Clinical practice guidelines (CPGs) are statements relating to evidence-based and economi-cally reasonable medical treatment processes (MTPs)for certain clinical circumstances.The executable MTPs in healthcare information systems can assist the clinical processes.In our previous work,several treat-ment patterns and their modeling proposals were pro-posed to reduce the effort spent in modeling MTPs.However,given a CPG document,all the process ele-ments are modeled manually.Besides,business pro-cess mining can extract MTP models automatically from execution logs.However,the existing process mining algorithms focus on the control-flow of struc-tured processes.This paper proposes an integrated framework for modeling executable MTPs based on process mining and treatment patterns,taking both the efficiency of mining and the quality of modeling into account.In this framework,an execution log process-ing approach is presented to identify the subsequences and decision points conforming to the treatment pat-terns and represent them with abstract activities.Ex-periments on a synthetic log of the non-secondary hy-pertension MTP and empirical findings demonstrate the effectiveness of our approach.The results show that the process mining in our approach framework can automatically generate more accurate MTP mod-els,and the subprocess models based on treatment pat-terns make the models easy to understand.