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Data Analytics in Healthcare and Medicine

Data Analytics in Healthcare and Medicine

Explore the transformative role of data analytics in healthcare and medicine. This course provides a comprehensive understanding of data analytics techniques, tools, and their applications in clinical and administrative settings, aiming to improve patient outcomes, operational efficiency, and decision-making processes.

Has discount
Expiry period Lifetime
Made in English
Last updated at Wed Oct 2024
Level
Beginner
Total lectures 34
Total quizzes 0
Total duration 0 Hours
Total enrolment 61
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Short description Explore the transformative role of data analytics in healthcare and medicine. This course provides a comprehensive understanding of data analytics techniques, tools, and their applications in clinical and administrative settings, aiming to improve patient outcomes, operational efficiency, and decision-making processes.
Outcomes
  • Understand the Fundamentals of Data Analytics in Healthcare: Define and differentiate between various types of data analytics (descriptive, diagnostic, predictive, and prescriptive). Explain the importance and role of data analytics in healthcare.
  • Manage Healthcare Data Effectively: Identify and describe different types of healthcare data sources. Implement best practices for data governance, privacy, and security in compliance with regulations like HIPAA.
  • Create and Interpret Data Visualizations: Apply principles of data visualization to create effective reports and dashboards. Utilize tools such as Tableau and Power BI to visualize healthcare data.
  • Perform Statistical Analysis: Conduct basic statistical analyses to interpret healthcare data. Use statistical techniques to identify trends and patterns in patient outcomes and healthcare operations.
  • Develop Predictive Models: Understand the basics of predictive analytics and machine learning. Apply predictive modeling techniques to healthcare data to forecast outcomes and support decision-making.
  • Apply Data Analytics to Real-World Healthcare Problems: Analyze case studies to understand the practical applications of data analytics in healthcare. Complete hands-on projects to gain practical experience in data analysis and model development.
  • Implement Data Analytics in Healthcare Organizations: Develop strategies for adopting data analytics in a healthcare setting. Address challenges and barriers to implementing data-driven approaches in healthcare organizations.
  • Complete a Capstone Project: Integrate knowledge and skills acquired throughout the course to develop a comprehensive data analytics plan for a healthcare organization. Present and peer-review the capstone project, demonstrating the ability to apply data analytics to improve healthcare outcomes and operations.
Requirements
  • Prerequisites: Basic understanding of healthcare systems and terminology. Familiarity with basic statistical concepts is helpful but not required.
  • Technical Requirements: Computer with internet access. Basic proficiency in using a computer and navigating the internet. Access to software tools such as Tableau, Power BI, R, and Python (guidance for access and installation will be provided).
  • Materials: No specific textbooks are required. All necessary readings and resources will be provided within the course.