OBJECTIVES : Depression is the most common mental health condition in the general population and its medication represents a substantial cost for the society. The aim of this study was to determine the average monthly antidepressant and antipsychotic drug prescription for patients diagnosed with depression and estimate the costs of their pharmaceutical treatment in Hungary, based on electronic medical records (EMR) collected in a tertiary hospital.

METHODS : Full set of EMRs of a virtual patient cohort diagnosed with depression (under F32 and F33 ICD10 codes) in the year of 2018 was analyzed in an anonymized form. Patients taking only antidepressant drugs were separated from patients taking an antidepressant (AD) and antipsychotic (AP) combination. Cost was calculated by multiplying the monthly volume of the prescribed drug use by the gross public price available from the Hungarian Public Drug Price registry (PUPHA).

RESULTS : In case of mono antidepressant therapy, based on 284 patients and their 384 cases, 17 different active compounds and 90 different formularies were applied. The most frequently prescribed active compound was escitalopram (ATC-N06AB10). In combination therapy, based on the data of 124 patients and their 200 cases 106 different formularies were used (59-ADSs and 47-APs), representing 20 different active compounds (13-ADs and 7-APs). The most commonly prescribed AD and AP active compound were escitalopram (ATC-N06AB10) and quetiapine (ATC-N05AH04) respectively. Result were cross validated with the national drug prescription database. The monthly average cost of mono AD and combination of AD plus AP therapy was 8.24 EUR and 20.04 EUR (1 EUR=350HUF) respectively.

CONCLUSIONS : Based on drug prescription recorded in the EMR the patient level resource use and cost calculation is feasible and attainable in a selected patient population. Thus, cost calculation required for economic modelling of health technologies can be supported by EMR based real-world data.