Healthcare Workforce Analytics using SQL

Project Overview

Healthcare organizations often struggle with employee burnout, rising stress levels, mental health absenteeism, and employee turnover. These issues can negatively impact workforce productivity, employee well-being, and patient care.

This project analyzes a healthcare workforce dataset using MySQL to identify key factors contributing to employee stress, burnout, mental health absences, and turnover intention. The analysis provides actionable insights that can help HR teams make data-driven decisions to improve employee retention and workplace well-being.

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Business Problem

The HR department wants to answer the following questions:

• Which departments have the highest employee stress?
• Which employee roles experience the most burnout?
• Does high stress lead to higher burnout?
• Do burnout and stress increase mental health absences?
• Which workplace factors contribute most to employee dissatisfaction?
• Which employees are at the highest risk of leaving?
• Which departments require immediate HR intervention?

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Dataset Information

The dataset contains employee information from a healthcare organization, including:

• Employee ID
• Employee Type
• Department
• Workplace Factor
• Stress Level
• Burnout Frequency
• Job Satisfaction
• Access to Employee Assistance Programs (EAPs)
• Mental Health Absences
• Turnover Intention

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Tools Used

• MySQL Workbench
• SQL

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SQL Concepts Demonstrated

This project covers a wide range of SQL concepts, including:

• SELECT
• WHERE
• GROUP BY
• HAVING
• ORDER BY
• Aggregate Functions (COUNT, AVG)
• CASE Statements
• Subqueries
• Common Table Expressions (CTEs)
• Window Functions
  • RANK()
  • DENSE_RANK()
  • ROW_NUMBER()
• Views

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Analysis Performed

1. Data Exploration

• Count total employees
• Check duplicate Employee IDs
• Understand workforce distribution
• Calculate average job satisfaction
• Calculate average mental health absences

2. Stress Analysis

• Employees with high stress
• Stress by department
• Stress by employee type
• Workplace factors contributing to stress
• Employees with maximum stress levels

3. Burnout Analysis

• Burnout by department
• Burnout by employee type
• Relationship between stress and burnout
• Burnout vs Job Satisfaction
• Burnout vs Mental Health Absences

4. Mental Health Analysis

• Average absences by department
• Average absences by employee type
• Employees above average absences
• Top employees with highest absences
• Relationship between stress, burnout and absences

5. Turnover Analysis

• Turnover by department
• Turnover by employee type
• Stress vs Turnover
• Burnout vs Turnover
• Job Satisfaction vs Turnover
• EAP Access vs Turnover
• Workplace Factors vs Turnover

6. Advanced SQL Analysis

• Employee Risk Score
• Top 10 High-Risk Employees
• Ranking departments using Window Functions
• Top employees within each department using ROW_NUMBER()
• Department Summary View

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Key Business Insights

The analysis helps HR identify:

• Departments experiencing the highest stress levels
• Employee roles with frequent burnout
• Workplace factors affecting employee well-being
• Employees with excessive mental health absences
• Factors influencing employee turnover
• High-risk employees requiring immediate HR attention

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Project Outcome

Using SQL, this project transforms raw healthcare employee data into meaningful HR insights that can support:

• Employee retention strategies
• Mental health initiatives
• Burnout reduction programs
• Better workforce planning
• Data-driven HR decision making

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Files Included

• Healthcare_sql_Analysis.sql

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## Author

**Sumedh Patil**

Aspiring Data Analyst skilled in SQL, Excel, and Power BI, focused on solving business problems through data analysis.