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DIGITAL PAYMENT TRANSACTION TRENDS DASHBOARD
Patient waiting time is an important operational measure used to understand the efficiency of healthcare services. Long waiting periods may occur because of high patient volume, appointment delays, registration procedures, limited staff availability, or inefficient service workflows. Analyzing waiting-time information can help healthcare facilities understand where delays occur and identify areas that require improvement. The Patient Wait-Time Analysis system is designed to collect, process, analyze, and visualize patient-flow and waiting-time information. The system can use data such as patient arrival time, registration time, appointment time, consultation start time, department, doctor, and service completion time. These records are processed to calculate individual and overall waiting durations. The system analyzes important measures such as average waiting time, minimum waiting time, maximum waiting time, patient volume, service duration, and department-wise performance. Waiting-time trends can be examined across different dates, time periods, departments, doctors, and service stages. Peak hours can also be identified by analyzing patient arrival patterns and waiting-time variations. An interactive dashboard can present the analyzed information using charts, graphs, tables, and key performance indicators. Users can apply filters to examine specific departments, doctors, dates, or service stages. This makes it easier to identify departments or periods where patients experience longer waiting times. Overall, the project demonstrates how data analytics and visualization can support healthcare operational management. The system provides a centralized method for understanding patient-flow patterns and service delays. The insights generated from the analysis can support better scheduling, staff allocation, resource planning, and service monitoring. Therefore, the Patient Wait-Time Analysis system provides a useful analytical approach for improving healthcare service efficiency and reducing unnecessary patient waiting.
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