Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions
The integration of Quality Management System (QMS) principles into the life cycle of development, deployment, and utilization of machine learning (ML) and artificial intelligence (AI) technologies within healthcare settings holds the potential to close the AI translation gap by establishing a robust...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-11-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-023-00968-8 |
| _version_ | 1797451383800070144 |
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| author | Shauna M. Overgaard Megan G. Graham Tracey Brereton Michael J. Pencina John D. Halamka David E. Vidal Nicoleta J. Economou-Zavlanos |
| author_facet | Shauna M. Overgaard Megan G. Graham Tracey Brereton Michael J. Pencina John D. Halamka David E. Vidal Nicoleta J. Economou-Zavlanos |
| author_sort | Shauna M. Overgaard |
| collection | DOAJ |
| description | The integration of Quality Management System (QMS) principles into the life cycle of development, deployment, and utilization of machine learning (ML) and artificial intelligence (AI) technologies within healthcare settings holds the potential to close the AI translation gap by establishing a robust framework that accelerates the safe, ethical, and effective delivery of AI/ML in day-to-day patient care. Healthcare organizations (HCOs) can implement these principles effectively by embracing an enterprise QMS analogous to those in regulated industries. By establishing a QMS explicitly tailored to health AI technologies, HCOs can comply with evolving regulations and minimize redundancy and rework while aligning their internal governance practices with their steadfast commitment to scientific rigor and medical excellence. |
| first_indexed | 2024-03-09T14:52:53Z |
| format | Article |
| id | doaj.art-12978f36937843baad12e4f776b42da2 |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-09T14:52:53Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-12978f36937843baad12e4f776b42da22023-11-26T14:19:32ZengNature Portfolionpj Digital Medicine2398-63522023-11-01611510.1038/s41746-023-00968-8Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutionsShauna M. Overgaard0Megan G. Graham1Tracey Brereton2Michael J. Pencina3John D. Halamka4David E. Vidal5Nicoleta J. Economou-Zavlanos6Mayo ClinicMayo ClinicMayo ClinicDuke UniversityMayo ClinicMayo ClinicDuke UniversityThe integration of Quality Management System (QMS) principles into the life cycle of development, deployment, and utilization of machine learning (ML) and artificial intelligence (AI) technologies within healthcare settings holds the potential to close the AI translation gap by establishing a robust framework that accelerates the safe, ethical, and effective delivery of AI/ML in day-to-day patient care. Healthcare organizations (HCOs) can implement these principles effectively by embracing an enterprise QMS analogous to those in regulated industries. By establishing a QMS explicitly tailored to health AI technologies, HCOs can comply with evolving regulations and minimize redundancy and rework while aligning their internal governance practices with their steadfast commitment to scientific rigor and medical excellence.https://doi.org/10.1038/s41746-023-00968-8 |
| spellingShingle | Shauna M. Overgaard Megan G. Graham Tracey Brereton Michael J. Pencina John D. Halamka David E. Vidal Nicoleta J. Economou-Zavlanos Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions npj Digital Medicine |
| title | Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions |
| title_full | Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions |
| title_fullStr | Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions |
| title_full_unstemmed | Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions |
| title_short | Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions |
| title_sort | implementing quality management systems to close the ai translation gap and facilitate safe ethical and effective health ai solutions |
| url | https://doi.org/10.1038/s41746-023-00968-8 |
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