Learning System for Continuous Professional Education in Low Vision Rehabilitatio

Emerald Education Systems开发了一个针对低视力康复服务提供商的在线继续专业教育学习系统。该CE学习系统包括三个组成部分：1)一套协调的深度在线课程，提供广泛而深入的低视力康复知识基础，以学习者控制的速度使用授课方法教授；2)在线远程监控系统，将临床环境中与低视力患者一起工作的学员的实时视频和音频传输到远程监控和指导学员的导师；以及3)基于网络的多学科学习社区，使低视力康复专业人员能够通过线程论坛和实时聊天进行互动，对发布的临床病例和问题相关文章进行制作和公开评论，并与同事共享资源。目前拟议的第一阶段STTR的目标是将约翰霍普金斯大学低视力康复研究人员的低视力患者调查、数据输入、数据分析和报告算法转移到EES，以开发CE学习系统的第四个组成部分。这第四个部分将审计参与的临床医生对低视力患者的实践，提供关于临床医生个人患者结果的反馈，并将他们的结果与同行和临床研究文献中发表的结果进行比较。第一个目标是开发和优化一种自适应的计算机辅助患者调查，该调查管理互联网上的活动清单，并估计每个患者的六项功能能力衡量标准。第二个目标是开发一个在线患者状态调查和在线临床和实践数据输入系统，该系统与人工智能调查数据和估计的功能能力测量一起，将为每个临床医生创建和存储多维数据超立方体。第三个目标是开发由EES服务器收集和存储的患者数据的标准化报告，临床医生可以下载该报告并将其添加到患者的记录中。第四个目标是开发一个在线分析处理系统，使临床医生能够监测结果，探索和切片他或她的患者的DataCube，执行患者亚组结果分析，并将汇总的结果与他或她的同行的数据或已发表研究的元数据进行比较。第一阶段的目标是在通用公共许可下使用开发良好的开源系统组件来开发这些系统组件的功能原型。第二阶段将开发一个阿尔法原型，它将与CE学习社区内容管理系统集成，并进行一个研究项目，以确定具有审计/反馈/基准的CE学习系统是否会导致实践的变化，从而改善患者的结果。

Emerald Education Systems has developed an online continuing professional education learning system that targets low vision rehabilitation service providers. This CE learning system has three components: 1) a set of coordinated in depth online courses that provide a broad and deep foundation of knowledge on low vision rehabilitation that is delivered using a didactic approach at a learner-controlled pace; 2) an online telementoring system that transmits live video and audio of a mentee working with a low vision patient in a clinical setting to a mentor who remotely monitors and guides the mentee; and 3) a web-based multidisciplinary learning community that enables low vision rehabilitation professionals to interact through threaded forums and live chat, produce and publicly comment on posted clinical cases and issue-related articles, and share resources with colleagues. The presently proposed Phase I STTR has the aim of transferring low vision patient survey, data entry, data analysis, and reporting algorithms from Johns Hopkins low vision rehabilitation researchers to EES to develop a fourth component of the CE learning system. This fourth component will audit participating clinicians' practices with low vision patients, provide feedback on the clinician's individual patient outcomes, and benchmark their outcomes against those of their peers and those published in the clinical research literature. The first aim is to develop and optimize an adaptive computer-assisted patient survey that administers the Activity Inventory over the internet and estimates six functional ability measures on an interval scale for each patient. The second aim is to develop an online patient state survey and online clinical and practice data entry system, which together with the AI survey data and estimated functional ability measures, will create and store a multidimensional data hypercube for each clinician. The third aim is to develop a standardized report of patient data collected by and stored in the EES server that can be downloaded by the clinician and added to the patient's records. The fourth aim is to develop an online analytical processing system that will enable the clinician to monitor outcomes, explore and slice the datacube for his or her patients, perform patient subgroup analyses of outcomes, and compare summarized outcomes to the data of his or her peers or to metadata from published studies. The goal of Phase I is to develop functional prototypes of these system components using well-developed open-source system components under a general public license. Phase II will develop an alpha prototype that will be integrated with the CE learning community content management system and conduct a research project to determine if the CE learning system with audit/feedback/benchmarking leads to changes in practices that result in improved patient outcomes.