This project features an interactive Microsoft Power BI dashboard that analyzes emergency room data for 9,216 patients across a 19-month period (April 2023 – October 2024). The dashboard empowers hospital administrators with real-time insights into patient trends, referrals, wait times, and more—driving data-informed decisions in critical care.
- Total Patients: 469
- Average Wait Time: 35.0 minutes
- Satisfaction Score: 4.63 / 5
- Referrals: 185 patients
- Top Age Group: 20–29 years
- Seen Within 30 Minutes: 57%
- Peak Time: Tuesday, 12 AM – 2 AM
- Total Patients: 9,216
- Average Wait Time: 35.3 minutes
- Satisfaction Score: 4.99 / 5
- Referrals: 3,816 patients
- Admissions: 50.04%
- Top Referral Departments:
- General Practice: 1,840
- Orthopedics: 995
- Peak Days: Monday, Saturday, Tuesday
- Peak Hours: 11 AM, 1 PM, 7 PM, 11 PM
Detailed patient data includes:
- ID, Name, Gender, Age, Race
- Wait Time, Referral Department, Admission Status
Supports audits, drill-downs, and individual case analysis.
- Most patients did not require referrals
- Dominant age groups: 20–39 years
- Race distribution: White > African American > Multiracial
- Gender and admission statuses are nearly balanced
- Identifies critical times for staffing and resource planning
- Power BI – Interactive dashboard development
- Excel / CSV – Data cleaning and preparation
- DAX – Custom metrics and calculated columns
- Optimizes emergency department resource management
- Enhances visibility of patient satisfaction trends
- Aids in real-time decision making
- Identifies operational bottlenecks
/Screenshots– Dashboard images/PBIX File– Power BI project file/Data– Sample dataset usedREADME.md– Documentation
Vishnu Sai Beere
GitHub Profile
For academic and educational use only. All data is anonymized. No real patient data is shared.