Development and Preliminary Testing of Health Equity Across the AI Lifecycle (HEAAL): A Framework for Healthcare Delivery Organizations to Mitigate the Risk of AI Solutions Worsening Health Inequities

Overview

Journal PLOS Digit Health

Date 2024 May 9

PMID 38723025

Authors

Jee Young Kim

Alifia Hasan

Katherine C Kellogg

William Ratliff

Sara G Murray

Harini Suresh

Alexandra Valladares

Keo Shaw

Danny Tobey

David E Vidal

Mark A Lifson

Manesh Patel

Inioluwa Deborah Raji

Michael Gao

William Knechtle

Linda Tang

Suresh Balu

Mark P Sendak

Affiliations

Soon will be listed here.

Abstract

The use of data-driven technologies such as Artificial Intelligence (AI) and Machine Learning (ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced regulatory frameworks, accountability measures, and governance standards to ensure safe, effective, and equitable use. To address these gaps and tackle a common challenge faced by healthcare delivery organizations, a case-based workshop was organized, and a framework was developed to evaluate the potential impact of implementing an AI solution on health equity. The Health Equity Across the AI Lifecycle (HEAAL) is co-designed with extensive engagement of clinical, operational, technical, and regulatory leaders across healthcare delivery organizations and ecosystem partners in the US. It assesses 5 equity assessment domains-accountability, fairness, fitness for purpose, reliability and validity, and transparency-across the span of eight key decision points in the AI adoption lifecycle. It is a process-oriented framework containing 37 step-by-step procedures for evaluating an existing AI solution and 34 procedures for evaluating a new AI solution in total. Within each procedure, it identifies relevant key stakeholders and data sources used to conduct the procedure. HEAAL guides how healthcare delivery organizations may mitigate the potential risk of AI solutions worsening health inequities. It also informs how much resources and support are required to assess the potential impact of AI solutions on health inequities.

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