Grootjans Willem, Krainska Uliana, Rezazade Mehrizi Mohammad H
Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Digital Business and Innovation Master, School of Business and Economics, Vrije Universiteit Amsterdam, Almere, The Netherlands.
Eur Radiol. 2025 Jun 3. doi: 10.1007/s00330-025-11672-4.
As many radiology departments embark on adopting artificial intelligence (AI) solutions in their clinical practice, they face the challenge that commercial applications often do not fit with their needs. As a result, they engage in a co-creation process with technology companies to collaboratively develop and implement AI solutions. Despite its importance, the process of co-creating AI solutions is under-researched, particularly regarding the range of challenges that may occur and how medical and technological parties can monitor, assess, and guide their co-creation process through an effective collaboration framework.
Drawing on the multi-case study of three co-creation projects at an academic medical center in the Netherlands, we examine how co-creation processes happen through different scenarios, depending on the extent to which the two parties engage in "resourcing," "adaptation," and "reconfiguration."
We offer a relational framework that helps involved parties monitor, assess, and guide their collaborations in co-creating AI solutions. The framework allows them to discover novel use-cases and reconsider their established assumptions and practices for developing AI solutions, also for redesigning their technological systems, clinical workflow, and their legal and organizational arrangements. Using the proposed framework, we identified distinct co-creation journeys with varying outcomes, which could be mapped onto the framework to diagnose, monitor, and guide collaborations toward desired results.
The outcomes of co-creation can vary widely. The proposed framework enables medical institutions and technology companies to assess challenges and make adjustments. It can assist in steering their collaboration toward desired goals.
Question How can medical institutions and AI startups effectively co-create AI solutions for radiology, ensuring alignment with clinical needs while steering collaboration effectively? Findings This study provides a co-creation framework allowing assessment of project progress, stakeholder engagement, as well as guidelines for radiology departments to steer co-creation of AI. Clinical relevance By actively involving radiology professionals in AI co-creation, this study demonstrates how co-creation helps bridge the gap between clinical needs and AI development, leading to clinically relevant, user-friendly solutions that enhance the radiology workflow.
随着许多放射科在临床实践中开始采用人工智能（AI）解决方案，他们面临着商业应用往往不符合其需求的挑战。因此，他们与科技公司开展共同创造过程，以合作开发和实施人工智能解决方案。尽管其很重要，但人工智能解决方案的共同创造过程研究不足，特别是关于可能出现的挑战范围，以及医疗和技术方如何通过有效的合作框架来监测、评估和指导他们的共同创造过程。
基于荷兰一家学术医疗中心三个共同创造项目的多案例研究，我们研究了共同创造过程如何通过不同场景发生，这取决于双方在“资源配置”“适应”和“重新配置”方面的参与程度。
我们提供了一个关系框架，有助于相关各方在共同创造人工智能解决方案时监测、评估和指导他们的合作。该框架使他们能够发现新的用例，并重新考虑他们既定的开发人工智能解决方案的假设和实践，也用于重新设计他们的技术系统、临床工作流程以及法律和组织安排。使用所提出的框架，我们确定了具有不同结果的不同共同创造历程，这些历程可以映射到该框架上，以诊断、监测和指导合作朝着期望的结果发展。
共同创造的结果可能有很大差异。所提出的框架使医疗机构和科技公司能够评估挑战并进行调整。它可以帮助引导他们的合作朝着期望的目标发展。
问题医疗机构和人工智能初创公司如何有效地共同创造放射学人工智能解决方案，确保与临床需求保持一致，同时有效地引导合作？发现本研究提供了一个共同创造框架，允许评估项目进展、利益相关者参与情况，以及为放射科引导人工智能共同创造的指导方针。临床意义通过让放射科专业人员积极参与人工智能共同创造，本研究展示了共同创造如何有助于弥合临床需求与人工智能开发之间的差距，从而产生增强放射科工作流程的临床相关、用户友好的解决方案。
