Low frequency of structured documentation for cancer genetic testing in a large electronic health record dataset: A brief report using All of Us Research data.

Annually, over two million individuals in the United States are diagnosed with cancer, with 10–20% attributed to hereditary cancer syndromes. Genetic testing for pathogenic variants is a standard component of cancer care guided by tumor pathology and family history. Despite this, access to and compl...

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Publicado en:Journal of Genetic Counseling Vol. 34; no. 2; pp. 1 - 8
Autores principales: Underhill, Meghan L., Li, Xintong, Shah, Jaimin, Dreisbach, Caitlin
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell Apr2025
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Low frequency of structured documentation for cancer genetic testing in a large electronic health record dataset: A brief report using All of Us Research data.
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          Underhill, Meghan L.
          Li, Xintong
          Shah, Jaimin
          Dreisbach, Caitlin
        affil: School of Nursing, University of Rochester, Rochester New York,, USA
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        subj:
          Neoplasms Diagnosis
          Genetic Screening Statistics and Numerical Data
          Genetic Screening Methods
          Documentation
          Electronic Health Records
          Data Management
          Human
          New York
          Funding Source
          Male
          Female
          Middle Age
          Prospective Studies
          Retrospective Design
          Record Review
          Descriptive Statistics
          Patient History Taking
          Family History
          Ovarian Neoplasms Diagnosis
          Breast Neoplasms Diagnosis
          Pancreatic Neoplasms Diagnosis
          Middle Aged: 45-64 years
          Male
          Female
      ab: Annually, over two million individuals in the United States are diagnosed with cancer, with 10–20% attributed to hereditary cancer syndromes. Genetic testing for pathogenic variants is a standard component of cancer care guided by tumor pathology and family history. Despite this, access to and completion of cancer genetic testing remains suboptimal. This study aims to understand the rates and factors associated with genetic testing completion among individuals with cancer. Utilizing data from the All of Us Research Program, which includes over one million Americans, we examined the documentation of genetic testing in electronic health records. Participants diagnosed with breast, ovarian, colon, endometrial, or pancreatic cancer were selected using the All of Us Workbench cohort builder tool. Descriptive and univariate analyses were conducted within the integrated Jupyter Notebook. Out of 60,135 individuals with a diagnostic code for the eligible cancers, over 73% reported a family history of cancer. However, only 281 individuals had a diagnosis or procedural code for a cancer genetic test, with 82% completing the test post‐cancer diagnosis. While the All of Us data is a robust resource for large‐scale research, challenges in data acquisition and interpretation arise due to the reporting structure of genetic findings in most data sources, such as electronic health records. To effectively utilize large‐scale data for addressing issues in cancer genetic testing, shared data elements and standardized documentation are essential.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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