Sawsan As-Sanie, MD

Dr. As-Sanie is an Associate Professor and the Director of the Minimally Invasive Gynecology Fellowship in the Department of Obstetrics and Gynecology. She is also the Director of the University of Michigan Endometriosis Center.

Dr. As-Sanie is an AOA graduate of the Johns Hopkins School of Medicine in 1998 and completed her residency in OB/GYN at MetroHealth Medical Center and the Cleveland Clinic Foundation in 2002. Following residency, she completed a three year clinical and research fellowship in Advanced Laparoscopic Surgery and Chronic Pelvic Pain at the University of North Carolina. During this time, she also received her MPH in epidemiology. She has extensive training in advanced laparoscopic and robotic surgery, as well as endometriosis-related chronic pelvic pain. Dr. As-Sanie is a Fellow of the American College of Obstetricians and Gynecologists and has achieved a Focused Practice designation in Minimally Invasive Gynecologic Surgery from the American Board of Obstetrics and Gynecology.

Dr. As-Sanie is dedicated to the health care of women with complex gynecologic disorders, including uterine fibroids, abnormal bleeding, ovarian masses, endometriosis, and chronic pelvic pain. She strives to listen to the concerns and needs of each unique patient, and will work with each woman to create a treatment plan that is best for her situation. If surgery is necessary, a minimally invasive approach is emphasized so that her patients can return to their families and usual activities as quickly as possible.

Dr. As-Sanie specializes in Minimally Invasive Gynecologic Surgery & Robotic Surgery (hysterectomy, myomectomy), endometriosis, chronic pelvic pain, uterine fibroids, and hysterectomy alternatives.

University of Michigan Health participates with most health insurance plans.

Dr. As-Sanie's primary research interests are aimed at defining the underlying mechanisms involved in the initiation and maintenance of endometriosis-related pelvic pain. She is particularly interested in developing methods to predict treatment outcomes, to help guide patients and physicians when making treatment choices.