Abstract
To measure how a change in gatekeeping model affects utilization of specialty mental health services.
Secondary data from health insurance claims for services during 1996-1999. The setting is a managed care organization that changed gatekeeping model in one of its divisions, from in-person evaluation to the use of a call-center.
We evaluate the impact of the change in gatekeeping model by comparing utilization during the 2 years before and 2 years after the change, both in the affected division and in another division where gatekeeping model did not change. The design is thus a controlled quasi-experimental one. Subjects were not randomized. Key dependent variables are whether each individual had any specialty mental health visits in a year; the number of visits; and the proportion of users exceeding eight visits in a year. Key explanatory variables include demographic variables and indicators for patient diagnoses and their intervention status (time-period, study group).
Claims data were aggregated to create analytic files with one record per member per year, with variables reporting demographic characteristics and mental health service use.
After controlling for secular trends at the other division, the division which changed gatekeeping model eventually experienced an increase in the proportion of enrollees receiving specialty mental health treatment, of 0.5 percentage point. Similarly, there was an increase of about 0.6 annual visits per user, concentrated at the low end of the distribution. These changes occurred only in the second year after the gatekeeping changes.
The results of this study suggest that the gatekeeping changes did lead to increases in utilization of mental health care, as hypothesized. At the same time, the magnitude of the increase in access and mean number of visits that we found was relatively modest. This suggests that while the change from face-to-face specialty gatekeeping to call-center intake does increase utilization, it is unlikely to overwhelm a system with new demand or create huge cost increases.