Hospital Analytics

Project Objectives

Analyze hospital Management Datasets.

Clean and prepare raw data for analysis

Build an interactive Power BI dashboard

Track key KPIs (Patients, Revenue, appointments)

Support data-driven decision making

Business Understanding

A hospital operates as an integrated system that provides medical services to patients through multiple functional units, including:

patient registration, doctor consultation, treatment, and billing.

The core services typically include:

Patient management (registration, demographics, insurance)

Doctor services (specializations, scheduling, consultations)

Appointment management (booking, status tracking)

Treatment services (procedures, diagnostics, costs)

Billing and payment processing

Dataset Description

Source: Kaggle Hospital Management Dataset

Contains the following Tables:

Patients

Doctors

Appointments

Treatments

Billing

Type: Relational dataset

Project Methodology

Steps:

Data Retrieving

Data Cleaning

Data Modeling

Data Analysis (DAX)

Dashboard Design

Insights & Recommendations

Data Retrieving:

Download dataset from Kaggle

Import into Power BI

Verify data structure

2. Data Cleaning in power Query:

Handle missing values

Correct data types

Rename columns

Add Calendar table

Add calculated column

3. Data Modeling

Create relationships:

Patient ↔ Appointments

Doctor ↔ Appointments

Calendar ↔ Billing

Treatment Appointment

Build a logical data model

Data Analysis (DAX)

Total Revenue

Total Patients

Average Treatment

Cost

Appointment Status

AVG age

Revenue per Hospital

Dashboard Design

A set of key performance indicators (KPIs) has been developed to provide clear, actionable insights into overall performance. These KPIs include total Revenue, Revenue growth, Total number of appointments, and the average number of appointments per doctor.

Design an interactive dashboard consisting of five key pages: a Home, Executive Overview, Doctor Performance, Patient Insights, and a Financial Analytics, with dynamic filters for date ranges and treatment types

Key Insights & Recommendations

High Appointment Cancellation pattern

Certain departments generate more revenue

Revenue is fully offset by costs, resulting in a zero-profit position

Focus on high-performing departments

Conclusion

Successfully built a Power BI dashboard

Provided actionable insights

Demonstrated full analytics workflow