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实施数据准确性计划,以提高 Axon 注册表®中的数据提取产量。

Implementation of a data accuracy plan to improve data extraction yield in the Axon Registry®.

机构信息

From the NeuroDevelopmental Science Center (M.C.C.V.), Akron Children's Hospital, OH; American Academy of Neurology (K.L., M.J.-G., A.B., B.M.), Minneapolis, MN; FIGmd Inc (A.D.), Rockford, IL; and Department of Neurology (L.K.J.), Mayo Clinic, Rochester, MN.

出版信息

Neurology. 2020 Jul 21;95(3):e310-e319. doi: 10.1212/WNL.0000000000009884. Epub 2020 Jun 26.

Abstract

OBJECTIVE

To conduct a data quality improvement project to improve the quality measure data mapping and to measure key phrase logic in the Axon Registry.® METHODS: Prior validation analysis of the Axon Registry identified 2 main areas for remediation: methodology for mapping data from electronic health record (EHR) into the registry clinical data record (CDR) and key phrase logic for each measure. Practice groups participating in Axon Registry and 6 Axon Registry quality measures were selected for intervention. Mapping of measure elements and measure performances for each of the selected measures and practices were reviewed before intervention. The Data Accuracy Plan (DAP) was performed, and documentation data and visit data counts and data yield after intervention were calculated and analyzed.

RESULTS

Documentation data and visit data counts and data yield increased for all 6 quality measures and all practices in the DAP. Increase in documentation data count ranged from 815 to 15,782 occurrences, while visit data count increase ranged from 519 to 16,383 visits. Average data yield range was 7.22% to 33.46% before intervention and increased to a range from 15.34% to 74.40% after intervention.

CONCLUSION

There was substantial improvement in the accuracy of data extraction for quality measure elements after intervention to improve methodology for mapping EHR data into CDR and key phrase logic. Implementation of changes and continued review of data mapping and data dictionary are important to ensure accurate measure performance and to improve reliability and validity of Axon Registry data.

摘要

目的

开展数据质量改进项目,以提高质量衡量标准数据映射的质量,并衡量 Axon Registry®中的关键短语逻辑。

方法

Axon Registry 的预先验证分析确定了需要修复的 2 个主要领域:将电子健康记录(EHR)中的数据映射到注册临床数据记录(CDR)的方法,以及每个衡量标准的关键短语逻辑。选择参与 Axon Registry 的实践小组和 6 个 Axon Registry 质量衡量标准进行干预。在干预之前,对选定的衡量标准和实践中的每个衡量标准元素和衡量标准表现进行了映射审查。执行数据准确性计划(DAP),并计算和分析干预后的文档数据和访问数据计数以及数据产量。

结果

在 DAP 中,所有 6 个质量衡量标准和所有实践的文档数据和访问数据计数以及数据产量都有所增加。文档数据计数的增加范围从 815 到 15782 次,而访问数据计数的增加范围从 519 到 16383 次。干预前的平均数据产量范围为 7.22%至 33.46%,干预后增加到 15.34%至 74.40%的范围。

结论

通过干预,在将 EHR 数据映射到 CDR 和关键短语逻辑的方法方面,质量衡量标准元素的数据提取准确性得到了显著提高。更改的实施和对数据映射和数据字典的持续审查对于确保衡量标准性能的准确性以及提高 Axon Registry 数据的可靠性和有效性非常重要。

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