A Real-Time Access Control of Patient Service in the Outpatient Clinic

With the increasing demand of patients for limited healthcare services, e.g., expert physicians in general hospitals and the long on-site waiting time of patients, a real-time admission control (AC) policy was developed considering both distinction and fairness among heterogeneous patients. The AC policy chooses the customer for the next service from the waiting area to minimize the expected total disutility according to the current system state. A continuous-time Markov decision process in a finite horizon was developed, and a myopic optimal policy was derived using a switching curve to discriminate patient admission based on patient types and waiting time. The effect of each parameter on the switching curve is analyzed, and managerial insights are discussed. In the numerical experiment, an empirical case in the Pediatric Department of Peking University Third Hospital is conducted using simulation models. Three commonly used scheduling policies and the myopic policy (MP) are tested in both Markovian settings and a real-world scenario. Simulation results confirm the effectiveness of the MP, because the total disutility of patients is significantly alleviated. Furthermore, the service experience of patients is expected to improve with the application of the AC policy.