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Hospital ER Performance Metrics Dashboard

When I started this project, my goal was simple: create a dashboard that’s not just functional but also visually appealing—because who says data can’t look good? I used Figma to design the soft, pastel layout (my favorite color palette!) and then brought it to life in Power BI with interactive visuals and dynamic filters.


The purpose of this dashboard is to analyze key performance metrics for a hospital ER. From tracking patient demographics to visualizing wait times and satisfaction scores, this project highlights how data can provide actionable insights while remaining approachable and easy to explore.



The Process Behind the Dashboard

Creating this dashboard was a multi-step process that combined data generation, cleaning, visualization and design. Here's how I brought it all together:


  1. Dataset Creation: I started by generating the dataset in Mockaroo, where I specified the parameters needed for the project. These included fields like Patient ID, Patient Name, Visit Date (ranging from 2021 to 2024), Race, Department, Admission Status, Wait Time, Satisfaction Score, Gender and Age. Once the dataset was ready, I exported it as a CSV file and converted it to an XLSX file to better structure the table.

    Spreadsheet interface for Patient ER Data. Fields include Patient ID, Visit Date, Department, with options for input type and settings.

  2. Data Quality Check: Before moving forward, I performed a data quality check to ensure everything was clean and ready for analysis. I validated that there were no duplicates or blank values and confirmed that all data types were consistent—text columns were categorized as text, numerical fields as numbers, and so on. You can get the dataset here.


  3. Data Modeling and Analysis in Power BI: Next, I uploaded the dataset into Power BI, where the analytical work began. I created a Data Group to categorize patient ages into the ranges seen in the report. Then, I built calculated measures for the key metrics and visuals I wanted to include, like total patients, average wait times and satisfaction scores. At this stage, I laid out the visuals in a rough order to get a feel for the dashboard’s structure, knowing the design would refine things later.


  4. Designing the Dashboard: With the data structure in place, I shifted my focus to the dashboard's design. Using Figma, I explored a color palette that felt soft and approachable while staying professional. I designed the background layout, including the tiles and squares that frame the visuals, and exported this design as a wallpaper for Power BI.


  5. Final Touches: After uploading the design into Power BI, I aligned and formatted each visual to fit seamlessly within the layout, ensuring both functionality and aesthetic appeal. To complete the project, I customized elements like the Filter Pane, Tooltips and Header Icons to match the dashboard’s theme, creating a cohesive and polished user experience.


Here’s a preview of the final design before reviewing the insights!

Hospital ER performance metrics dashboard with graphs and data on patients by month, gender, race, department, day, and age range. Pink theme.


Results & Insights

This dashboard uncovers some interesting trends in ER performance, such as:

  • Friday is the busiest day of the week, seeing the highest number of patient visits.

  • The average wait time is 152.4 minutes, which may contribute to the relatively low satisfaction score of 5.49/10.

  • Over 50% of patients who visit the ER are admitted, indicating a significant proportion of high-severity cases.

  • The majority of patients are aged 60 and above, highlighting the importance of prioritizing elderly care.

  • Departmental data highlights Toxicology and Urology as receiving the highest number of patients, potentially indicating a growing need for specialized resources in these areas to address frequent emergencies effectively.



Explore the Dashboard

Take a moment to explore the embedded report below—sign into Power BI to interact with the dashboard and uncover insights yourself!


If you're curious to work with the data behind this dashboard, you can download the dataset here to analyze it on your own, or view the report directly here (access request required).


Disclaimer: All data used in this dashboard is randomly generated using Mockaroo and does not represent real patient information. This project is solely for demonstration and portfolio purposes.


Conclusion

This project was an incredible opportunity to combine design and analytics into a cohesive, user-friendly experience. I learned how to balance aesthetics with functionality, refine my skills in Power BI and Figma, and think critically about how to turn data into actionable insights.


From generating and cleaning the dataset to designing the dashboard and analyzing the results, this project reflects my passion for creating meaningful, visually engaging tools that make complex data easy to understand. It’s a rewarding process to see how design and analytics can come together to tell a story—and I’m excited to apply these skills to even more projects in the future!

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