Lytle Kay S, Westra Bonnie L, Whittenburg Luann, Adams Mischa, Akre Mari, Ali Samira, Furukawa Meg, Hartleben Stephanie, Hook Mary, Johnson Steven G, Settergren Theresa Tess, Thibodeaux Mariaelena
Alpha Alpha & Beta Nu, Chief Nursing Information Officer, Duke University Health System, Durham, NC, USA.
Associate Professor Emerita, School of Nursing, University of Minnesota, Minneapolis, MN, USA.
J Nurs Scholarsh. 2021 May;53(3):306-314. doi: 10.1111/jnu.12646. Epub 2021 Mar 15.
The rapid implementation of electronic health records (EHRs) resulted in a lack of data standardization and created considerable difficulty for secondary use of EHR documentation data within and between organizations. While EHRs contain documentation data (input), nurses and healthcare organizations rarely have useable documentation data (output). The purpose of this article is to describe a method of standardizing EHR flowsheet documentation data using information models (IMs) to support exchange, quality improvement, and big data research. As an exemplar, EHR flowsheet metadata (input) from multiple organizations was used to validate a fall prevention IM.
A consensus-based, qualitative, descriptive approach was used to identify a minimum set of essential fall prevention data concepts documented by staff nurses in acute care. The goal was to increase generalizable and comparable nurse-sensitive data on the prevention of falls across organizations for big data research.
The research team conducted a retrospective, observational study using an iterative, consensus-based approach to map, analyze, and evaluate nursing flowsheet metadata contributed by eight health systems. The team used FloMap software to aggregate flowsheet data across organizations for mapping and comparison of data to a reference IM. The FloMap analysis was refined with input from staff nurse subject matter experts, review of published evidence, current documentation standards, Magnet Recognition nursing standards, and informal fall prevention nursing use cases.
Flowsheet metadata analyzed from the EHR systems represented 6.6 million patients, 27 million encounters, and 683 million observations. Compared to the original reference IM, five new IM classes were added, concepts were reduced by 14 (from 57 to 43), and 157 value set items were added. The final fall prevention IM incorporated 11 condition or age-specific fall risk screening tools and a fall event details class with 14 concepts.
The iterative, consensus-based refinement and validation of the fall prevention IM from actual EHR fall prevention flowsheet documentation contributes to the ability to semantically exchange and compare fall prevention data across multiple health systems and organizations. This method and approach provides a process for standardizing flowsheet data as coded data for information exchange and use in big data research.
Opportunities exist to work with EHR vendors and the Office of the National Coordinator for Health Information Technology to implement standardized IMs within EHRs to expand interoperability of nurse-sensitive data.
电子健康记录（EHR）的迅速实施导致数据缺乏标准化，给组织内部及组织之间二次使用EHR文档数据带来了相当大的困难。虽然EHR包含文档数据（输入），但护士和医疗保健组织很少拥有可用的文档数据（输出）。本文的目的是描述一种使用信息模型（IM）来标准化EHR流程表文档数据的方法，以支持数据交换、质量改进和大数据研究。作为一个示例，来自多个组织的EHR流程表元数据（输入）被用于验证一个预防跌倒IM。
采用基于共识的定性描述方法，以确定急症护理中注册护士记录的预防跌倒基本数据概念的最小集合。目标是增加可推广和可比的护士敏感数据，用于跨组织的预防跌倒大数据研究。
研究团队采用回顾性观察研究，使用基于共识的迭代方法来映射、分析和评估八个卫生系统提供的护理流程表元数据。该团队使用FloMap软件汇总各组织的流程表数据，以便将数据映射并与参考IM进行比较。FloMap分析在注册护士主题专家的意见、已发表证据的审查、当前文档标准、磁体识别护理标准以及预防跌倒护理非正式用例的基础上进行了完善。
从EHR系统分析的流程表元数据代表了660万患者、2700万次就诊和6.83亿条观察记录。与原始参考IM相比，增加了五个新的IM类，概念减少了14个（从57个减至43个），并增加了157个值集项目。最终的预防跌倒IM纳入了11种针对特定病情或年龄的跌倒风险筛查工具以及一个包含14个概念的跌倒事件详细信息类。
基于共识从实际EHR预防跌倒流程表文档中对预防跌倒IM进行迭代完善和验证，有助于跨多个卫生系统和组织进行预防跌倒数据的语义交换和比较。这种方法和途径提供了一个将流程表数据标准化为编码数据以用于信息交换和大数据研究的过程。
存在与EHR供应商和国家卫生信息技术协调办公室合作在EHR中实施标准化IM的机会，以扩大护士敏感数据的互操作性。
