In this project, I analyzed real hospital discharge data from New York State, categorized by county and hospital. The goal was to understand the factors contributing to extended hospital stays, which in turn increase healthcare costs. After cleaning and preparing the dataset, I developed interactive Power BI dashboards to visualize key metrics such as length of stay, patient demographics, diagnosis types, and treatment procedures.
The analysis revealed that patients with more severe conditions and those undergoing surgical procedures tended to have longer hospital stays, leading to higher costs. Additionally, factors like patient age (with individuals over 70 years old) and the type of admission (e.g., emergency or urgent) were closely linked to extended stays. Geographic variations between counties and specific hospitals also played a role in patient outcomes and cost variations.
The interactive dashboards provided insights into these patterns, allowing healthcare administrators and policymakers to explore the data and make informed decisions. Ultimately, this project helped identify opportunities to reduce the length of hospital stays, optimize resource allocation, and manage healthcare costs more effectively, with a focus on improving both efficiency and patient care.
Download the data frames here!
