Epidemiology and health service resource allocation policy for alcohol, drug abuse, and mental disorders.

Data from the NIMH Epidemiologic Catchment Area (ECA) Study in Baltimore, Md., are used to illustrate the association between alcohol, drug abuse, and mental disorder diagnoses with health service use. A probability sample of 3,481 adult (age 18 and over) residents of a geographically defined Baltimore City population of 175,000 was found to have a 23.4 per 100 population, 6-month prevalence of 13 specific alcohol, drug, and mental disorders. Of this population, 7.1 percent sought outpatient mental health treatment from both general medical physicians and mental health specialists in a 6-month period. The presence of a mental disorder diagnosis increased the average number of visits to all health providers from 1.91 to 4.06 during the same 6-month period. Although the presence of a mental disorder diagnosis clearly increased the probability of using both general medical and mental health services, only 15.6 percent of the persons with a mental disorder sought any mental health treatment during this 6-month timeframe--leaving 84 percent of those with mental disorders not seeking any outpatient treatment during the same period. The addition of a measure of high symptomatology (a score of 4 or more on the General Health Questionnaire) increased the percentage of persons with mental disorder using services to 30.5 percent. When a measure of disability was added to the diagnosis and the high symptom level score, 54.7 percent of the population could be predicted to use some mental health service. These data demonstrate the necessity of having additional patient assessment measures with a diagnosis to predict probable service use. However, even in the most comprehensive multidimensional model, more research is required to explore the phenomena of presumed unmet need--the 45 percent of those with a diagnosis, disability, and high symptoms who do not use services. Hence, epidemiologists who wish to participate in setting policy for resource allocation must join with their colleagues in economics, sociology, and health services research to identify all factors in addition to disease states that either predispose population groups to use services or represent additional resource allocation needs.