Evaluation of the digital genetic assistant in technology assisted genetic counseling for genetic carrier screening
Rapid growth in genetic testing usage resulted in declining availability of genetic counselors (GCs) per ordered tests, prolonging the waiting times for face-to-face (F2F) counseling. We evaluated the digital genetic assistant (DGA) for reproductive genetic carrier screening (RGCS) in a real-life clinical setting using a "couple-based" paradigm. The platform provides digital patient intake and automated counseling for low-risk individuals, as well as GC-facing tools that reduce administrative burden in patient-related activities. Among 225 couples undergoing RGCS during the study period, 4% had high-risk results requiring F2F counseling and an additional 4% of low-risk couples requested F2F counseling, suggesting that DGA use reduced GC-participant F2F interactions by 69.3%. GC evaluations revealed that the DGA triaging algorithm was accurate and surveys demonstrated high degrees of user comprehension and satisfaction. These results highlight the utility of digital platforms for patient intake and delivery of low-risk results in settings with limited genetic counseling resources.
Authors
- Haike Reznik Wolf
- Elon Pras (ORCID: https://orcid.org/0000-0001-8094-7429)
- Adi Reches
- Alina Kurolap (ORCID: https://orcid.org/0000-0002-7005-3621)
- Liat Ries Levavi
- Hagit Baris Feldman (ORCID: https://orcid.org/0000-0003-4065-7560)
- Doron M. Behar (ORCID: https://orcid.org/0000-0002-2623-4599)
- Yael Furman
- Nurit Goldstein
- Yuval Yaron (ORCID: https://orcid.org/0000-0001-8622-7668)
- Michal Berkenstadt (ORCID: https://orcid.org/0000-0003-0561-7088)
- Vered Ofen Glassner
- Galit Delmar
- Liat Abo Gutstein
- Mori Anouchi
Institutions
- Tel Aviv University (IL)
- Tel Aviv Sourasky Medical Center (IL)
- Sheba Medical Center (IL)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1038/s41746-025-01573-7
- Citations
- 1
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.82