J Clin Obstet Gynecol Infertil | Volume 8, Issue 1 | Review Article | Open Access
Underkofler KA, Novicoff W, Thomas MHz, Sopata C, Savage S and Ring KL*
1Emily Couric Clinical Cancer Center, University of Virginia, USA 2Department of Orthopedic Surgery, University of Virginia, USA 3Department of Obstetrics & Gynecology, University of Virginia, USA 4Invitae Corporation, San Francisco, USA
*Correspondance to: Kari L Ring
Fulltext PDFBackground: Approximately 5.6% of the general population carries a germline pathogenic variant in a cancer gene. Current screening methods fail to identify many of these patients. Providers report limitations in time and expertise as barriers to identification of high-risk patients. Gia® (Genetic Information Assistant) is a cloud-based genetic information and assessment chatbot from InvitaeⓇ designed to assist screening patients for high-risk pathogenic variants and educate regarding genetic testing. Objective: To utilize Lean methodology to map the current process of screening for high-risk individuals and compare to an ideal future state process that utilizes Gia to model how Gia may increase rates of screening for hereditary cancer syndromes in less time. Study Design: Current process observations took place in two general gynecology clinics, one that cares for a diverse and underinsured population, and another that serves a population with a higher proportion of privately insured patients. A value stream map was developed based on observations of the current state. Ideal state maps were then developed to incorporate Gia and illustrate how it may be used to improve areas identified as inefficient in the current state. Results: Screening for hereditary cancer pathogenic variants occurred in 8 of 10 observed encounters in Clinic A and 9 of 9 in Clinic B (80% vs. 100%). In Clinic A, 40% (4/10) of patients were high-risk for a pathogenic variant and of these, 75% (3/4) had an appropriate provider action taken. In Clinic B, 33% (3/9) of patients were noted to be high-risk, and all received appropriate intervention from the provider (3/4 in Clinic A vs. 3/3 in Clinic B). The average provider time investment to screen in Clinic A was 8.3% of the encounter (average 99 seconds) compared to 9.5% of the encounter (average 114 seconds) in Clinic B. High-risk patient screening in Clinic A occupied 13.9% of the encounter (average 167 seconds) and low-risk patient screening occupied 2.6% of the encounter (average 31 seconds). Similarly, in Clinic B, high-risk screening occupied 14.4% of the encounter (average 173 seconds) compared to 7% of the encounter (average 84 seconds) for low-risk patients. Conclusion: Screening for pathogenic variants in genes linked to hereditary cancer is not standardized or universal, and may exacerbate disparities in care. Identification of barriers in screening processes and use of technology such as Gia to overcome these barriers may result in more universal and equitable genetic screening.
Familial cancer; Genetic screening; Health technology; Pathogenic variants; Quality improvement
Underkofler KA, Novicoff W, Thomas MH, Sopata C, Savage S, Ring KL. The Application of Lean Methodology in Hereditary Cancer Syndrome Screening: Can a Clinical Chatbot Lead to Improvement?. J Clin Obstet Gynecol Infertil. 2024; 8(1): 1065..