This work presents an early analysis of a targeted survey aimed at studying domain specialists’ perceived complexity of process models describing various healthcare procedures. Process models with varying levels of information generated from real-world datasets are evaluated by healthcare professionals via a targeted survey to assess their implicit perceptional state via human interpretable metrics; understandability, correctness and usability. While, explicit descriptive metrics (Precision, Generalization, Replay Fitness and Simplicity) of respective process models were generated and contrasted against current survey results to investigate the behavior and collective perceiving state of the domain expert during model interpretation. Current results provide several insights into the predictability of perceived complexity with available formal metrics and give a broad basis for further analysis of the user’s perceptional state during the survey.