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Genetics provides a vital tool for primary health-care practitioners, aiding in targeted medication therapy, managing multifactorial illness risks, and addressing hereditary reproductive hazards. Discovering genomic variations linked to diseases enhances our understanding of these medical conditions, facilitating the development of personalized treatments and influencing health-care decisions. It has been predicted that advancing technologies and research will improve clinical practices. For instance, the post-COVID-19 era saw the increasing fusion of genetic approaches with digital health tools, marked by the incorporation of genetic data into electronic medical records, which helps advance the maturation of precision medicine. However, challenges such as managing large datasets and limited resource accessibility hinder the full potential of genetic data. Standardizing data formats and integrating genetic data with health-care systems remains problematic and unfeasible for collaboration. The rise of telemedicine and remote monitoring has paved the way for more expanded genetic counseling access, whereas artificial intelligence provides a promising tool for revolutionizing precision medicine through extensive genomic data analysis. Nonetheless, privacy, standardization, and ethical concerns persist, calling for more secure data management practices in genomic health care. Ensuring compliance with the General Data Protection Regulation and Health Insurance Portability and Accountability Act is crucial for ethical data handling. Moreover, a shortage of trained professionals limits access to specialized care, especially in underserved areas. This study reviews digital health applications in genetics and genomics, assessing their impact on health-care delivery and patient outcomes. Addressing these challenges is critical for fostering effective, equitable health-care solutions, a prerequisite for promoting a precise, patient-centered approach to medicine.
Crimi et al. (2024) studied this question.