🚀 Data Analyst Project Series – Part 7

Healthcare Data Analysis Project

🎯 Project Goal 
The goal of this project is to analyze healthcare data and discover insights related to: 
• Patient trends
• Hospital performance
• Disease analysis
• Treatment costs
• Patient satisfaction
• Resource utilization

Healthcare Analytics is one of the fastest-growing fields in Data Analytics because hospitals and healthcare organizations rely heavily on data-driven decisions. 

This project is widely used in: 
• Hospitals
• Clinics
• Health insurance companies
• Pharmaceutical companies
• Public health organizations

🛠 STEP 1: Choose the Dataset 
Recommended Dataset Types 
Search on Kaggle: 
• Healthcare Dataset
• Hospital Management Dataset
• Patient Records Dataset
• Medical Cost Dataset

📂 STEP 2: Understand the Dataset 

Common Columns 
Column Name : Meaning 
Patient ID : Unique patient identifier 
Age : Patient age 
Gender : Male/Female 
Disease : Diagnosed illness 
Admission Date : Hospital admission date 
Discharge Date : Hospital discharge date 
Doctor : Assigned doctor 
Treatment Cost : Total treatment expense 
Insurance : Insurance coverage 
Hospital Department : Department name 
Patient Satisfaction : Satisfaction rating 

🧹 STEP 3: Data Cleaning 
Healthcare data is sensitive and must be highly accurate. 

✔ Cleaning Tasks 
Remove Duplicate Patient Records 

Check: 
• Duplicate Patient IDs

Handle Missing Values 
Common missing fields: 
• Disease
• Treatment Cost
• Satisfaction Scores

Methods: 
• Replace missing values
• Remove incomplete records carefully

Standardize Disease Names 
Example: 
• “Diabetes”
• “diabetic”
• “DM”

Convert into a standard format. 

Correct Date Formats 
Examples: 
• Admission Date
• Discharge Date

Convert into proper date formats. 

📊 STEP 4: Define Healthcare KPIs 

Essential KPIs 

✔ Total Patients 
COUNT(Patient_ID) 

✔ Average Treatment Cost 
AVG(Treatment_Cost) 

✔ Average Hospital Stay 
Purpose: 
Measures average patient hospitalization duration. 

✔ Patient Satisfaction Score 
AVG(Patient_Satisfaction) 

✔ Insurance Coverage Percentage 
Purpose: 
Measures healthcare insurance utilization. 

🗄 STEP 5: Analyze Healthcare Data Using SQL 
📌 SQL Query Examples 

1. Most Common Diseases
SELECT Disease,
       COUNT(*) AS Total_Cases
FROM Patients
GROUP BY Disease
ORDER BY Total_Cases DESC
LIMIT 10;

2. Department-wise Patient Count
SELECT Hospital_Department,
       COUNT(*) AS Patient_Count
FROM Patients
GROUP BY Hospital_Department
ORDER BY Patient_Count DESC;

3. Average Treatment Cost by Disease
SELECT Disease,
       AVG(Treatment_Cost) AS Avg_Cost
FROM Patients
GROUP BY Disease
ORDER BY Avg_Cost DESC;

4. Monthly Patient Admissions
SELECT MONTH(Admission_Date) AS Month,
       COUNT(*) AS Admissions
FROM Patients
GROUP BY MONTH(Admission_Date)
ORDER BY Month;

5. Doctors Handling Maximum Patients
SELECT Doctor,
       COUNT(*) AS Total_Patients
FROM Patients
GROUP BY Doctor
ORDER BY Total_Patients DESC;

📈 STEP 6: Build Healthcare Dashboard 
Use: 
• Power BI
• Tableau

🎨 Dashboard Layout 
Section 1: KPI Cards 
Display: 
• Total Patients
• Average Treatment Cost
• Average Hospital Stay
• Patient Satisfaction Score

Section 2: Visualizations 
✔ Bar Chart 
Use for: 
• Disease Analysis

✔ Line Chart 
Use for: 
• Monthly Admissions

✔ Pie Chart 
Use for: 
• Insurance Coverage

✔ Heatmap 
Use for: 
• Department Utilization

✔ Map Visualization 
Use for: 
• Region-wise Patient Distribution

🎛 STEP 7: Add Dashboard Filters 
Add: 
✔ Disease 
✔ Department 
✔ Doctor 
✔ Insurance Type 
✔ Admission Date 

Interactive dashboards improve healthcare monitoring.