Cleaning & Processing Healthcare Data in Excel

High-quality analysis depends on high-quality data. In this practical course, you’ll learn how to clean, prepare and standardise healthcare datasets using Microsoft Excel before they are used for reporting, dashboards or further statistical analysis.

Working through realistic healthcare scenarios, you’ll develop the skills to identify common data quality problems, resolve inconsistencies and prepare reliable datasets suitable for clinical, operational and public health reporting.

This course provides essential foundations for anyone beginning a career in healthcare analytics or wishing to improve the quality of their day-to-day data management.

Learning Outcomes

By the end of this course you will be able to:

• Recognise common healthcare data quality issues.
• Identify and correct missing values and duplicate records.
• Clean datasets using Excel functions and tools.
• Standardise healthcare data for consistency.
• Validate and quality assure datasets.
• Prepare healthcare data for analysis and reporting.

Course Modules

• Module 1: Introduction to Healthcare Data
  • Understand the characteristics of healthcare data and explore common challenges encountered when working with clinical and operational datasets.
• Module 2: Data Quality Issues
  • Learn how to identify missing values, duplicate records, inconsistencies and common data quality problems.
• Module 3: Excel Tools for Data Cleaning
  • Use practical Excel functions including IFERROR, VLOOKUP, CONCATENATE and other essential tools to clean healthcare data efficiently.
• Module 4: Handling Outliers and Data Normalisation
  • Identify unusual observations, investigate potential errors and standardise data for consistent analysis.
• Module 5: Data Validation and Error Prevention
  • Apply validation rules and quality assurance techniques to reduce future data entry errors.
• Module 6: Standardising Healthcare Data
  • Learn methods for formatting healthcare datasets consistently to improve reporting and interoperability.
• Module 7: Handling Categorical Data and Dates
  • Work effectively with categories, coding systems and date fields commonly found within healthcare datasets.
• Module 8: Preparing Data for Analysis
  • Transform raw healthcare information into clean, structured datasets suitable for dashboards, reporting and statistical analysis.
• Module 9: Real-world Healthcare Case Studies
  • Apply your knowledge using practical healthcare examples and learn common approaches to solving real data quality challenges.
• Module 10: Final Project
  • Complete an end-to-end healthcare data cleaning project, preparing a realistic dataset for professional analysis and reporting.

Skills You’ll Gain

• Data Cleaning
• Data Quality Assurance
• Excel Functions
• Data Validation
• Duplicate Detection
• Missing Data Handling
• Data Preparation
• Healthcare Data Standards
• Reporting Readiness