- Current traditional medicine practices are uniform for all patients, resulting in high costs and predominantly relying on trial and error for disease diagnosis and treatment plans.
- Advanced genomic research and technology have expedited the integration of precision medicine into clinical practices, aiming to enhance patient outcomes.
- AI-enabled precision medicine holds great promise in helping healthcare providers, research institutions, and pharmaceutical companies to administer the appropriate treatment to the right patient at the right time, thereby reducing disease prevalence and the cost of care.
Our Advice
Critical Insight
- Most healthcare organizations lack optimized data landscapes, resulting in a typical data analysis turnaround time of 26 hours. This time frame is too slow for real-time use in acute care settings.
- While the accessibility of genetic data for precision medicine is increasing for individuals and clinicians, cost remains a barrier, as it is expensive and often has limited insurance coverage.
- The implementation cost of AI is a notable concern for healthcare organizations, especially when managing competing priorities.
Impact and Result
Info-Tech’s human-centric, value-based approach serves as a guide for deploying AI applications in precision medicine. This approach encompasses:
- Understanding the evolutionary state of precision medicine.
- Identifying the benefits and challenges associated with AI-powered precision medicine.
- Assessing AI maturity for precision medicine using a maturity assessment tool.