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Diffusion Dynamics of Radiology IT -Systems in German Hospitals -A Bayesian Bass Model

机译:德国医院放射学的扩散动态-A贝叶斯低音模型

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Radiology has a reputation for having a high affinity to innovation -particularly with regard to information technologies. Designed for supporting the peculiarities of radiological diagnostic workflows, Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (PACS) developed into widely used information systems in hospitals and form the basis for advancing the field towards automated image diagnostics. RIS and PACS can thus serve as meaningful indicators of how quickly IT innovations diffuse in secondary care settings - an issue that requires increased attention in research and health policy in the light of increasingly fast innovation cycles. We therefore conducted a retrospective longitudinal observational study to research the diffusion dynamics of RIS and PACS in German hospitals between 2005 and 2017. Based upon data points collected within the “IT Report Healthcare” and building on Rogers’ Diffusion of Innovation (DOI) theory, we applied a novel methodological technique by fitting Bayesian Bass Diffusion Models on past adoption rates. The Bass models showed acceptable goodness of fit to the data and the results indicated similar growth rates of RIS and PACS implementations and suggest that market saturation is almost reached. Adoption rates of PACS showed a slightly higher coefficient of imitation (q = 0.25) compared to RIS (q = 0.11). However, the diffusion process expands over approximately two decades for both systems which points at the need for further research into how innovation diffusion can be accelerated effectively. Furthermore, the Bayesian approach to Bass modelling showed to have several advantages over the classical frequentists approaches and should encourage adoption and diffusion research to adapt similar techniques.
机译:放射学具有良好的对创新的声誉 - 在关于信息技术方面具有高度亲和力。设计用于支持放射性诊断工作流程的特性,放射信息系统(RIS)和图片归档和通信系统(PAC)在医院广泛使用的信息系统中开发,并构成了推进现场实现自动图像诊断的基础。因此,RIS和PACS可以作为IT创新在二级护理环境中漫步的迅速的有意义指标 - 这是一个问题,需要在越来越快的创新周期的范围内需要增加研究和健康政策的关注。因此,我们进行了回顾性的纵向观察研究,研究了2005年至2017年德国医院RIS和PACS的扩散动态。根据“IT报告医疗保健”和罗杰斯的创新(DOI)理论的扩散,基于数据点,我们通过拟合过去采用率的贝叶斯低音扩散模型应用了一种新颖的方法技术。低音模型显示适合数据的可接受的善良,结果表明RIS和PACS实施的类似增长,并表明市场饱和度几乎达到了。与RIS相比,PAC的采用率显示出略微较高的模仿系数(Q = 0.25)(Q = 0.11)。然而,扩散过程扩展到两十年来,两个系统都需要进一步研究创新扩散如何有效地加速。此外,贝叶斯建模的贝叶斯途径表明,在古典频繁的思想方法上有几个优势,并鼓励采用和扩散研究适应类似的技术。

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