Background

Quality indicators (QIs) are being increasingly used in medicine to compare and improve the quality of care delivered. The feasibility of data collection is an important prerequisite for QIs. Information technology can improve efforts to measure processes and outcomes. In intensive care units (ICU), QIs can be automatically measured by exploiting data from clinical information systems (CIS).

Objective

To describe the development and application of a tool to automatically generate a minimum dataset (MDS) and a set of ICU quality metrics from CIS data.

Methods

We used the definitions for MDS and QIs proposed by the Spanish Society of Critical Care Medicine and Coronary Units. Our tool uses an extraction, transform, and load process implemented with Python to extract data stored in various tables in the CIS database and create a new associative database. This new database is uploaded to Qlik Sense, which constructs the MDS and calculates the QIs by applying the required metrics. The tool was tested using data from patients attended in a 30-bed polyvalent ICU during a six-year period.

Results

We describe the definitions and metrics, and we report the MDS and QI measurements obtained through the analysis of 4546 admissions. The results show that our ICU’s performance on the QIs analyzed meets the standards proposed by our national scientific society.

Conclusions

This is the first step toward using a tool to automatically obtain a set of actionable QIs to monitor and improve the quality of care in ICUs, eliminating the need for professionals to enter data manually, thus saving time and ensuring data quality.

中文翻译：

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从重症监护病房的临床信息系统常规收集的数据中自动生成最小数据集和质量指标

背景

质量指标（QIs）越来越多地用于医学中，以比较和改善所提供的护理质量。数据收集的可行性是QI的重要前提。信息技术可以改善衡量过程和结果的努力。在重症监护病房（ICU）中，可以通过利用来自临床信息系统（CIS）的数据来自动测量QI。

目的

描述从CIS数据自动生成最小数据集（MDS）和一组ICU质量指标的工具的开发和应用。

方法

我们使用了西班牙重症监护医学和冠心病学会提出的MDS和QI的定义。我们的工具使用通过Python实现的提取，转换和加载过程来提取存储在CIS数据库中各个表中的数据，并创建一个新的关联数据库。此新数据库将上载到Qlik Sense，Qlik Sense构造MDS并通过应用所需指标来计算QI。使用六年来在30张病床的多价ICU中就诊的患者数据对工具进行了测试。

结果

我们描述了定义和度量标准，并报告了通过对4546个招生的分析获得的MDS和QI测量。结果表明，我们的ICU在所分析的QI方面的表现符合我们国家科学学会提出的标准。

结论

这是使用工具自动获取一组可行的QI来监视和改善ICU的护理质量的第一步，从而消除了专业人员手动输入数据的需要，从而节省了时间并确保了数据质量。