An electronic health record based on structured narrative
An electronic health record based on structured narrative
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DOI：
10.1197/jamia.m2131
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发表时间：
2008-01-01
影响因子：
6.4
通讯作者：
Stetson, Peter
中科院分区：
文献类型：
--
作者：
Johnson, Stephen B.;Bakken, Suzanne;Stetson, Peter
目标：开发一种电子健康记录，有助于快速捕获临床医生的详细叙述观察结果，并对叙述信息进行部分结构化以便集成和重用。设计：我们提出了一种设计，将非结构化文本和编码数据融合成一个称为结构化叙述的单一模型。每个主要临床事件（例如，遭遇或手术）都被表示为一个文档，该文档经过标记以识别总体结构（部分、字段、段落、列表）以及句子内的精细结构（概念、修饰语、关系）。标记的项目与标准化代码相关联，这些标准化代码能够链接到其他事件以及有效地重用信息，这可以加快临床医生的数据输入速度。自然语言处理用于识别精细结构，这可以减少基于表单的输入的需要。验证：通过临床医生的使用示例验证模型，并讨论用户界面、数据结构和处理规则的相关方面。讨论：所提出的模型将所有患者信息表示为具有标准化总体结构（模板）的文档。临床医生以自由文本形式输入数据，这些数据通过自然语言处理实时编码，使其可立即用于其他计算，例如警报或评论。此外，叙述数据通过时间关系、严重性和程度修饰符、因果关系、临床解释和基本原理来注释和增强结构化数据。结论：结构化叙述有潜力通过允许表达自由、提供即时反馈、支持临床信息的重用以及为后续处理（例如质量保证和临床研究）构建数据来促进直接从临床医生获取数据。
Objective: To develop an electronic health record that facilitates rapid capture of detailed narrative observations from clinicians, with partial structuring of narrative information for integration and reuse.Design: We propose a design in which unstructured text and coded data are fused into a single model called structured narrative. Each major clinical event (e.g., encounter or procedure) is represented as a document that is marked up to identify gross structure (sections, fields, paragraphs, lists) as well as fine structure within sentences (concepts, modifiers, relationships). Marked up items are associated with standardized codes that enable linkage to other events, as well as efficient reuse of information, which can speed up data entry by clinicians. Natural language processing is used to identify fine structure, which can reduce the need for form-based entry.Validation: The model is validated through an example of use by a clinician, with discussion of relevant aspects of the user interface, data structures and processing rules.Discussion: The proposed model represents all patient information as documents with standardized gross structure (templates). Clinicians enter their data as free text, which is coded by natural language processing in real time making it immediately usable for other computation, such as alerts or critiques. In addition, the narrative data annotates and augments structured data with temporal relations, severity and degree modifiers, causal connections, clinical explanations and rationale.Conclusion: Structured narrative has potential to facilitate capture of data directly from clinicians by allowing freedom of expression, giving immediate feedback, supporting reuse of clinical information and structuring data for subsequent processing, such as quality assurance and clinical research.