Application of a Data Quality Framework to Ductal Carcinoma In Situ Using Electronic Health Record Data From the All of Us Research Program.

IF 3.3 Q2 ONCOLOGY JCO Clinical Cancer Informatics Pub Date : 2024-08-01 DOI:10.1200/CCI.24.00052

Lew Berman, Yechiam Ostchega, John Giannini, Lakshmi Priya Anandan, Emily Clark, Matthew Spotnitz, Lina Sulieman, Michael Volynski, Andrea Ramirez

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Abstract

Purpose: The specific aims of this paper are to (1) develop and operationalize an electronic health record (EHR) data quality framework, (2) apply the dimensions of the framework to the phenotype and treatment pathways of ductal carcinoma in situ (DCIS) using All of Us Research Program data, and (3) propose and apply a checklist to evaluate the application of the framework.

Methods: We developed a framework of five data quality dimensions (DQD; completeness, concordance, conformance, plausibility, and temporality). Participants signed a consent and Health Insurance Portability and Accountability Act authorization to share EHR data and responded to demographic questions in the Basics questionnaire. We evaluated the internal characteristics of the data and compared data with external benchmarks with descriptive and inferential statistics. We developed a DQD checklist to evaluate concept selection, internal verification, and external validity for each DQD. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) concept ID codes for DCIS were used to select a cohort of 2,209 females 18 years and older.

Results: Using the proposed DQD checklist criteria, (1) concepts were selected and internally verified for conformance; (2) concepts were selected and internally verified for completeness; (3) concepts were selected, internally verified, and externally validated for concordance; (4) concepts were selected, internally verified, and externally validated for plausibility; and (5) concepts were selected, internally verified, and externally validated for temporality.

Conclusion: This assessment and evaluation provided insights into data quality for the DCIS phenotype using EHR data from the All of Us Research Program. The review demonstrates that salient clinical measures can be selected, applied, and operationalized within a conceptual framework and evaluated for fitness for use by applying a proposed checklist.

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利用 "我们所有人 "研究计划的电子健康记录数据，将数据质量框架应用于原位导管癌。

目的：本文的具体目的是：(1) 制定电子健康记录（EHR）数据质量框架并使之可操作化；(2) 利用 "我们所有人 "研究计划数据，将该框架的各个维度应用于乳腺导管原位癌（DCIS）的表型和治疗途径；(3) 提出并应用检查表来评估该框架的应用：我们开发了一个包含五个数据质量维度（DQD；完整性、一致性、连贯性、可信性和时间性）的框架。参与者签署了同意书和《健康保险可携性与责任法案》（Health Insurance Portability and Accountability Act）授权书以共享电子病历数据，并回答了基础知识问卷中的人口统计学问题。我们评估了数据的内部特征，并通过描述性和推论性统计将数据与外部基准进行了比较。我们制定了一份 DQD 核对表，以评估每个 DQD 的概念选择、内部验证和外部有效性。我们使用观察性医疗结果合作组织通用数据模型（OMOP CDM）的DCIS概念ID代码选择了2209名18岁及18岁以上的女性：使用提出的 DQD 核对表标准，(1) 选择了概念，并对其一致性进行了内部验证；(2) 选择了概念，并对其完整性进行了内部验证；(3) 选择了概念，并对其一致性进行了内部验证和外部验证；(4) 选择了概念，并对其合理性进行了内部验证和外部验证；(5) 选择了概念，并对其时间性进行了内部验证和外部验证：本次评估和评价利用 "我们所有人 "研究计划的电子病历数据，对 DCIS 表型的数据质量进行了深入了解。审查表明，可以在概念框架内选择、应用和操作突出的临床措施，并通过应用建议的核对表来评估是否适合使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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