Title: Harnessing data for healthcare advancement

Location: US

Company: University of Cambridge

About this course:
This course introduces key principles of data-driven decision-making in healthcare data science, focusing on managing and leveraging health data effectively across 3 modules.
You'll begin in Module 1 by exploring what it means to be data-driven, ensuring data consistency, accessibility, and reliability while addressing challenges like missing information. You’ll also learn the essentials of metadata management and ethical considerations for handling health data.
Module 2 will teach you how to develop a HDS project by understanding healthcare systems, teamwork, and project management. You'll explore how data flows within healthcare, the roles involved in health data science, and how collaboration enhances patient outcomes. Essential tools for navigating health data projects will also be introduced.
In Module 3, you’ll focus on collaboration and communication in health data science. You’ll examine factors that contribute to project success, including effective documentation and data visualization techniques.
By the end of this course, you'll be equipped with the knowledge and skills to manage health data projects efficiently and communicate findings to diverse stakeholders.

In Module 1 we introduce you to data-driven decision-making where you will learn to

describe what data-driven decision-making is.

explain data integrity, FAIR principles and five-safes rule

demonstrate an understanding of data quality and metadata.

analyse data access processes and principles.

In Module 2 we focus on healthcare systems where you will learn to:

describe the healthcare system

outline the different health data science project roles.

distinguish between the different types of data flows.

show how patient pathways and collaborative pathways operate.

compare different effective tools in a health data science project.

In Module 3 we will review factors that grant success of a HDS project, you will learn to:

define a common language for a health data science collaborations

discuss the best study protocols for a common collaborative language.

illustrate how to effectively document, evaluate and communicate results.

analyse data visualisation in health data reports.

Learn to manage health data, develop data science projects, and collaborate effectively in healthcare. This course covers data-driven decision-making, healthcare systems, project management, and data visualization to ensure impactful healthcare outcomes.

Duration: 10 weeks

Curriculum:
- Module 1: Introduction to Data-Driven Decision-Making
- Module 2: Healthcare system

- Module 3: Effective Collaboration