Ethical AI in Health Economics: A transparent model overlaid on a human brain, symbolizing ethical decision-making.

Ethical AI: How to Build Responsible Health Economic Models

Theo Raines in Health & Wellness November 2025 • 4 min read.

"A new framework for transparent, reusable, and updatable health economic software."

In an era dominated by data-driven decisions, health economics relies heavily on computer models to analyze complex systems influencing human health. These models, often implemented as software or Computational Health Economic Models (CHEMs), guide critical decisions on healthcare resource allocation and policy. However, the ethical dimensions of developing and deploying these models are often overlooked.

Traditional health economic research focuses on the conceptual and mathematical underpinnings of models, often neglecting the software implementation. This gap raises significant ethical concerns, as the validity and reliability of these models depend not only on their theoretical soundness but also on how they are implemented and maintained in software.

This article addresses the critical need for ethical guidelines in the development and use of CHEMs. We propose a new framework that encourages transparency, reusability, and updatability (TRU) in health economic model software. By adhering to these principles, developers and funders can ensure that CHEMs are socially responsible, fit for purpose, and beneficial to society.

Why Ethics Matter in Health Economic Modeling

Ethical AI in Health Economics: A transparent model overlaid on a human brain, symbolizing ethical decision-making.

Health economics grapples with allocating scarce resources to maximize health outcomes. The models used in this field are simplified representations of complex systems, and their computational implementations (CHEMs) drive real-world decisions. Ensuring these models are ethically sound is crucial for several reasons:

Value Judgements: CHEMs embed value judgments in their assumptions, feature selections, and evidence standards. These judgments must be transparent and aligned with societal values to avoid biased or unfair outcomes.

Model Validity: Flaws in model design, insufficient validation, and reproducibility issues can undermine the reliability of CHEMs, leading to inaccurate and potentially harmful recommendations.
Software Quality: Poorly implemented software can introduce errors, compromise data integrity, and hinder independent assessment.
Ethical Oversight: A lack of clear ethical guidelines and oversight mechanisms can result in models that perpetuate inequalities or fail to promote social good.

To address these concerns, we propose a set of ethical goals for CHEM developers and funders, grounded in established research ethics principles. These goals span the entire lifecycle of a model, from planning to implementation and release.

A Call to Action: Investing in Ethical CHEMs

Achieving these ethical goals requires a concerted effort from developers, funders, and the broader health economics community. Governments and research institutions should invest in enabling infrastructure, training, and resources to support the development of TRU CHEMs. By prioritizing ethical considerations, we can harness the power of health economic models to improve healthcare decision-making and promote a more equitable and just society. It's about building models that not only provide answers but also reflect our shared values and commitment to the well-being of all.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2403.17798,

Title: Ethical Considerations When Planning, Implementing And Releasing Health Economic Model Software: A New Proposal

Subject: econ.gn q-fin.ec

Authors: Matthew P Hamilton, Caroline Gao, Jonathan Karnon, Luis Salvador-Carulla, Sue M Cotton, Cathrine Mihalopoulos

Published: 25-03-2024

Everything You Need To Know

What is the primary focus of the TRU framework, and how does it improve health economic modeling?

The TRU framework aims to enhance health economic modeling by emphasizing transparency, reusability, and updatability in Computational Health Economic Models (CHEMs). Transparency ensures that the assumptions and processes within the models are clear and understandable. Reusability allows for components of the models to be used in other projects, reducing redundancy and promoting efficiency. Updatability ensures that models can be adapted to reflect new data and insights, maintaining their relevance and accuracy over time. By adhering to the TRU principles, developers and funders can ensure that CHEMs are socially responsible, fit for purpose, and beneficial to society.

Why is software implementation of CHEMs a critical ethical concern?

The software implementation of Computational Health Economic Models (CHEMs) is a critical ethical concern because it directly impacts the validity and reliability of these models. Flaws in software, such as coding errors, can lead to inaccurate results, which can result in poor healthcare decisions. The software's design affects how data is handled, the assumptions included, and the interpretation of the outcomes, which also has ethical implications. Therefore, the quality of software implementation is essential to ensure CHEMs are reliable and aligned with societal values.

What are the key ethical goals proposed for CHEM developers and funders?

The ethical goals proposed for developers and funders of Computational Health Economic Models (CHEMs) span the entire lifecycle of a model, from its initial planning to its final release. These goals promote the creation of models that are transparent, fair, and reliable. These are not explicitly mentioned, but TRU principles are a foundation to achieve those. This means developers must make ethical considerations an integral part of their software's design and maintenance. Funders are responsible for ensuring that they support the development of models that can be trusted to provide accurate, and ethically sound results. Both parties must ensure that the models developed are aligned with societal values and avoid perpetuating inequalities.

How do value judgments influence health economic models, and why is it important to address them?

Value judgments are embedded in various aspects of Computational Health Economic Models (CHEMs), including assumptions, feature selections, and evidence standards. These judgments reflect choices about which factors are most important and how they should be measured, which have a direct impact on the model outcomes. If these value judgments are not transparent and aligned with societal values, the models may lead to biased or unfair outcomes, particularly in how resources are allocated. Addressing them involves making these judgments explicit, ensuring they are justifiable, and considering their potential impacts to promote fairness and equity in healthcare decision-making.

What actions are recommended for the health economics community to ensure ethical AI in healthcare resource allocation?

The health economics community should invest in enabling infrastructure, training, and resources to support the development of transparent, reusable, and updatable Computational Health Economic Models (CHEMs). Governments and research institutions have a role in promoting ethical considerations. Prioritizing these ethical considerations will improve healthcare decision-making and foster a more equitable and just society by building models that reflect shared values and a commitment to the well-being of all. Specifically, the community should embrace and implement the TRU framework.