Precision medicine has improved the quality of healthcare by providing personalized preventive measures, diagnostic tools, and treatment methods based on an individual's genetics, environment and lifestyle. Although precision medicine has provided positive impacts in many areas including cancer, cardiovascular disease, type 2 diabetes, and rare genetic conditions there are still several major constraints to its successful application. Genomic studies have been limited in representing diverse populations resulting in less reliable risk assessment and the current clinical reference ranges often fail to reflect normal age-related biological changes. The purpose of this study is to assess constraints in current precision medicine approaches and identify a broader framework for precision medicine by considering both age and genetic diversity. An organized literature analysis was performed to find relevant research related to how genomic information is represented, the role of aging, and the impact of guidelines on clinical decision-making. Most genomic data have been obtained from individuals of European descent, limiting their predictive ability for other populations. Several studies found that laboratory reference ranges inherited from earlier generations misclassify healthy older adults. Representative samples of diverse populations need to be included when multi-omic data and AI tools are used to improve risk assessment and personalized treatment. Precision medicine needs to go beyond a person’s genetic profile to include aging and population diversity. To close gaps in research we must increase participation of underrepresented groups, develop age-specific clinical guidelines, and reduce structural barriers to healthcare. This inclusion can help reduce health disparities and improve outcomes for diverse populations.