Objective: This study presents a methodology to estimate prevalence rates for specific diagnosed conditions among the ~170 million Americans covered by employer-sponsored insurance (ESI). Individuals with ESI represent over 58% of the United States population, a large group with fewer cost barriers to care. Methods: Estimates were made from the 2006 MarketScan databases, which include all healthcare claims for approximately 17 million employees, dependents, and retirees with ESI. The Sample Select Prevalence tool identified patients diagnosed with asthma, osteoporosis, allergic rhinitis (AR), essential hypertension, rheumatoid arthritis (RA), type II diabetes, congestive heart failure (CHF), or hypercholesterolemia (using relevant ICD-9-CM diagnosis codes), and calculated prevalence rates. Weights were developed based on the Medical Expenditure Panel Survey (MEPS), a probability sample that estimates the number of Americans by health insurance type. The ratio of MEPS population estimate to MarketScan population within certain strata of demographic characteristics provided the projection weights. Prevalence rates were calculated for the total population and by age, gender, geographic region, and health plan type. Results: Based on the 2006 MarketScan databases, annual rates per 100,000 were as follows: 12,101.63 (hypertension), 5,102.10 (type II diabetes), 4,648.86 (AR), 4,257.15 (hypercholesterolemia), 3,015.54 (asthma), 947.14 (osteoporosis), 713.7 (CHF), 532.97 (RA). These rates varied by age, gender, and geography. Annual expenditures per patient in the convenience sample ranged from $5,920 (AR) to $36,615 (CHF). Conclusion: Reliable estimates of prevalence and costs for diagnosed health conditions are valuable to policy makers, providers, and payers. This study demonstrates a reliable projection methodology for estimating annual prevalence, treatment rates, and costs associated with a diagnosed disease or condition based on a large convenience sample of healthcare claims data.