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利用电子病历中的结构化临床文档进行睡眠医学的质量改进和基于实践的研究。

Quality improvement and practice-based research in sleep medicine using structured clinical documentation in the electronic medical record.

作者信息

Maraganore Demetrius M, Freedom Thomas, Simon Kelly Claire, Lovitz Lori E, Musleh Camelia, Munson Richard, Nasir Nabeela, Patel Smita, Paul Joya, Viola-Saltzman Mari, Meyers Steven, Chesis Richard, Hillman Laura, Tideman Samuel, Pham Anna, Vazquez Rosa Maria, Frigerio Roberta

机构信息

Department of Neurology, NorthShore University HealthSystem, 2650 Ridge Ave, Evanston, IL 60201, USA.

Department of Neurology, University of Florida, 1149 Newell Drive, Gainesville, FL 32611, USA.

出版信息

Sleep Sci Pract. 2020 Jan 2;4:1. doi: 10.1186/s41606-019-0038-2.

Abstract

BACKGROUND

We developed and implemented a structured clinical documentation support (SCDS) toolkit within the electronic medical record, to optimize patient care, facilitate documentation, and capture data at office visits in a sleep medicine/neurology clinic for patient care and research collaboration internally and with other centers.

METHODS

To build our SCDS toolkit, physicians met frequently to develop content, define the cohort, select outcome measures, and delineate factors known to modify disease progression. We assigned tasks to the care team and mapped data elements to the progress note. Programmer analysts built and tested the SCDS toolkit, which included several score tests. Auto scored and interpreted tests included the Generalized Anxiety Disorder 7-item, Center for Epidemiological Studies Depression Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Insomnia Severity Index, and the International Restless Legs Syndrome Study Group Rating Scale. The SCDS toolkits also provided clinical decision support (untreated anxiety or depression) and prompted enrollment of patients in a DNA biobank.

RESULTS

The structured clinical documentation toolkit captures hundreds of fields of discrete data at each office visit. This data can be displayed in tables or graphical form. Best practice advisories within the toolkit alert physicians when a quality improvement opportunity exists. As of May 1, 2019, we have used the toolkit to evaluate 18,105 sleep patients at initial visit. We are also collecting longitudinal data on patients who return for annual visits using the standardized toolkits. We provide a description of our development process and screenshots of our toolkits.

CONCLUSIONS

The electronic medical record can be structured to standardize Sleep Medicine office visits, capture data, and support multicenter quality improvement and practice-based research initiatives for sleep patients at the point of care.

摘要

背景

我们在电子病历中开发并实施了一个结构化临床文档支持(SCDS)工具包,以优化患者护理、促进文档记录,并在睡眠医学/神经科诊所的门诊就诊时收集数据,用于内部患者护理以及与其他中心的研究合作。

方法

为构建我们的SCDS工具包,医生们频繁会面以开发内容、定义队列、选择结局指标,并确定已知可改变疾病进展的因素。我们将任务分配给护理团队,并将数据元素映射到病程记录中。程序员分析师构建并测试了SCDS工具包,其中包括多项评分测试。自动评分和解读的测试包括广泛性焦虑障碍7项量表、流行病学研究中心抑郁量表、爱泼华嗜睡量表、匹兹堡睡眠质量指数、失眠严重程度指数以及国际不宁腿综合征研究组评分量表。SCDS工具包还提供临床决策支持(未治疗的焦虑或抑郁),并促使患者加入DNA生物样本库。

结果

结构化临床文档工具包在每次门诊就诊时捕获数百个离散数据字段。这些数据可以以表格或图形形式显示。当存在质量改进机会时,工具包内的最佳实践建议会提醒医生。截至2019年5月1日,我们已使用该工具包对18105名睡眠患者进行了初诊评估。我们还在使用标准化工具包收集复诊患者的纵向数据。我们提供了开发过程的描述以及工具包的屏幕截图。

结论

电子病历可以进行结构化,以规范睡眠医学门诊就诊、收集数据,并在护理点支持针对睡眠患者的多中心质量改进和基于实践的研究计划。

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