PubMed:24278828 JSONTXT 4 Projects

An application of cmaps in the description of clinical information structure and logic in electronic health records. The development and implementation of competent and cost-effective computerized medical records that profoundly improve physician productivity and knowledge management will require the development of a new paradigm for the representation and analysis of medical knowledge and logic. Medical knowledge is acquired inductively by observing, measuring, and eliciting information from patients in a process that is investigational rather than transactional. Most, if not all, current approaches to health information technology (HIT) rely on a logic and data structure that imposes significant limitations on the ability of physicians to thoroughly and efficiently document and access empiric patient data because the information is almost invariably organized in a way which presumes, rather than makes explicit, the relationships of concepts and their meaning. Cmapping provides a graphical method of capturing and displaying expert content knowledge that is simple to comprehend and modify and provides a foundation for a dynamic, inductive, and inclusive method of clinical documentation and research. The basis of medical decision analysis along with representative samples of medical knowledge modeling in the Cmap format is presented. The knowledge structures that are captured in Cmaps can be expressed directly in propositional logic, enabling the capability to convert Cmapped clinical expressions to be used to define a description logic for clinical evidence documentation and analysis that can in turn be mapped to multiple natural languages. The described description logic approach can be used to formulate digital messages and documents and to automate the process of converting description specifications formulated in propositional logic into operational electronic health record solutions for capture and reporting of clinical encounters. It has also been demonstrated that using Cmaps to elicit content knowledge from physicians to build point-of-care clinical documentation screens can significantly reduce the time and costs necessary to implement the physician's knowledge into operational systems and that using Cmaps eliminates the need for HIT expertise in the rules-encoding process.开发并执行有效和具备成本效益的 计算机化医疗记录，能够显著提高 医生的工作效率和知识管理水平， 但是，这需要开发用于表述和分析 医学知识和逻辑的全新模式。通过 观察、检测及引导，医生获得患者 信息，并将信息归纳为医学知识， 但是，这是一项调查过程，医生与 患者不存在交互作用。现今多数（ 如果不是全部的话）使用健康信息 技术 (health information technology, HIT) 的方式均依赖于逻辑 和数据结构，这使得医生彻底并有 效地记录和存取以实验为根据的患 者数据受到较大限制，因为信息总 是以假定（而非明确说明）概念及 其含义的关系的方式进行组 织。Cmapping 以图解的方式捕获并 显示专业认知知识，它易于理解和 修改，并为获得动态、归纳和相容 的临床文件编制和研究方法奠定基 础。医疗判定分析以及典型的医学 知识模型化范例均能够以 Cmap 格 式提供。在 Cmap 中捕获的知识结 构，能够以命题逻辑直接表达，并 能够使用转换为 Cmapped 格式的临 床表述，定义临床证据文件编制和 分析的描述逻辑，并可依次映射为 多种自然语言。上述描述性逻辑方 法可用于公式化数字讯息和文件， 并自动化将用命题逻辑公式表示的 描述规格转换为可用的电子健康记 录解决方案以捕获并报告临床发现 的程序。经证实，使用 Cmap 推导 医生的认知知识，以建立医护点临 床文献筛选机制，可有效减少将医 生的知识纳入工作系统所需的时间 和成本，并可使用 Cmap，消除规则 编写过程对 HIT 专业知识的需求。