Background
Like many other medical technologies and treatments, there is a lack of reliable evidence on treatment effectiveness of mental health care. Increasingly, data from non‐experimental settings are being used to study the effect of treatment. However, as in a number of studies using non‐experimental data, a simple regression of outcome on treatment shows a puzzling negative and significant impact of mental health care on the improvement of mental health status, even after including a large number of potential control variables. The central problem in interpreting evidence from real‐world or non‐experimental settings is, therefore, the potential ‘selection bias’ problem in observational data set. In other words, the choice/quantity of mental health care may be correlated with other variables, particularly unobserved variables, that influence outcome and this may lead to a bias in the estimate of the effect of care in conventional models.
Aims of the Study
This paper addresses the issue of estimating treatment effects using an observational data set. The information in a mental health data set obtained from two waves of data in Puerto Rico is explored. The results using conventional models—in which the potential selection bias is not controlled—and that from instrumental variable (IV) models—which is what was proposed in this study to correct for the contaminated estimation from conventional models—are compared.
Methods
Treatment effectiveness is estimated in a production function framework. Effectiveness is measured as the improvement in mental health status. To control for the potential selection bias problem, IV approaches are employed. The essence of the IV method is to use one or more instruments, which are observable factors that influence treatment but do not directly affect patient outcomes, to isolate the effect of treatment variation that is independent of unobserved patient characteristics. The data used in this study are the first (1992–1993) and second (1993–1994) wave of the ongoing longitudinal study Mental Health Care Utilization Among Puerto Ricans, which includes information for an island‐wide probability sample of over 3000 adults living in poor areas of Puerto Rico. The instrumental variables employed in this study are travel distance and health insurance sources.
Results
It is very noticeable that in this study, treatment effects were found to be negative in all conventional models (in some cases, highly significant). However, after the IV method was applied, the estimated marginal effects of treatment became positive. Sensitivity analysis partly supports this conclusion. According to the IV estimation results, treatment is productive for the group in most need of mental health care. However, estimations do not find strong enough evidence to demonstrate treatment effects on other groups with less or no need. The results in this paper also suggest an important impact of the following factors on the probability of improvement in mental health status: baseline mental health status,...