Pharmacogenetic testing identifies genetic biomarkers that are predictive of individual sensitivity to particular drugs. A significant proportion of medications that are widely prescribed for older adults are metabolized by enzymes that are encoded by highly polymorphic genes. Pharmacogenetic testing is increasingly used to optimize the medication regimen; however, its potential in older adults with polypharmacy has not been systematically explored. Following the initial case–series study, this study hypothesized that frequently hospitalized older adults with polypharmacy have higher frequency of pharmacogenetic polymorphism as compared to older adults with polypharmacy who are rarely admitted to a hospital. To test this hypothesis, a nested case–control study was conducted with pharmacogenetic polymorphism as an exposure and hospitalization rate as an outcome. In this study, frequently hospitalized older adults (≥65 years of age) with polypharmacy were matched with rarely hospitalized older adults with poly-pharmacy by age, gender, race, ethnicity, and chronic disease score. Average age and number of prescription drugs did not differ in cases and controls (77.2±5.0 and 78.3±5.1 years, 14.3±5.3 and 14.0±2.9 medications, respectively). No statistically significant difference in sociodemographic, clinical, and behavioral characteristics that are known to affect hospitalization risk was found between the cases and controls. Major pharmacogenetic polymorphism defined as presence of at least one allelic combination resulting in poor or rapid metabolizer status was identified in all the cases. No major pharmacogenetic polymorphisms were detected in controls. Based on the exact McNemar’s test, the difference in major pharmacogenetic polymorphism frequency between cases and controls was statistically significant (p<0.05). In 50% of cases, more than one major pharmacogenetic polymorphism was found. The frequency of CYP2C19 rapid metabolizer, CYP3A4/5 poor metabolizer, VKORC1 low sensitivity, and CYP2D6 rapid metabolizer status in cases was 67%, 33%, 33%, and 17%, respectively, which significantly exceeded respective prevalence in general population. The mean number of major gene–drug interactions found in cases was 2.8±2.2, whereas no major drug–gene interactions were identified in controls. The difference in the number of major drug–gene interactions between cases and controls was statistically significant (p<0.05). The pilot data supported the hypothesis that pharmacogenetic polymorphism may represent an independent risk factor for frequent hospitalizations in older adults with polypharmacy. Due to small sample size, the results of this proof-of-concept study cannot be conclusive. Further work on the utility of pharmacogenetic testing for optimization of medication regimens in this vulnerable group of older adults is warranted.