Personalized medicine, often known as precision medicine, is intended to differentiate tailored treatment from trial and error. The modern notion has grown to particularly integrate a patient's "omic profile" in disease prevention, diagnosis, and treatment. Precision medicine has shifted from an academic exercise to a clinical reality for some conditions, with others not far behind. Rapid genomic discoveries made possible by genome-wide association studies (GWAS) combined with decreasing sequencing and genotyping costs have shifted precision medicine from an academic exercise to a clinical reality for some conditions, while others are not far behind. With the advent of electronic health records (EHRs), it is now possible to conduct population-scale research while also successfully delivering individualized medication to individual patients via clinical decision support. The inclusion of historically under-represented groups in sufficient numbers to allow statistically accurate inferences of the influence of relevant risk variables, including genetic contributions to disease risk, is a major problem for precision medicine research. Precision medicine experts have acknowledged the need of increasing diversity and have used a range of methods to do so.