Project Overview

Goal

Process

Key Insights

The goal of this project was to identify the key aspects of hospital care that most significantly influence hospital rating and recommendation scores and to explore how these scores vary geographically across U.S. counties. By understanding the drivers of patient satisfaction, hospital administrators can prioritize high-impact areas to improve patient trust, financial performance, and operational success. Public health officials can improve patient outcomes, allocate resources more effectively, and address systemic inequalities in care quality by studying counties with the best rating and recommendation scores.

• Sourced the “Patient Survey (HCAHPS) - Hospital” dataset from the Centers for Medicare & Medicaid Services, covering inpatient experiences from April 1, 2023, to March 31, 2024.
• Utilized MySQL to clean the data—handle missing values, fix formatting issues, and create a new table to remove unusable rows to enhance data processing efficiency.
• Integrated U.S. county population data (2024) from the U.S. Census Bureau to assess geographical trends.
• The dataset was exported to Excel after extracting key hospital performance measures to create a correlation matrix and perform a regression analysis to determine which factors have the strongest effect on hospital rating and recommendation scores. The results were visualized in Excel to highlight the strongest predictors of these scores.
• Designed interactive dashboards using Tableau to visualize geographic patterns of hospital scores by county across small, medium, and large counties.

1. Care Transition, Nurse Communication, and Doctor Communication have the largest effect on hospital Rating and Recommendation scores.
2. Counties with higher hospital rating scores generally also reported higher recommendation scores, while counties with lower ratings tended to have lower recommendation scores, showing a strong alignment between the two measures.
3. Hospitals in counties with a small population size have the highest Rating and Recommendation scores.

1st Insight: Care Transition, Nurse communication, and Doctor Communication have the largest effect on hospital Rating and Recommendation scores.

Correlation Analysis

• Care Transition (r = 0.89), Nurse Communication (r = 0.88), and Doctor Communication (r = 0.81) had the strongest positive correlation with Hospital Rating.
• Care Transition (r = 0.87), Nurse Communication (r = 0.82), and Doctor Communication (r = 0.77) had the strongest positive correlation with Hospital Recommendation.

The 3 Most Influential Factors on Overall Rating

Based on regression analysis (R² = 86%), the strongest predictors of higher hospital ratings are:

• Care Transition has the single biggest impact on ratings.
• Nurse Communication is the second strongest driver—nearly 3x more impactful than doctor communication.
• R Square (0.86 or 86%): This means that 86% of the variability in Overall Ratings is explained by the various factors of hospital care.

The 3 Most Influential Factors on Recommendation Score

Based on Regression analysis (R² = 78%), the strongest predictors of hospital recommendation scores are: