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电子临床质量指标中高影响力数据元素的评估与分层:CancerLinQ®与美国癌症治疗中心的联合数据质量倡议

Assessment and Stratification of High-Impact Data Elements in Electronic Clinical Quality Measures: A Joint Data Quality Initiative Between CancerLinQ® and Cancer Treatment Centers of America.

作者信息

Lettvin Rory J, Wayal Alpna, McNutt Amy, Miller Robert S, Hauser Robert

机构信息

Rory J. Lettvin, Alpna Wayal, Amy McNutt, and Robert S. Miller, American Society of Clinical Oncology, Alexandria, VA; and Robert Hauser, Cancer Treatment Centers of America, Boca Raton, FL.

出版信息

JCO Clin Cancer Inform. 2018 Dec;2:1-10. doi: 10.1200/CCI.17.00139.

Abstract

PURPOSE

A joint data quality initiative between the Cancer Treatment Centers of America and the ASCO big data health technology platform CancerLinQ® was initiated to document and codify the steps taken to evaluate, stratify, and determine the potential effect of data elements used for electronic clinical quality measures as captured within structured fields in electronic health records.

METHODS

The processes involved the identification of clinical concepts required in measure population criteria and then to map these to the corresponding components of the CancerLinQ data model. A quantitative assessment of mappings between electronic clinical quality measure clinical concepts and attributes from the CancerLinQ clinical database was performed. In parallel, a qualitative analysis of high-impact data elements from the Cancer Treatment Centers of America clinical measures was made using local, expert consensus.

RESULTS

An impact assessment was derived using a count of the data elements across measures and the specific population criteria affected.

CONCLUSION

A list of putative high-impact data elements can provide guidance for clinicians to facilitate specific data element capture related to quality metrics in an electronic environment.

摘要

目的

美国癌症治疗中心与美国临床肿瘤学会大数据健康技术平台CancerLinQ®发起了一项联合数据质量倡议,以记录和编纂在电子健康记录的结构化字段中捕获的、用于电子临床质量指标的数据元素的评估、分层及确定其潜在影响的步骤。

方法

这些流程包括识别指标人群标准中所需的临床概念,然后将其映射到CancerLinQ数据模型的相应组件。对电子临床质量指标临床概念与CancerLinQ临床数据库属性之间的映射进行了定量评估。同时,利用当地专家共识对美国癌症治疗中心临床指标中的高影响数据元素进行了定性分析。

结果

通过计算各指标中的数据元素及受影响的特定人群标准得出了影响评估结果。

结论

一份假定的高影响数据元素列表可为临床医生提供指导,以便在电子环境中促进与质量指标相关的特定数据元素的采集。

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