Optimizing genetics online resources for diverse readers.

PURPOSE: Clear and accurate genetic information should be available to health-care consumers at an individualized level of comprehension. The objective of this study is to evaluate the complexity of common online resources and to simplify text content using automated text processing tools. METHODS: We extracted all text from Genetics Home Reference and MedlinePlus in bulk and analyzed content using natural language processing. We applied custom tools to improve the readability and compared readability before and after text optimization. RESULTS: Commonly used educational materials were more complex than the recommended reading level for the general public. Genetic health information entries from Genetics Home Reference (n = 1279) were written at a median 13.0 grade level. MedlinePlus entries, which are not exclusively genetic (n = 1030), had a median grade level of 7.7. When we optimized text for the 59 actionable conditions by prioritizing medical details using a standard structure, the average reading grade level improved. CONCLUSION: Factors that increase complexity are long sentences and difficult words. Future strategies to reduce complexity include prioritizing relevant details and using more illustrations. Simplifying and providing standardized online health resources would benefit diverse consumers and promote inclusivity.

Genetics workforce: distribution of genetics services and challenges to health care in California.

PURPOSE: Access to genetics health-care services is often complicated by the distance to hospitals, workforce shortages, and insurance coverage. Despite technological advances and decreasing costs of genetic sequencing, the benefits of personalized medicine may be inaccessible to many patients. To assess potential disparities in care, we examined the genetics workforce in California and geographical issues that people encounter in seeking care. METHODS: Data on all board-certified genetics providers were analyzed including medical geneticists (MGs) and genetic counselors (GCs) in California. To assess distance traveled for care, we computed the distance patients traveled for n = 288 visits to University of California-San Francisco (UCSF) Medical Genetics. We performed geographic optimization to minimize the distance to genetics providers. RESULTS: The provider-to-patient ratio in California is 1:330,000 for MGs, 1:100,000 for GCs, and 1:1,520,000 for biochemical MGs. Genetics providers are concentrated in major metropolitan areas in California. People travel up to 386 miles for genetics care within the state (mean = 76.6 miles). CONCLUSION: There are substantial geographic barriers to genetics care that could increase disparities. Our findings highlight a challenging genetics workforce shortage. The shortage may be even greater due to care subspecialization or lack of full-time equivalency and staffing. We are currently promoting efforts to increase remote health-care options, training, and modified models of care.