This project involves a comprehensive analysis of a Hospital Emergency Room's operational data using Excel for data processing and Power Pivot. The goal was to build an interactive dashboard to visualize key performance indicators (KPIs), monitor patient flow, and identify areas for improving efficiency and patient satisfaction. The dashboard provides stakeholders with actionable insights for better decision-making and resource management.
- Analyze and visualize patient admission rates (Admitted vs. Not Admitted).
- Track and evaluate patient wait times and the percentage of patients seen within the target time.
- Measure and report on patient satisfaction scores.
- Understand patient demographics through age group and gender distribution analysis.
- Identify the most common departments for patient referrals from the ER.
- Create a dynamic, user-friendly dashboard for monthly reporting and trend analysis.
The sourced dataset for this project:
- Dataset Link: Hospital ER Dataset
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Project Workflow
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Key Charts & Visualizations
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Core Key Performance Indicators (KPIs)
- Patient Volume: The ER handled a total of 513 patients during the analyzed period.
- Admission Rate: A slight majority of patients (52.4%) were admitted for further treatment, while 47.6% were treated and discharged from the ER.
- Operational Timeliness: Only 38.4% of patients were seen within the target wait time of 30 minutes, indicating a significant area for improvement in patient flow.
- Patient Satisfaction: The average patient satisfaction score was 4.96, suggesting room for enhancement in the patient experience.
- Demographics: The patient age group was fairly distributed, with the highest number of patients (72) belonging to the 0-9 years bracket. The gender distribution was nearly equal.
- Referral Trends: The majority of patients (299) did not require a referral to a specialty department. Among those who did, General Practice was the most common referral department (103 referrals), followed by Orthopedics (65).
This Hospital ER Dashboard identifies patient wait times as the key area for improvement, providing clear insights to enhance operational efficiency and patient satisfaction.
This end-to-end dashboard project highlights my ability to solve business problems with data, demonstrating key data analyst skills in Excel, data modeling, and visualization. I welcome any questions, feedback, or opportunities to collaborate.
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