MODEL DEVELOPMENT FOR ASSESSING COST-EFFECTIVENESS AND PREPARE REIMBURSEMENT DOSSIER OF RTMS IN PATIENT POPULATION WITH TREATMENT-RESISTANT DEPRESSION IN HUNGARY

Author(s)

Bella R1, Kovács S2, Vincze G2, Fittler A2, Botz L2, Zemplényi A3
1University of Pécs, Pécs, BA, Hungary, 2University of Pécs, Pécs, Hungary, 31) University of Pécs; 2) Syreon Research Institute, Pécs, BA, Hungary

Presentation Documents

OBJECTIVES : Major depressive disorder (MDD) is a common mental illness as being the second leading cause of disability worldwide. Treatment-resistant depression (TRD) amounts to 45% of total MDDs, however the definition is not yet standardized. Repetitive Transcranial Magnetic Stimulation (rTMS) has a rich literature for the treatment of TRD-patients. The aim of this study was to define an appropriate model concept for the cost effectiveness analysis of rTMS intervention in the TRD subpopulation of MDD in Hungary from payer perspective, to support the reimbursement process initiated by a tertiary healthcare provider.

METHODS : A systematic literature review was conducted and reported in compliance with the PRISMA Statement. After the screening, potentially relevant articles were analyzed in full text, and data were systematically extracted by use of explicit methodology.

RESULTS : The search query resulted in 61 articles, which after the deduplication and title abstract screening were narrowed down to six from which information about models employed in full economic analyses of rTMS were extracted. In general, within these articles a model time equal or shorter than 1 year were applied to cover the acute phase and a short maintenance period, however no relapse was implemented due to short model time. From methodological perspective decision tree and Markov models were used to assess the effect of rTMS during the acute and maintenance phase respectively. The cost-effectiveness of rTMS was determined in a comparison to electroconvulsive therapy or to medical management.

CONCLUSIONS : Based on the identified conceptual challenges we developed a model in line with the HTA guideline of Hungary. The model applies the combination of decision tree in the acute and Markov model in the maintenance phase with medical management as comparator. The suggested model time is 3 years, which enables to model relapse, aligned with the natural history of the disease.

Conference/Value in Health Info

2019-11, ISPOR Europe 2019, Copenhagen, Denmark

Code

PMH26

Disease

Medical Devices, Mental Health, Neurological Disorders

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