This research focuses on the Oncology Outpatient Department of a leading private Healthcare (OPD) which has been experiencing prolonged waiting which is currently causing problems in patient satisfaction and operational inefficiencies. The primary inefficiencies in chemotherapy patient care are the following: inadequate allocation of resources, administrative burden, and inefficient communication. To address this, the study suggests incorporating AI-powered chatbots in scheduling automation, a token system in digital form, and adequate staffing during peak periods. This proposal also features the preferential treatment of female patients through the token system in order to meet specific demands. In this regard, this study intends to apply the M/M/s queuing model with the aim of making optimal usage of resources, streamlining patient flow, and ultimately reducing delay. It is further integrated with pre-verification of insurance details that accelerate registration and remove administrative barriers. The findings are such that these measures can work in tandem to improve operational efficiency, reduce waiting times, and enhance the overall patient experience in the Oncology OPD.