Related Experiment Video
Updated: Oct 16, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Maintaining Quality of Genetic Counseling Services While Maximizing Efficiency: Protocol for the GC-PRO Intervention
Deborah Cragun1, Elena R Fisher2, Ashley Petersen3
1College of Public Health, University of South Florida, Tampa, Florida, USA.
Abstract:
The rapid integration of genomic medicine into clinical care has created an unprecedented demand for genetic counseling (GC) services. Attempts to streamline care have involved integration of GC assistants, group counseling sessions, and development of educational technology supplements; meanwhile, improving the efficiency of the core clinical interaction itself remains understudied. This study will evaluate the GC-PRO Intervention, a targeted communication training for genetic counselors designed to optimize visit time by aligning counseling with patient-centered needs and removing processes that do not contribute to positive patient experiences. Using a stepped-wedge cluster randomized trial design across clinical specialties (e.g., prenatal, cancer, cardiology, and general genetics) at two academic health centers, we will recruit approximately 20 genetic counselors and 994 patients. To ensure the intervention and study design are culturally responsive, we are utilizing a community-based participatory research approach with four multicultural community advisory boards. The intervention training focuses on three evidence-based communication skills: Tailoring (assessing and integrating patient needs and values), Streamlining (reducing time spent gathering patient medical and family history information), and Main Messaging (reducing lecturing through increasing conversational exchanges). The primary outcome is visit time, and secondary outcomes include patient-reported measures of empowerment, activation, trust, working alliance, patient-centered communication, and overall satisfaction. Data will be analyzed using linear and generalized mixed-effects models to compare the intervention to standard of care, accounting for calendar time, counselor nesting, and pre-specified patient characteristics to improve precision. We hypothesize that this intervention will significantly reduce average visit time while maintaining or improving session quality, as measured against pre-specified non-inferiority thresholds. With 80% power to detect a 5-min difference in session length, this study aims to provide a scalable framework for efficient GC services without sacrificing the counselor-patient relationship or patient-centered outcomes.
