Almashmoum Maryam, Cunningham James, Ainsworth John
Division of Informatics Imaging and Data Sciences, School of Health Sciences Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, United Kingdom.
Nuclear Medicine Department, Faisal Sultan Bin Eissa, Kuwait Cancer Control Center, Kuwait city, Kuwait.
JMIR Hum Factors. 2025 May 6;12:e54484. doi: 10.2196/54484.
Knowledge sharing in medical imaging departments is driven by the need to improve health care services, develop health care professionals' skills, and reduce repetitive mistakes. It is considered an important step in the implementation of knowledge management solutions. By following a maturity model of knowledge sharing, knowledge-sharing practices can be improved.
This study aimed to develop a maturity model for knowledge sharing in the medical imaging department to help managers to assess the level of maturity of knowledge-sharing practices. In modern health care institutions, improvements in health care professionals' skills and health care services are often driven through practicing knowledge-sharing behaviors. Managers can follow the indicators of maturity model of knowledge sharing and its measurements to identify the current level and move to the next level.
This study was conducted in 4 stages: an overview stage that highlighted the factors that affect knowledge-sharing practices in medical imaging departments; an analysis factor stage that was designed to assess the factors that affect knowledge sharing using a concurrent mixed methods approach (questionnaires and semistructured interviews) in 2 medical imaging departments; a structuring maturity model knowledge sharing stage, where a maturity model of knowledge sharing was developed based on the findings of the first and second stages; and finally, an assessment of reliability and validity stage, where a modified Delphi method was used to obtain consensus among experts on model components to be ready for implantation.
The model presented in this study includes 17 indicators, divided into 11 components. Those components were derived from the findings of the questionnaires and semistructured interviews that were applied in the medical imaging departments. It consisted of 5 maturity levels: initial, aware, defined, managed, and optimized. In each level, measurements were included to help managers assess the current level by answering the questions. On the basis of reliability, the experts reached a consensus agreement on the model's components in 2 rounds with SD <1.
This maturity model of knowledge sharing in medical imaging departments allows managers and policy makers to measure the maturity level of knowledge sharing in those departments. Although the model has been applied to medical imaging departments, it could easily be modified for application in other institutions.
医学影像科室的知识共享是由改善医疗服务、提升医护人员技能以及减少重复性错误的需求所驱动的。它被视为实施知识管理解决方案的重要一步。通过遵循知识共享的成熟度模型，可以改进知识共享实践。
本研究旨在开发一种医学影像科室知识共享的成熟度模型，以帮助管理人员评估知识共享实践的成熟度水平。在现代医疗机构中，医护人员技能和医疗服务的提升通常是通过践行知识共享行为来推动的。管理人员可以依据知识共享成熟度模型的指标及其衡量方法来确定当前水平并迈向更高水平。
本研究分四个阶段进行：概述阶段，突出影响医学影像科室知识共享实践的因素；分析因素阶段，旨在通过在两个医学影像科室采用问卷调查和半结构化访谈相结合的混合方法来评估影响知识共享的因素；构建知识共享成熟度模型阶段，根据第一和第二阶段的研究结果开发知识共享成熟度模型；最后是可靠性和有效性评估阶段，采用改进的德尔菲法在专家之间就模型组件达成共识，以便准备实施。
本研究提出的模型包括17项指标，分为11个组件。这些组件源自医学影像科室问卷调查和半结构化访谈的结果。它由5个成熟度级别组成：初始级、知晓级、定义级、管理级和优化级。在每个级别中都包含了衡量标准，以帮助管理人员通过回答问题来评估当前水平。基于可靠性，专家们在两轮讨论中就模型组件达成了共识，标准差<1。
这种医学影像科室知识共享成熟度模型使管理人员和政策制定者能够衡量这些科室知识共享的成熟度水平。尽管该模型已应用于医学影像科室，但它可以很容易地进行修改以应用于其他机构。
