A reimbursement framework for artificial intelligence in healthcare

Michael D Abràmoff; Cybil Roehrenbeck; Sylvia Trujillo; Juli Goldstein; Anitra S Graves; Michael X Repka; Ezequiel Zeke Silva Iii

doi:10.1038/s41746-022-00621-w

Back

A reimbursement framework for artificial intelligence in healthcare

Journal article

Open access

A reimbursement framework for artificial intelligence in healthcare

Michael D Abràmoff, Cybil Roehrenbeck, Sylvia Trujillo, Juli Goldstein, Anitra S Graves, Michael X Repka and Ezequiel Zeke Silva Iii

NPJ digital medicine, Vol.5(1), pp.72-72

06/09/2022

DOI: 10.1038/s41746-022-00621-w

PMCID: PMC9184542

PMID: 35681002

Files and links (1)

url

https://doi.org/10.1038/s41746-022-00621-wView

Published (Version of record) Open Access

Abstract

Responsible adoption of healthcare artificial intelligence (AI) requires that AI systems which benefit patients and populations, including autonomous AI systems, are incentivized financially at a consistent and sustainable level. We present a framework for analytically determining value and cost of each unique AI service. The framework’s processes involve affected stakeholders, including patients, providers, legislators, payors, and AI creators, in order to find an optimum balance among ethics, workflow, cost, and value as identified by each of these stakeholders. We use a real world, completed, an example of a specific autonomous AI service, to show how multiple “guardrails” for the AI system implementation enforce ethical principles. It can guide the development of sustainable reimbursement for future AI services, ensuring the quality of care, healthcare equity, and mitigation of potential bias, and thereby contribute to realize the potential of AI to improve clinical outcomes for patients and populations, improve access, remove disparities, and reduce cost.

Details

Title: Subtitle: A reimbursement framework for artificial intelligence in healthcare
Creators: Michael D Abràmoff - Digital Diagnostics, Coralville, IA, USA. michael-abramoff@uiowa.edu
Cybil Roehrenbeck - Hogan Lovells (United States)
Sylvia Trujillo - Ochin
Juli Goldstein - Digital Diagnostics, Coralville, IA, USA
Anitra S Graves - Indiana University
Michael X Repka - Johns Hopkins University
Ezequiel Zeke Silva Iii - University of Texas Health, Long School of Medicine, San Antonio, TX, USA
Resource Type: Journal article
Publication Details: NPJ digital medicine, Vol.5(1), pp.72-72
DOI: 10.1038/s41746-022-00621-w
PMID: 35681002
PMCID: PMC9184542
NLM abbreviation: NPJ Digit Med
eISSN: 2398-6352
Language: English
Date published: 06/09/2022
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Fraternal Order of Eagles Diabetes Research Center; Ophthalmology and Visual Sciences
Record Identifier: 9984267241702771

Metrics

38 Record Views

62 Times Cited - Web of Science

See more details