Background: In a previous single center study we found that a standardized drug treatment algorithm (ALGO) was more cost effective than treatment as usual (TAU) for inpatients with major depression. This report aimed to determine whether this promising initial finding could be replicated in a multicenter study.
Methods: Treatment costs were calculated for two time periods: the study period (from enrolment to exit from study) and time in hospital (from enrolment to hospital discharge) based on daily hospital charges. Cost per remitted patient during the study period was considered as primary outcome.
Results: 266 patients received ALGO and 84 received TAU. For the study period, ALGO costs were significantly lower than TAU (ALGO: 7 848 ± 6 065 €; TAU: 10 033 ± 7 696 €; p = 0.04). For time in hospital, costs were not different (ALGO: 14 734 ± 8 329 €; TAU: 14 244 ± 8 419 €; p = 0.617). Remission rates did not differ for the study period (ALGO: 57.9%, TAU: 50.0%; p=0.201). Remission rates were greater in ALGO (83.3%) than TAU (66.2%) for time in hospital (p = 0.002). Cost per remission was lower in ALGO (13 554 ± 10 476 €) than TAU (20 066 ± 15 391 €) for the study period (p < 0.001) and for time in hospital (ALGO: 17 582 ± 9 939 €; TAU: 21 516 ± 12 718 €; p = 0.036).
Limitations: Indirect costs were not assessed. Different dropout rates in TAU and ALGO complicated interpretation.
Conclusions: Treatment algorithms enhance the cost effectiveness of the care of depressed inpatients, which replicates our prior results in an independent sample.
Keywords: Cost effectiveness analysis; Depression; Health economy; Treatment algorithm.
Copyright © 2017. Published by Elsevier B.V.