Article Abstract

Article Abstract

Online ISSN: 1099-176X Print ISSN: 1091-4358
The Journal of Mental Health Policy and Economics
Volume 14, Issue 3, 2011. Pages: 125-135
Published Online: 30 September 2011

Cost-effectiveness Analysis of Olanzapine and Risperidone in Norway

Kun Kim,¹ Eline Aas²

¹MS, i3 innovus, Klarabergsviadukten 90, Hus D, 111 64, Stockholm Sweden
²PhD, University of Oslo, Department of Health Management and Health Economics, P.O. Box 1089 Blindern NO-0318 Oslo, Norway

* Correspondence to: Kun Kim, i3 innovus, Klarabergsviadukten 90, Hus D, 111 64, Stockholm, Sweden.
Tel: +46-8-545 28748
Fax: +46-8-545 28540
E-mail:kun.kim@i3innovus.com

Source of Funding: None declared

Abstract

Our aim was to develop a decision analytic model to evaluate the cost-effectiveness of antipsychotics in a Norwegian setting. The Positive and Negative Symptom Scale (PANSS) score was used to measure effectiveness of the antipsychotics, and costs were analyzed from the payer’s perspective. A comprehensive decision model was developed by combining a decision tree model and a Markov model. The model results indicated that olanzapine was a dominant alternative to risperidone. However, the Probability Sensitivity Analysis (PSA) results indicated that the chance of olanzapine being an optimal alternative was 67.1% in the model. Based on the PSA analysis, we could not conclude that olanzapine is an optimal alternative to risperidone in Norway. However, we demonstrated that PSA is a useful tool to examine uncertain parameters and the model facilitates calculation of the overall costs per patient treated with antipsychotics in Norway.

Background: Antipsychotic medications are the mainstay for schizophrenia treatment, and olanzapine and risperidone are popular choices among atypical antipsychotics in Norway. Our aim was to develop a decision analytic model to evaluate the cost-effectiveness of antipsychotics in a Norwegian setting.

Methods: The Positive and Negative Symptom Scale (PANSS) score was used to measure effectiveness of the antipsychotics, and costs were analyzed from the payer's perspective. Sensitivity analysis, including Probability Sensitivity Analysis (PSA), was conducted using Monte Carlo simulation to identify uncertain parameters and their effect on the results.

Results: A comprehensive decision model was developed by combining a decision tree model and a Markov model. The model results indicated that olanzapine was a dominant alternative to risperidone (cost per patient in the first year; olanzapine 68,718 vs. risperidone 70,359, PANSS score reductions; olanzapine 112.60 vs. risperidone 111.55, and cost per patient from the second to fifth year; olanzapine 148,732 vs. risperidone 154,632). However, the PSA results indicated that olanzapine and risperidone were not different in terms of cost-effectiveness within a 95% confidence interval. The Incremental Cost-Effectiveness (ICE) scatterplot showed that the chance of olanzapine being an optimal alternative was 67.1% in the model.

Discussion: Based on the PSA analysis, we could not conclude that olanzapine is an optimal alternative to risperidone in Norway. However, PSA may be a useful tool to examine the results generated by a decision analytic model using uncertain parameters. The model facilitates calculation of the costs per patient treated with antipsychotics, and the model may be useful as a basic frame for modeling patients with schizophrenia in Norway.

Received 1 March 2011; accepted 30 August 2011