Advantages of the Net Benefit Regression Framework for Economic Evaluations of Interventions in the Workplace
A Case Study of the Cost-Effectiveness of a Collaborative Mental Health Care Program for People Receiving Short-Term Disability Benefits for Psychiatric Disorders
Dr. Hoch earned his Ph.D. in Health Economics from the Johns Hopkins School of Public Health, after completing his MA in Economics from The Johns Hopkins University. Dr. Hoch received his B.A. from the University of California at San Diego. Dr. Hoch’s experience is in applied health economics related to cancer, mental health, and other health issues affecting poor and vulnerable populations. An award-winning teacher, Dr. Hoch has taught Health Economics and Economic Evaluation classes in the United States and internationally. Dr. Hoch pursues research making health economics more useful to decision makers.
Objective: Economic evaluations commonly accompany trials of new treatments or interventions; however, regression methods and their corresponding advantages for the analysis of cost-effectiveness data are not well known.
Methods: To illustrate regression-based economic evaluation, we present a case study investigating the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders. We implement net benefit regression to illustrate its strengths and limitations.
Results: Net benefit regression offers a simple option for cost-effectiveness analyses of person-level data. By placing economic evaluation in a regression framework, regression-based techniques can facilitate the analysis and provide simple solutions to commonly encountered challenges.
Conclusions: Economic evaluations of person-level data (eg, from a clinical trial) should use net benefit regression to facilitate analysis and enhance results.
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