We study the behavioral processes undergirding physician forecasts, evaluating accuracy and systematic biases in estimates of patient survival and characterizing physicians' loss functions when it comes to prediction. Similar to other forecasting experts, physicians face different costs depending on whether their best forecasts prove to be an overestimate or an underestimate of the true probabilities of an event. We provide the first empirical characterization of physicians loss functions. We find that even the physicians subjective belief distributions over outcomes are not well calibrated, with the loss characterized by asymmetry in favor of over-predicting patients' survival. We show that the physicians' bias is further increased by (1) reduction of the belief distributions to point forecasts, (2) communication of the forecast to the patient, and (3) physicians own past experience and reputation.