| Title | Generative AI costs in large healthcare systems, an example in revenue cycle. |
| Publication Type | Journal Article |
| Year of Publication | 2025 |
| Authors | Burns ML, Chen S-Y, Tsai C-A, Vandervest J, Pandian B, Nong P, Hanauer DA, Rosenberg A, Platt J |
| Journal | NPJ Digit Med |
| Volume | 8 |
| Issue | 1 |
| Pagination | 579 |
| Date Published | 2025 Sep 30 |
| ISSN | 2398-6352 |
| Abstract | Application of large language models in healthcare continues to expand, specifically for medical free-text classification tasks. While foundation models like those from ChatGPT show potential, alternative models demonstrate superior accuracy and lower costs. This study underscores significant challenges, including computational costs and model reliability. Amidst rising healthcare expenditures and AI's perceived potential to reduce costs, a combination of local and commercial models might offer balanced solutions for healthcare systems. |
| DOI | 10.1038/s41746-025-01971-x |
| Alternate Journal | NPJ Digit Med |
| PubMed ID | 41028226 |
| PubMed Central ID | PMC12485018 |
| Grant List | R01 EB030492 / EB / NIBIB NIH HHS / United States 1-RO1-EB030492 / / National Institutes of Health, The National Institute of Biomedical Imaging and Bioengineering (NIBIB), Public Trust of Artificial Intelligence in the Precision CDS Health Ecosystem / |
