Smart HealthCare Scheduler

The key issue of the day is the management of health service, and waiting time is rising in all the hospitals and clinics. To avoid this kind of issue, many programs have been introduced by the hospitals, but they are always managed through some sort of arrangement. To overcome this problem and make the patient feel relaxed and calm while undergoing treatment, a long-term solution is required. For the modern healthcare setting to function effectively, efficiency and patient acceptance are required. In most developing countries, the outpatient population is severely challenged. In our Smart HealthCare Scheduler project, HPTDT is proposed to enhance scheduling efficiency and reduce reaction time by rapidly determining whether a patient is normal or in a critical condition. The HP-TDT scheduling technique contains three phases, which include registration, data gathering, and scheduling. The OAH model is applied during the registration process to reduce the response time up to key generation. Next, the PDC algorithm is used for performing the data gathering phase. Due to the consideration of a number of operations that occur within the data gathering, PDC reduces the overhead of computation. Lastly, two-factor, entropy and information gain based on the decision tree are used for scheduling. Therefore, the efficiency of the scheduling is improved through categorization of patients into normal and critical statuses. The crucial efficiency of scheduling is therefore increased while the response time and computational overhead are decreased with the proposed approach.