learning for moral choice analysis in health economics: A literature review and research agenda

Smeele, Nicholas V.R. (Erasmus Universiteit Rotterdam)
Chorus, C.G. (TU Delft Industrial Design Engineering)
Schermer, Maartje H.N. (Erasmus MC)
de Bekker-Grob, Esther W. (Erasmus Universiteit Rotterdam)

Industrial Design Engineering

2023

Background: Discrete choice models (DCMs) for moral choice analysis will likely lead to erroneous model outcomes and misguided policy recommendations, as only some characteristics of moral decision-making are considered. Machine learning (ML) is recently gaining interest in the field of discrete choice modelling. This paper explores the potential of combining DCMs and ML to study moral decision-making more accurately and better inform policy decisions in healthcare. Methods: An interdisciplinary literature search across four databases – PubMed, Scopus, Web of Science, and Arxiv – was conducted to gather papers. Based on the Preferred Reporting Items for Systematic and Meta-analyses (PRISMA) guideline, studies were screened for eligibility on inclusion criteria and extracted attributes from eligible papers. Of the 6285 articles, we included 277 studies. Results: DCMs have shortcomings in studying moral decision-making. Whilst the DCMs' mathematical elegance and behavioural appeal hold clear interpretations, the models do not account for the ‘moral’ cost and benefit in an individual's utility calculation. The literature showed that ML obtains higher predictive power, model flexibility, and ability to handle large and unstructured datasets. Combining the strengths of ML methods with DCMs has the potential for studying moral decision-making. Conclusions: By providing a research agenda, this paper highlights that ML has clear potential to i) find and deepen the utility specification of DCMs, and ii) enrich the insights extracted from DCMs by considering the intrapersonal determinants of moral decision-making.

Discrete choice models
Health preference research
Literature review
Machine learning
Moral decision-making
Moral preferences
Research agenda

http://resolver.tudelft.nl/uuid:ef493877-34d0-40a2-89b9-991a4204d947

https://doi.org/10.1016/j.socscimed.2023.115910

0277-9536

Social Science & Medicine, 326

Institutional Repository

review

© 2023 Nicholas V.R. Smeele, C.G. Chorus, Maartje H.N. Schermer, Esther W. de Bekker-Grob