The increasing number of contaminants released into the environment necessitates innovative strategies for their detection and identification, particularly in complex environmental matrices like hospital wastewater. Hospital effluents contain both natural and synthetic hormones that might significantly contribute to endocrine disruption in aquatic ecosystems. In this study, HT-EDA has been implemented to identify the main effect-drivers (testosterone, androsterone and norgestrel) from hospital effluent using microplate fractionation, the AR-CALUX bioassay and an efficient data processing workflow. Through nontargeted screening, over 5000 features (ESI+) were initially detected, but our workflow’s prioritization based on androgenic activity prediction reduced the number of features requiring further analysis by over 95%, significantly streamlining the workload. In addition, the semiquantitative nontarget analysis allowed for the calculation of the contribution of an identified compound to the total activity of the sample without the need for reference standards. While this contribution was low (∼4.3%) and applicable to only one compound (1,4-androstadiene-3,17-dione), it presents the first approach for calculating such contributions without relying on standards. Compared to the available alternatives our workflow demonstrates clear environmental relevance by enhancing HT-EDA for more efficient identification and prioritization of effect-drivers in hospital effluents, and it can be adapted to address other environmental threats in complex mixtures.