Since recent years, smartphone-based color imaging systems are increasingly applied for Neonatal jaundice detection applications. The systems are mostly performing the estimation of bilirubin concentration levels based on the correlation of newborns' skin colour images with that of total serum bilirubin (TSB) and transcutaneous bilirubinometry (TcB) measurements. However, the colour reproduction capacity of smartphone cameras are known to be influenced by various factors resonated from the technological and acquisition process variabilities. For an accurate bilirubin estimation, despite the type of smartphone and illumination conditions used to capture the newborns' skin images, a complete model, or data set, which can represent all the possible real world acquisitions scenarios has to be utilized. Due to various challenges in generating such a model or a data set, some solutions opt towards the application of reduced data set (designed for reference conditions and devices only) and colour correction systems (for the transformation of other smartphone skin images to the reference space). Such approaches will make the bilirubin estimation methods to be highly dependent on the accuracy of their employed colour correction systems, in their capability to reducing device-to-device colour reproduction variability. However, the state-of-the-art methods with similar methodologies usually were only evaluated and validated on a single smartphone camera. But the vulnerability of the systems to wrong jaundice diagnosis can only be shown with a thorough investigation of the colour reproduction variability for extended number of smartphones and illumination conditions. Accordingly, this work presents and discuss the results of such broad investigation, including the evaluation of seven smartphone cameras, ten light sources, and three different colour correction approaches. The overall results show statistically significant colour differences among devices, even after color correction applications, and that more control and caution is required in the application of smartphone devices for skin colour based jaundice diagnosis.