Introduction to Data for Healthcare Professionals – November 2026 Tutor Led

Categories: Excel
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About Course

Welcome to Introduction to Data for Healthcare Professionals!

Healthcare is becoming increasingly data-driven. Whether you work in clinical care, administration, public health, research, or management, understanding healthcare data is now an essential skill. Every patient interaction generates valuable information that can be used to improve patient outcomes, support clinical decision-making, monitor performance, and shape healthcare policy.

This course has been designed specifically for healthcare professionals who want to build confidence in working with data, regardless of their previous experience. You do not need a technical background to complete this course. We begin with the fundamentals before gradually introducing more practical concepts and real-world healthcare applications.

Throughout the course, you will learn how healthcare data is collected, stored, processed, analysed and presented. You will also explore the importance of clinical coding, data quality, ethical responsibilities, and the role data plays in improving patient care and organisational performance.

By the end of this course, you will have a solid understanding of the healthcare data lifecycle and the confidence to interpret, manage and communicate data effectively within your own professional role.

  • Course Format: 6 Live Sessions
  • Delivery Platform: Microsoft Teams
  • Audience: Healthcare professionals with little to moderate Excel experience
  • Duration: 6 sessions x 3 hours

COURSE OVERVIEW

Course Title: Introduction to Data for Healthcare Professionals: From Raw Healthcare Data to Dashboards

Course Aim: To equip healthcare professionals with practical Excel skills for handling, cleaning, analysing and visualising healthcare data.

Learning Outcomes

By the end of the course, participants will be able to:

  • Understand different types of healthcare data
  • Navigate Excel confidently
  • Understand CSV vs Excel workbooks
  • Import and organise healthcare data
  • Clean and standardise datasets using Excel formulas
  • Apply filtering and sorting techniques
  • Use pivot tables and pivot charts
  • Create basic dashboards
  • Understand the purpose of Power Query
  • Interpret healthcare datasets visually

Course Structure

Session 1
Introduction to Health Data
Duration: 3 hours

Session 2
Excel Fundamentals
Duration: 3 hours

Session 3
Data Cleaning with Excel
Duration: 3 hours

Session 4
Formulas, Filtering and Analysis
Duration: 3 hours

Session 5
Visualisation and Introduction to Power Query
Duration: 3 hours

Session 6
Dashboard Building and Final Capstone Launch
Duration: 3 hours

Who This Course Is For

This course is suitable for:

  • Healthcare Assistants
  • Nurses
  • Allied Health Professionals
  • Medical Students
  • Administrators
  • Clinical Coders
  • Healthcare Managers
  • Public Health Professionals
  • Researchers
  • Anyone interested in healthcare data

No previous experience in data analysis or programming is required.

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Course Content

Module 1: Introduction to Health Data
Microsoft Teams meeting Join: https://teams.microsoft.com/meet/387875040696671?p=luk6P6TZGuKyhuJxPi Meeting ID: 387 875 040 696 671 Passcode: fc2Nq93z

  • Session One: May 2026
    00:00
  • Introduction to health data
    00:00

Module 2: Types of Health Data
Explore structured and unstructured data, quantitative and qualitative data, clinical records, administrative data, laboratory results, imaging, and more.

Module 3: Clinical Terminology and Coding
Learn the foundations of clinical terminology and healthcare coding systems such as ICD-10, SNOMED CT, and OPCS.

Module 4: Data Input and Collection Methods
Understand where healthcare data comes from, how it is collected, and best practices for ensuring accurate, reliable information.

Module 5: Data Processing in Excel
Develop practical Excel skills for cleaning, organising, validating and preparing healthcare datasets for analysis.

Module 6 – Data Analysis Techniques
Learn introductory analytical techniques, including descriptive statistics, filtering, summarising and interpreting healthcare data.

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