BACKGROUND: Understanding resource utilization patterns among high-cost patients may inform cost reduction strategies. OBJECTIVE: To identify patterns of high-cost healthcare utilization and associated clinical diagnoses and to quantify the significance of hot-spotters among high-cost users. DESIGN: Retrospective analysis of high-cost patients in 2012 using data from electronic medical records, internal cost accounting, and the Centers for Medicare and Medicaid Services. K-medoids cluster analysis was performed on utilization measures of the highest-cost decile of patients. Clusters were compared using clinical diagnoses. We defined Bhotspotters^as those in the highest-cost decile with ≥4 hospitalizations or ED visits during the study period. PARTICIPANTS AND EXPOSURE: A total of 14,855 Medicare Fee-for-service beneficiaries identified by the Medicare Quality Resource and Use Report as having received 100 % of inpatient care and ≥90 % of primary care services at Cleveland Clinic Health System (CCHS) in Northeast Ohio. The highest-cost decile was selected from this population. MAIN MEASURES: Healthcare utilization and diagnoses. KEY RESULTS: The highest-cost decile of patients (n = 1486) accounted for 60 % of total costs. We identified five patient clusters: BAmbulatory,^with 0 admissions; BSurgical,^with a median of 2 surgeries; BCritically Ill,^with a median of 4 ICU days; BFrequent Care,^with a median of 2 admissions, 3 ED visits, and 29 outpatient visits; and BMixed Utilization,^with 1 median admission and 1 ED visit. Cancer diagnoses were prevalent in the Ambulatory group, care complications in the Surgical group, cardiac diseases in the Critically Ill group, and psychiatric disorders in the Frequent Care group. Most hot-spotters (55 %) were in the Bfrequent care^clus-ter. Overall, hot-spotters represented 9 % of the high-cost population and accounted for 19 % of their overall costs. CONCLUSIONS: High-cost patients are heterogeneous; most are not so-called Bhot-spotters^with frequent admissions. Effective interventions to reduce costs will require a more multi-faceted approach to the high-cost population.