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Hα emission from point-like sources can be associated to different stellar populations, spanning various evolutionary stages. Therefore, population studies play a key role towards a better understanding of the evolution of our Galaxy; an enhancement of the list of identified Hα-excess sources can foster such analyses. We present a new stellar population-based identification of Hα-excess candidates that hinges on Gaia and IPHAS photometric data, as well as on Gaia astrometric measurements, to select Hα-bright outliers in the Northern Galactic Plane. The outlier selection is performed on a subset-by-subset basis, after that the objects are partitioned in the Gaia colour-absolute magnitude space and in the Galactic coordinate space, independently; these diverse approaches are meant to minimise the selection biases due to stellar population mixing and due to different extinction, respectively. Each target in the data set is associated to two significance parameters σ (one for each partition type) that quantify the confidence that the object being studied is an Hα-outlier, with respect to the other objects in the corresponding partition. The applied algorithm selects 28,496 Hα-excess candidates out of 7,474,835 objects in the data set, with a significance higher than 3 (3σ outliers). The completeness fraction relative to this Hα-excess identification is between 3% and 5%, which constitutes a significant improvement with respect to previous similar studies. The purity fraction of the suggested, more conservative, 5σ selection is 81.9%. The purity and completeness fractions are obtained via a visual inspection of the corresponding LAMOST spectra.