During the past 2 decades, psychiatric epidemiological studies have contributed a rapidly growing body of scientific knowledge on the scope and risk factors associated with mental disorders in communities. Technological advances in diagnostic criteria specificity and community case-identification interview methods, which made such progress feasible, now face new challenges. Standardized methods are needed to reduce apparent discrepancies in prevalence rates between similar population surveys and to differentiate clinically important disorders in need of treatment from less severe syndromes. Reports of some significant differences in mental disorder rates from 2 large community surveys conducted in the United States—the Epidemiologic Catchment Area study and the National Comorbidity Survey—provide the basis for examining the stability of methods in this field. We discuss the health policy implications of discrepant and/or high prevalence rates for determining treatment need in the context of managed care definitions of "medical necessity."