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@article{183665,
        author = {Saumyadip Sasmal},
        title = {A REPORT ON UTILIZATION OF DATA ANALYTICS FOR IMPROVING OPD EFFICIENCY},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {4018-4027},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183665},
        abstract = {Outpatient Departments (OPDs) are critical touchpoints in any hospital setting, serving as the first line of interaction between patients and healthcare providers. However, OPDs often suffer from operational inefficiencies, such as long waiting times, poor scheduling, and uneven doctor workloads, which affect both patient satisfaction and service delivery. The primary aim of this research is to explore how data analytics can be leveraged to identify inefficiencies in OPD operations and recommend actionable strategies for improvement.
This study adopts a quantitative, descriptive-analytical research design, utilizing historical data from hospital OPD records, including appointment schedules, patient counts, consultation durations, and waiting times. Data was collected over a period of 3 to 6 months and analyzed using tools such as Microsoft Excel, Python (Pandas, Scikit-learn), and visualization platforms like Power BI. Techniques such as descriptive analytics were used to examine current trends in patient flow, while predictive analytics helped forecast peak periods and potential bottlenecks. Prescriptive analytics were employed to recommend optimized staff allocation and patient scheduling frameworks.Here are Some keywords for research on "Utilization of Data Analytics for Improving OPD Efficiency":},
        keywords = {OPD Efficiency, Data Analytics, Healthcare Operations, Patient Waiting Time, Hospital Management, Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, Appointment Scheduling, Patient Flow Optimization, Outpatient Department, Health Informatics, Load Balancing, Patient Satisfaction, Real-time Monitoring, Doctor Workload Management, Healthcare Data, Operational Challenge},
        month = {August},
        }