Naive clinical capacity planning, myopic appointment scheduling techniques, and unavoidable appointment interruptions lead to excessive patient waiting time, physician idle time and overtime, which result in inefficient use of clinical resources, increased clinical costs, untimely access to care, decreased continuity of care, and dissatisfied patients. Previous research have found that efficient appointment scheduling methods may significantly improve both patient and clinic related outcomes. Furthermore, the concept of patient-centered medical home (PCMH) has become one of the predominant models of health care delivery in the last two decades. PCMH is a proactive and team based approach to care, which places the patient at the center of care and benefits from data analytics to make informed clinical decisions. Motivated by PCMH principles, this dissertation research aims to investigate patient-centered appointment scheduling in physician clinics. More specifically, we address the following problems: 1) primary care capacity planning for open-access appointment systems; 2) adaptive appointment scheduling for patient-centered medical homes; 3) managing interruptions in appointment schedules in physician clinics. To solve these problems, we use stochastic optimization and simulation optimization. Our patient-centered capacity planning, appointment scheduling, and appointment interruption management strategies provide significant value in terms of both operational and patient oriented performance measures.