The journal of mental health policy and economics
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J Ment Health Policy Econ · Jun 1999
The productivity of mental health care: an instrumental variable approach.
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. ⋯ The results in this paper are supportive of the concerns on the credibility of evaluation results using observation data set when the endogeneity of the treatment variable is not controlled. Unobserved factors contribute to the downward bias in the conventional models. The IV approach is shown to be an appropriate method to reduce the selection bias for the group in most need for mental health care, which is also the group of most policy and treatment concern. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: The results of this work have implications for resource allocation in mental health care. Evidence is found that mental health care provided in Puerto Rico is productive, and is most helpful for persons in most need for mental health care. According to what estimated from the IV models, on the margin, receiving formal mental health care significantly increases the probability of obtaining a better mental health outcome by 19.2%, and one unit increase in formal treatment increased the probability of becoming healthier by 6.2% to 8.4%. Consistent with other mental health literature, an individual's baseline mental health status is found to be significantly related to the probability of improvement in mental health status: individuals with previous treatment history are less likely to improve. Among demographic factors included in the production function, being female, married, and high education were found to contribute to a higher probability of improvement. IMPLICATION FOR FURTHER RESEARCH: In order to provide accurate evidence of treatment effectiveness of medical technologies to support decision making, it is important that the selection bias be controlled as rigorously as possible when using information from a non-experimental setting. More data and a longer panel are also needed to provide more valid evidence. tion.