Purpose: Congenital heart defects involve pathologies in which the heart has only one functional pumping chamber. In these conditions, treatments consist of three procedures where stage 1 occurs just after birth and links the systemic and pulmonary circulations through an artificial shunt. Computational fluid dynamics is a tool to explore hemodynamics in patient-specific simulations, and understand specific physiopathologies. Representative hemodynamics models are built based on imaging data for example to explore several virtual surgical options. In this context, the specification of boundary conditions is necessary to compute pressure and flow in the entire domain. However, these boundary conditions are rarely the measured variables. Besides, to take into account the rest of the circulation outside of the three-dimensional modeled domain, a number of reduced order models exist. Methods: In this work a method is presented to iteratively but automatically tune from clinically measured hemodynamics data reduced model parameters. Target pressures such as minimum, maximum or average over one or both lungs are considered, depending on the clinical measurement. A 5-parameter model representing more specifically the arterial and venous pulmonary circulation is proposed. Results: The methodology is demonstrated with six stage 1 patient specific models: the clinical target data are well matched, except for one case where clinical data were incoherent. Inhomogeneous pressure, swirling blood flow patterns and very high wall shear stress 3D maps highlight similarities and differences among patients. Steady and pulsatile tuning results are similar. Conclusions: The highly complex fluid dynamics of this stage is for the first time analyzed around the distal systemic-to-pulmonary shunt anastomosis and the connected pulmonary arteries. The distal vasculature of each outlet is better represented than previously. This work demonstrates how simulations can help to check the coherence of the clinical data or provide insights to clinicians that are otherwise difficult to measure, such as in the presence of kinks. A strategy for the case of incoherent clinical data is proposed to match the data. Finally, the choice of steady versus pulsatile tuning, limitations and possible extensions of this work are discussed.