2023 ACMG Annual Clinical Genetics Meeting Digital Edition: Poster Gallery-Limitations of automated approaches to utilizing the EHR to identify high-risk patients for hereditary cancer genetic testing

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A study conducted at NYU Langone Health Perlmutter Cancer Center and the University of Utah Health examined the implementation of an automated workflow for identifying high-risk patients eligible for hereditary cancer genetic testing. The study found that a significant number of patients identified through the automated workflow may require manual review to determine eligibility for genetic testing. This manual review process is complex, time-consuming, and requires trained staff in cancer genetics to facilitate.<br /><br />One challenge in the automated workflow was assessing prior genetic testing and counseling. The algorithm used in the workflow was specific for patients without prior genetic testing, but patients with prior testing or counseling needed different assessment and education. However, documentation of these services in the electronic health record (EHR) was often incomplete or missing, leading to the need for further investigation by genetic counseling assistants (GCAs) to determine eligibility for services.<br /><br />Other factors that impact the efficiency and accuracy of automated processes include state licensure laws that regulate the provision of genetic services and the need to update algorithms when there are changes in clinical guidelines.<br /><br />The findings of the study highlight the importance of carefully evaluating what steps can be automated in genomic medicine workflows and determining where manual review and staff support will be needed. This is necessary for the sustainability of such workflows.<br /><br />The study was part of a broader clinical trial called Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE), which aimed to improve the identification of high-risk patients for hereditary cancer. The trial used a clinical decision support (CDS) algorithm based on structured family history data captured in the EHR to identify eligible patients.<br /><br />Out of the selected sample of patients from NYU Langone Health and the University of Utah Health, a significant percentage were determined to be ineligible for genetic counseling and/or testing services. The main reasons for ineligibility included previous genetic testing, being out of state, previous genetic counseling, familial mutation, incorrect family history, and unwillingness to activate a patient portal account.<br /><br />Overall, the study emphasizes the need for ongoing evaluation and support in implementing automated workflows for identifying high-risk patients for hereditary cancer genetic testing.

Asset Subtitle

Presenting Author - Rachelle Chambers, MS, CGC; Co-Author - Meenakshi Sigireddi, MD; Co-Author - Kimberly A. Kaphingst, ScD; Co-Author - Rachel Monahan, BA; Co-Author - Wendy Kohlmann, MS; Co-Author - Amanda Gammon, MS, CGC; Co-Author - Brianne M. Daly, BA; Co-Author - Lingzi Zhong, PhD;

Meta Tag

Bioinformatics

Cancer Syndromes

Genetic Testing

Risk Assessment

Co-Author Meenakshi Sigireddi, MD

Co-Author Kimberly A. Kaphingst, ScD

Co-Author Rachel Monahan, BA

Co-Author Wendy Kohlmann, MS

Co-Author Amanda Gammon, MS, CGC

Co-Author Brianne M. Daly, BA

Co-Author Lingzi Zhong, PhD

Presenting Author Rachelle Chambers, MS, CGC

Keywords

automated workflow

high-risk patients

hereditary cancer genetic testing

manual review

eligibility

genetic testing

cancer genetics

prior genetic testing

genetic counseling

electronic health record (EHR)