Utilization of health information technology among cancer genetic counselors

• Authors: Jordon B. Ritchie, Medical University of South Carolina; Caitlin G. Allen, Emory University; Heath Morrison, Medical University of South Carolina; Michelle Nichols, Medical University of South Carolina; Steven D. Lauzon, Medical University of South Carolina; Joshua D. Schiffman, Huntsman Cancer Institute; Chanita Hughes Halbert, Medical University of South Carolina; Brandon M. Welch, Medical University of South Carolina
• Journal Title: Molecular Genetics and Genomic Medicine
• Volume: Volume 8, Number 8
• Publisher: Wiley | 2020-08-01, Pages e1315-e1315
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1002/mgg3.1315
• Subjects: Biology, Genetics; Health Sciences, Health Care Management
• Keywords: biomedical informatics; genetic counseling; health information technology; software; Counselors; Facilities and Services Utilization; Genetic Counseling; Genetic Testing; Health Knowledge, Attitudes, Practice; Humans; Medical Informatics; Neoplasms; Software; Surveys and Questionnaires

Abstract

Background: Health information technology (IT) is becoming increasingly utilized by cancer genetic counselors (CGCs). We sought to understand the current engagement, satisfaction, and opportunities to adopt new health IT tools among CGCs. Methods: We conducted a mixed-mode survey among 128 board-certified CGCs using both closed- and open-ended questions. We then evaluated the utilization and satisfaction among 10 types of health IT tools, including the following: cancer screening tool, family health history (FHx) collection tools, electronic health records (EHRs), telegenetics software, pedigree drawing software, genetic risk assessment tools, gene test panel ordering tools, electronic patient education tools, patient communication tools, and family communication tools. Results: Seven of 10 health IT tools were used by a minority of CGCs. The vast majority of respondents reported using EHRs (95.2%) and genetic risk assessment tools (88.6%). Genetic test panel ordering software had the highest satisfaction rate (very satisfied and satisfied) at 80.0%, followed by genetic risk assessment tools (77.1%). EHRs had the highest dissatisfaction rate among CGCs at 18.3%. Dissatisfaction with a health IT tool was associated with desire to change: EHRs (p <.001), cancer screening tools (p =.010), genetic risk assessment tools (p =.024), and family history collection tools (p =.026). We found that nearly half of CGCs were considering adopting or changing their FHx tool (49.2%), cancer screening tool (44.9%), and pedigree drawing tool (41.8%). Conclusion: Overall, CGCs reported high levels of satisfaction among commonly used health IT tools. Tools that enable the collection of FHx, cancer screening tools, and pedigree drawing software represent the greatest opportunities for research and development.