On the hospital floor, prompt detection and appropriate treatment of clinical deterioration of ward patients are essential for successful rescue. In this paper, a continuous time Markov chain model is presented to describe the ward patient status and analyze the patient rescue processes, which are characterized by the transitions between different patient states, such as risk, non-risk, intervention by care providers (nurse, physician, rapid response team), or elevation to intensive care, etc. Closed formulas to calculate the probability of the patient in different states are developed for single patient case. A system-theoretic method, referred to as shared resource iteration (SRI), is developed to study the multiple patients scenario. It is justified that such an iterative method is convergent and results in a high accuracy in estimation of patient state probabilities through numerical experiments. Moreover, monotonic properties have been investigated to provide guidance for continuous improvement.