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

Author:

Berman Lew1ORCID,Ostchega Yechiam1ORCID,Giannini John1ORCID,Anandan Lakshmi Priya2ORCID,Clark Emily2ORCID,Spotnitz Matthew1ORCID,Sulieman Lina3,Volynski Michael4,Ramirez Andrea1ORCID

Affiliation:

1. National Institutes of Health, All of Us Research Program, Bethesda, MD

2. Leidos, Frederick, MD

3. Vanderbilt University Medical Center, Nashville, TN

4. InfoPro Systems, Rockville, MD

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.

Publisher

American Society of Clinical Oncology (ASCO)

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