Modeling and incorporating idiosyncratic preferences of patients (risk aversion, bounded rationality, asymmetric aversion to information, risk communication, rational inattention, etc.) is ubiquitous in building multi-period/dynamic decision-making models for personalized medical and health care. Additional difficulties for the construction of such models come from the interaction of uncertainty and time, as updated information becomes progressively available over the course of a treatment, recovery, pregnancy, etc.. In my talk, I will introduce representative decision-making models for cases arising in OB-GYN, present the related optimization problems and discuss the associated conceptual, methodological and computational difficulties in solving them.