Healthcare Data Analysis Project
Healthcare Data Analysis Project
In a recent project, I delved into the complexities of scheduling and logistical inefficiencies at an infusion center, aiming to uncover the root causes behind patient tardiness for their appointments, suboptimal chair utilization, and the impact of preceding appointments on subsequent infusion treatment delays. Employing advanced data analysis tools such as Python for data manipulation and analysis, along with powerful libraries like Seaborn, NumPy, and Matplotlib for in-depth statistical analysis and visual representation, I meticulously analyzed appointment schedules, patient flow, and chair occupancy rates to determine the root causes of the issues, and developed recommendations based off of that insight.
In a recent project, I delved into the complexities of scheduling and logistical inefficiencies at an infusion center, aiming to uncover the root causes behind patient tardiness for their appointments, suboptimal chair utilization, and the impact of preceding appointments on subsequent infusion treatment delays. Employing advanced data analysis tools such as Python for data manipulation and analysis, along with powerful libraries like Seaborn, NumPy, and Matplotlib for in-depth statistical analysis and visual representation, I meticulously analyzed appointment schedules, patient flow, and chair occupancy rates to determine the root causes of the issues, and developed recommendations based off of that insight.
Cleansed/analyzed large data set using Pandas, Jupyter Notebook, Numpy
Created informative data visualizations using Seaborn, Matplotlib, Tableau
Crafted and presented slide deck with recommendations for infusion center operational improvements
