Impact of computer-assisted data collection, evaluation and management on the cancer genetic counselor's time providing patient care

The composition and capacity of the clinical genetics workforce in high-income countries: a scoping review

As genetics becomes increasingly integrated into all areas of health care and the use of complex genetic tests continues to grow, the clinical genetics workforce will likely face greatly increased demand for its services. To inform strategic planning by health-care systems to prepare to meet this future demand, we performed a scoping review of the genetics workforce in high-income countries, summarizing all available evidence on its composition and capacity published between 2010 and 2019. Five databases (MEDLINE, Embase, PAIS, CINAHL, and Web of Science) and gray literature sources were searched, resulting in 162 unique studies being included in the review. The evidence presented includes the composition and size of the workforce, the scope of practice for genetics and nongenetics specialists, the time required to perform genetics-related tasks, case loads of genetics providers, and opportunities to increase efficiency and capacity. Our results indicate that there is currently a shortage of genetics providers and that there is a lack of consensus about the appropriate boundaries between the scopes of practice for genetics and nongenetics providers. Moreover, the results point to strategies that may be used to increase productivity and efficiency, including alternative service delivery models, streamlining processes, and the automation of tasks.

An internal performance assessment of CancerGene Connect: an electronic tool to streamline, measure and improve the genetic counseling process

CancerGene Connect (CGC) is a web-based program that combines the collection of family and medical history, cancer risk assessment, psychosocial assessment, report templates, a result tracking system, and a patient follow up system. The performance of CGC was assessed in several ways: pre-appointment completion data analyzed for demographic and health variables; a time study to assess overall time per case and to compare the data entry by the genetic counselor compared to the patient, and a measured quality assessment of the program via observation and interview of patients. Prior to their appointment, 52.3% of 2,414 patients completed the online patient questionnaire section of CGC. There were significant differences in completion rates among racial and ethnic groups. County hospital patients were less likely to complete the questionnaire than insured patients (p < 0.0001); and likewise uninsured patients and patients with Medicare/Medicaid were less likely to complete the questionnaire than private patients (p < 0.0001). The average genetic counseling time per case was 82 min, with no significant differences whether the counselor or the patient completed CGC. CGC reduces genetic counselor time by approximately 14-46% compared to average time per case using traditional risk assessment and documentation methods previously reported. All surveyed users felt the questionnaire was easy to understand. CGC is an effective tool that streamlines workflow, and provides a standardized data collection tool that can be used to evaluate and improve the genetic counseling process.