HealthData IQ

HealthData IQ is a comprehensive data analysis project that explores healthcare facility information across the United States. The project includes robust data cleaning, exploratory data analysis (EDA), statistical analysis, and SQL-based querying to derive meaningful insights from hospital-level data.

👥 Team Members

Name	Role	Responsibilities
Vaibhav Pandey	Team Leader	Data Cleaning, EDA
Niladribhushan Chaturvedi	Team Member	Statistical Analysis, SQL Queries

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📊 Project Overview

The project focuses on analyzing various hospital attributes such as:

• Overall hospital ratings
• Readmission and mortality rates
• Geographic distribution of hospitals
• Performance comparisons across states and counties

The goal is to empower stakeholders with key insights into healthcare quality and accessibility.

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🧹 Data Cleaning & Preparation

Performed by Vaibhav Pandey:

• Removed duplicates and missing values
• Standardized categorical variables
• Merged datasets to consolidate useful columns
• Filtered out incomplete or invalid rows
• Ensured consistency in numerical columns for rating and scoring

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📈 Exploratory Data Analysis (EDA)

Conducted to understand:

• Distribution of hospital ratings
• State-wise and county-wise hospital performance
• Patterns in readmissions, mortality, and survey scores
• Correlations between patient survey scores and hospital performance

EDA was primarily visualized using:

• Histograms
• Boxplots
• Bar charts
• Correlation heatmaps

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📐 Statistical Analysis

Performed by Niladribhushan Chaturvedi:

• Hypothesis testing on hospital rating distributions
• ANOVA to compare ratings across multiple states
• Z-tests and t-tests to analyze mortality/readmission impacts
• Summary statistics to support insights from EDA

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🗃️ SQL Queries

Implemented by Niladribhushan Chaturvedi, SQL was used to extract deeper insights from the cleaned dataset.

Key queries include:

1. Hospitals above average rating
2. Top 5 cities by hospital count
3. Best hospitals per county
4. States with average rating below 3.5
5. Lowest rated hospitals in each state

📄 Full SQL script available: HealthLensIQ-SQL.sql

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📁 Repository Structure

HealthData-IQ/ │ ├── HealthData IQ.ipynb # Complete analysis notebook ├── Cleaned_HospInfo_Final.xls # Cleaned and prepared dataset ├── HealthLensIQ-SQL.sql # SQL queries for insights └── README.md # Project documentation

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🧰 Tools & Technologies Used

• Python (Pandas, NumPy, Matplotlib, Seaborn, SciPy, Statsmodels)
• Jupyter Notebook
• Microsoft Excel
• SQL (SQLite/MySQL)
• Git & GitHub

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💡 Key Insights

• Several states have average hospital ratings below acceptable thresholds.
• City-wise distribution shows significant concentration in certain urban areas.
• Patient satisfaction scores often correlate with higher hospital ratings.
• Statistical analysis validates rating disparities across regions.

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📫 Contact

For queries or collaboration, feel free to connect:

• Vaibhav Pandey: GitHub
• Niladribhushan Chaturvedi: LinkedIn