An early pipeline framework for assessing vendor AI solutions to support return on investment
Abstract The success of AI solutions in health systems depends on governance from use case inception through deployment and auditing. This proposed early pipeline governance framework for vendor AI solutions highlights a four-pronged approach: strategic alignment, executive sponsorship, impact and v...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01767-z |
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| _version_ | 1850207478233432064 |
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| author | Charles E. Binkley David Bouslov Ali Zaidi Lauren Kaye Ralph Whalen Sameer Sethi Jose Azar |
| author_facet | Charles E. Binkley David Bouslov Ali Zaidi Lauren Kaye Ralph Whalen Sameer Sethi Jose Azar |
| author_sort | Charles E. Binkley |
| collection | DOAJ |
| description | Abstract The success of AI solutions in health systems depends on governance from use case inception through deployment and auditing. This proposed early pipeline governance framework for vendor AI solutions highlights a four-pronged approach: strategic alignment, executive sponsorship, impact and value case assessment, and risk assessment. Each component can be scaled to health systems of any size and the risk and impact assessments can take place simultaneously or sequentially. |
| format | Article |
| id | doaj-art-f00ca4e66be24ce993b3baeec5b106d6 |
| institution | OA Journals |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-f00ca4e66be24ce993b3baeec5b106d62025-08-20T02:10:31ZengNature Portfolionpj Digital Medicine2398-63522025-06-01811710.1038/s41746-025-01767-zAn early pipeline framework for assessing vendor AI solutions to support return on investmentCharles E. Binkley0David Bouslov1Ali Zaidi2Lauren Kaye3Ralph Whalen4Sameer Sethi5Jose Azar6Hackensack Meridian HealthHackensack Meridian School of MedicineHackensack Meridian School of MedicineHackensack Meridian HealthHackensack Meridian HealthHackensack Meridian HealthHackensack Meridian HealthAbstract The success of AI solutions in health systems depends on governance from use case inception through deployment and auditing. This proposed early pipeline governance framework for vendor AI solutions highlights a four-pronged approach: strategic alignment, executive sponsorship, impact and value case assessment, and risk assessment. Each component can be scaled to health systems of any size and the risk and impact assessments can take place simultaneously or sequentially.https://doi.org/10.1038/s41746-025-01767-z |
| spellingShingle | Charles E. Binkley David Bouslov Ali Zaidi Lauren Kaye Ralph Whalen Sameer Sethi Jose Azar An early pipeline framework for assessing vendor AI solutions to support return on investment npj Digital Medicine |
| title | An early pipeline framework for assessing vendor AI solutions to support return on investment |
| title_full | An early pipeline framework for assessing vendor AI solutions to support return on investment |
| title_fullStr | An early pipeline framework for assessing vendor AI solutions to support return on investment |
| title_full_unstemmed | An early pipeline framework for assessing vendor AI solutions to support return on investment |
| title_short | An early pipeline framework for assessing vendor AI solutions to support return on investment |
| title_sort | early pipeline framework for assessing vendor ai solutions to support return on investment |
| url | https://doi.org/10.1038/s41746-025-01767-z |
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