Since the processes in the health-care domain deal with humans' life, the slightest deviation from the normal state can lead to irreparable damages to individuals and society. Therefore, monitoring the quality of the processes in this area has attracted many researchers’ attention. On the other hand, the introduction of new therapies for various diseases has made process monitoring difficult due to the lack of historical data. In this paper, the effect of heterogeneity of patient conditions (including gender, age, etc.) and treatment in different conditions (such as treatment with different therapist groups) has been considered using the accelerated failure time (AFT) regression model and the risk of each patient has been adjusted accordingly. Then, survival times of patients are monitored using a control chart based on the residual values of the AFT regression. Performance of the proposed control chart is evaluated using the average run length (ARL) criterion. The results indicate that the proposed method has a proper performance in identifying out-of-control status in processes in the health-care domain. The results showed that taking into account the therapist groups as well as increasing the number of in-control observations, increase the ability of the proposed control chart to detect shifts in the process.