Healthcare Dashboard
Data visualization project analyzing hospital readmission trends by diagnosis, treatment, and patient demographics to identify high-risk groups and improve care outcomes.
Key Features
- Analysis of readmission rates by length of hospital stay
- Identification of high-risk age groups and diagnoses
- Evaluation of A1C test results to assess diabetes management
- Interactive filters for age, diagnosis, and emergency visits
- Reference lines to highlight averages across all stay durations
Technologies Used
Tableau
SQL
Data Visualization
Healthcare Analytics
Results
- Identified 7–9 day stays had highest readmission rate at 51%
- Discovered patients without A1C testing had 47% readmission rate
- Found older age groups (70–90) had highest readmission rates
- Highlighted top diagnoses with highest readmission numbers
Dashboard Overview
Readmission by Diagnosis & Age
Readmission by Treatment & Stay
Project Takeaways