Introducing Edna: A trainee chatbot designed to support communication about additional (secondary) genomic findings. Issue 4 (April 2021)

• Record Type: Journal Article
• Authors: Ireland, David; Bradford, DanaKai; Szepe, Emma; Lynch, Ella; Martyn, Melissa; Hansen, David; Gaff, Clara
• Is Part Of: Patient education and counseling. Volume 104:Issue 4(2021)
• Page Start: 739
• Page End: 749
• Publication Date: 2021-04
• Subjects: Genetic counseling -- Additional findings -- Secondary findings -- Patients -- Chatbot -- Conversation agent -- Family history -- Natural language processing -- Sentiment analysis; Patient education -- Periodicals; Health counseling -- Periodicals; Health education -- Periodicals; Counseling -- Periodicals; Patient Education -- Periodicals; Éducation des patients -- Périodiques; Counseling -- Périodiques; Éducation sanitaire -- Périodiques; 615.5071
• DOI: 10.1016/j.pec.2020.11.007
• Languages: English
• ISSNs: 0738-3991

Abstract

Highlights: Analysis of genetic counseling transcripts provided insights into patient needs. A chatbot can assist patients to make informed decisions for additional findings. Natural language processing algorithms applied to program a digital genetic resource. Chatbot able to collect family history and refer patients to genetic counselors. Conversation agent able to emulate natural flow of genetic counseling sessions. Abstract: Objective: To support informed decision-making about reanalysis of clinical genomic data for risk of preventable conditions ('additional findings') by developing a chatbot (electronic genetic resource, 'eDNA'). Methods: Interactions in pre-test genetic counseling sessions (13.5 h) about additional findings were characterized using proponent, thematic and semantic analyses of transcripts. We then wrote interfaces to draw supplementary data from external genetics applications. To create Edna, this content was programmed using a chatbot framework which interacts with patients via speech-to-text. Results: Conditions, terms, explanations of concepts, and key factors to consider in decision making were all encoded into chatbot conversations emulating counseling session flows. Patient agency can be enhanced by prompted consideration of the personal and familial implications of testing. Similarly, health literacy can be broadened through explanation of genetic conditions and terminology. Novel aspects include sentiment analysis and collection of family history. Medical advice and the impact of existing genetic conditions were deemed inappropriate for inclusion. Conclusion: Edna's successful development represents a movement towards accessible, acceptable and well-supported digital health processes for patients to make informed decisions for additional findings. Practice implications: Edna complements genetic counseling by collecting and providing genomic information before or after pre-test consultations.