Date of Award

5-2024

Document Type

Thesis - Closed Access

Degree Name

MS in Human Genetics

First Advisor

Katie Gallagher

Second Advisor

John Greally

Third Advisor

Monisha Sebastin

Abstract

This study aimed to assess the attitudes of genetics providers regarding a clinical decision aid designed to assist in genetic diagnosis of rare pediatric disease. User experience, expectations, and opinions were investigated related to clinical decision and AI-driven software in healthcare diagnostics. Six participants employed at Montefiore Medical Center, who have experience ordering whole genome sequencing, were selected to participate in a semi-structured interview assessing their opinions and expectations for a clinical decision aid, GenomeDiver, designed to improve lab-clinician communication. Responses were assessed via manifest and latent content analysis, which was mutually reviewed for coder consensus. While all participants believed GenomeDiver could be helpful for genetic diagnostics, particularly in the case of complex patient presentations or variants of uncertain significance, they expressed concern about the risk of misinterpretation by untrained individuals, risk to patient-provider relationships, and the logistics of setting up and using the tool in a clinical setting. The results of our study highlight important considerations to be made in the development of software designed to improve diagnosis through genetic testing and help providers harness the power of “big data” in genomic diagnostics.

Under author imposed embargo.
Available for download on Thursday, May 01, 2025

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