Governance of Clinical AI applications to facilitate safe and equitable deployment in a large health system: Key elements and early successes.
Governance of Clinical AI applications to facilitate safe and equitable deployment in a large health system: Key elements and early successes.
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DOI：
10.3389/fdgth.2022.931439
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发表时间：
2022
影响因子：
--
通讯作者：
Patterson, Brian W.
中科院分区：
文献类型：
--
作者：
Liao, Frank;Adelaine, Sabrina;Afshar, Majid;Patterson, Brian W.
在医疗保健领域成功部署和有意义地采用人工智能的关键挑战之一是人工智能应用程序的卫生系统级治理。这种治理不仅对于患者安全和卫生系统的问责至关重要，而且对于培养临床医生的信任以提高采用率并促进有意义的健康结果至关重要。在本案例研究中，我们描述了威斯康星大学健康分校 (UWH) 的此类治理结构的发展情况，该结构通过安全部署和持续监控有效性来对人工智能应用程序进行监督，从有效性和用户可接受性评估到安全部署。我们的结构利用多学科指导委员会和特定项目的小组委员会。委员会成员制定了涵盖信息学、数据科学、临床操作、道德和公平的多利益相关者视角。我们的结构包括指导原则，为人工智能应用程序的初始部署和持续使用的认可提供切实的参数。该委员会的任务是确保所有申请的可解释性、准确性和公平性原则。为了落实这些原则，我们提供了一个价值流，以在临床实施的不同阶段应用人工智能治理原则。这种结构使得人工智能应用程序能够有效地应用于临床。有效的治理带来了几个成果：（1）清晰的监督和认可制度结构； (2) 成功部署的路径，包括技术、临床和操作方面的考虑； (3) 持续监测的流程，以确保随着临床实践和疾病流行的发展，解决方案仍然可以接受； (4) 纳入人工智能应用的道德和公平使用指南。
One of the key challenges in successful deployment and meaningful adoption of AI in healthcare is health system-level governance of AI applications. Such governance is critical not only for patient safety and accountability by a health system, but to foster clinician trust to improve adoption and facilitate meaningful health outcomes. In this case study, we describe the development of such a governance structure at University of Wisconsin Health (UWH) that provides oversight of AI applications from assessment of validity and user acceptability through safe deployment with continuous monitoring for effectiveness. Our structure leverages a multi-disciplinary steering committee along with project specific sub-committees. Members of the committee formulate a multi-stakeholder perspective spanning informatics, data science, clinical operations, ethics, and equity. Our structure includes guiding principles that provide tangible parameters for endorsement of both initial deployment and ongoing usage of AI applications. The committee is tasked with ensuring principles of interpretability, accuracy, and fairness across all applications. To operationalize these principles, we provide a value stream to apply the principles of AI governance at different stages of clinical implementation. This structure has enabled effective clinical adoption of AI applications. Effective governance has provided several outcomes: (1) a clear and institutional structure for oversight and endorsement; (2) a path towards successful deployment that encompasses technologic, clinical, and operational, considerations; (3) a process for ongoing monitoring to ensure the solution remains acceptable as clinical practice and disease prevalence evolve; (4) incorporation of guidelines for the ethical and equitable use of AI applications.
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影响因子：
8.8
作者：
Churpek, Matthew M.;Yuen, Trevor C.;Edelson, Dana P.
通讯作者：
Edelson, Dana P.
影响因子：
3
作者：
Patterson, Brian W.;Engstrom, Collin J.;Shah, Manish N.
通讯作者：
Shah, Manish N.
DOI：
10.1016/j.hjdsi.2021.100598
发表时间：
2022-03
期刊：
Healthcare (Amsterdam, Netherlands)
影响因子：
--
作者：
Jacobsohn GC;Leaf M;Liao F;Maru AP;Engstrom CJ;Salwei ME;Pankratz GT;Eastman A;Carayon P;Wiegmann DA;Galang JS;Smith MA;Shah MN;Patterson BW
通讯作者：
Patterson BW
影响因子：
15.2
作者：
Marwaha JS;Landman AB;Brat GA;Dunn T;Gordon WJ
通讯作者：
Gordon WJ
影响因子：
19.7
作者：
Zhang R;Tie X;Qi Z;Bevins NB;Zhang C;Griner D;Song TK;Nadig JD;Schiebler ML;Garrett JW;Li K;Reeder SB;Chen GH
通讯作者：
Chen GH