Translating behavioral health services research into benefits policy.
This article uses a 4-pronged statistical approach to examine the impact of a mental health carve-out at a major employer. To examine net financial impact of the carve-out, the authors perform a pre-post, multivariate regression analysis of changes in costs. Using a random-effects model, the authors explore the ultimate financial impact of the carve-out for patients and for the firm. Using a multinomial logistic regression, they examine differing program effects by intensity of use. A fixed-effects negative binomial regression models the episodic nature of outpatient care, controlling for patient-specific unobserved characteristics that influence health care utilization. The carve-out slightly reduced overall mental health costs and utilization while expanding entry-level access to routine services. At the same time, the specific carve-out shifted financial burdens from the firm onto high-utilization patients. Therefore, this carve-out appears poorly suited to the care of individuals experiencing severe and debilitating psychiatric disorders.
Grazier
K L
KL
University of Michigan, USA.
Pollack
H
H
D000328:Adult; D002140:California; D004059:Diffusion of Innovation; D005260:Female; D006264:Health Benefit Plans, Employee / Q000458:organization & administration*; D017048:Health Care Costs / Q000706:statistics & numerical data; D006291:Health Policy; D006297:Health Services Accessibility / Q000458:organization & administration; D006302:Health Services Research / Q000458:organization & administration*; D006801:Humans; D007358:Insurance, Psychiatric; D016015:Logistic Models; D008297:Male; D008605:Mental Health Services / Q000191:economics*; D008875:Middle Aged; D015999:Multivariate Analysis; D011243:Preferred Provider Organizations / Q000458:organization & administration*; D015397:Program Evaluation