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Using clinical health data for better healthcare

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Using clinical health data for better healthcare

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Gain insight into a topic and learn the fundamentals.
4.6

118 reviews

Beginner level
No prior experience required
Flexible schedule
2 weeks at 10 hours a week
Learn at your own pace
97%
Most learners liked this course

Gain insight into a topic and learn the fundamentals.
4.6

118 reviews

Beginner level
No prior experience required
Flexible schedule
2 weeks at 10 hours a week
Learn at your own pace
97%
Most learners liked this course

There are 4 modules in this course

Digital health is rapidly being realised as the future of healthcare. While this is placing emphasis on the input of quality health data in digital records and systems, the delivery of safe and quality healthcare relies not only on the input of data, but also the ability to access and derive meaning from data to generate evidence, inform decision making and drive better health outcomes.

This course provides insight into the use of healthcare data, including an overview of best practices and the practical realities of obtaining useful information from digital health systems via the understanding of the fundamental concepts of health data analytics. Learners will understand why data quality is essential in modern healthcare, as they are guided through various stages of the data life cycle, starting with the generation of quality health data, through to discovering patterns and extracting knowledge from health data using common methodologies and tools in the basic analysis, visualisation and communication of health data. In doing so, learners explore current healthcare delivery contexts, and future and emerging digital health data systems and applications that are rapidly becoming tomorrow’s reality. On completion of this course, you will be able to: 1. Identify digital health technologies, health data sources, and the evolving roles of health workforce in digital health environments 2. Understand key health data concepts and terminology, including the significance of data integrity and stakeholder roles in the data life cycle 3. Use health data and basic data analysis to inform and improve decision making and practice. 4. Apply effective methods of communication of health data to facilitate safe and quality care. During this course, you will interact with learning content contributed by: • Digital Health Cooperative Research Centre • Australian Digital Health Agency • eHealth NSW • Sydney Local Health District • The NSW Ministry of Health • Health Education and Training Institute • Clinical Excellence Commission • Chris O’Brien Lifehouse • Monash Partners / Australian Health Research Alliance • Australian Research Data Commons • Justice Health & Forensic Mental Health Network • South Eastern Sydney Local Health District • Western Sydney Local Health District • Westmead Breast Cancer Institute • Agency for Clinical Innovation • Western NSW Local Health District • Sydney Children’s Hospital Network This course is a collaborative venture between NSW Health, the University of Sydney and the Digital Health Cooperative Research Centre, including dedicated resources from eHealth NSW, Health Education and Training Institute, and the Research in Implementation Science & eHealth group. While many learning resources and case examples are drawn from the NSW Health service context, this course has relevance for all existing and future health workforce, regardless of role or work context. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation.

This module explores current digital health environments, identifying the many uses of digital health technologies and health data sources. We look at the evolving roles of the health workforce in digital health environments, considering roles and responsibilities. The importance of data analytics for decision making and healthcare outcomes is introduced. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation.

What's included

7 videos5 readings3 assignments1 discussion prompt

7 videosTotal 27 minutes
  • Welcome and introduction2 minutes
  • Introduction to Module 12 minutes
  • Five ways digital health data is changing healthcare8 minutes
  • Data driven care: turning data from a personal health journey into actionable information3 minutes
  • Do healthcare professionals really need to know data analytics?5 minutes
  • The potential of health data to drive healthcare transformations: Digital Health CRC4 minutes
  • Module 1 conclusion2 minutes
5 readingsTotal 185 minutes
  • Article and instructions for quiz: 'Five ways digital data is changing health care'30 minutes
  • Data driven care - video and infographic20 minutes
  • Worksheet and instructions for activity: Data driven care - your context30 minutes
  • Activity: Vision for digital health and data analytics60 minutes
  • Module 1 readings45 minutes
3 assignmentsTotal 40 minutes
  • Five ways digital health data is changing healthcare - Change to attitudes20 minutes
  • Data driven care - your context10 minutes
  • Vision for digital health and data analytics10 minutes
1 discussion promptTotal 10 minutes
  • Introduce yourself and your health context10 minutes

In this module, we review key health data concepts and terminology. We emphasise the importance of data integrity and the benefits and consequences of high or low quality data. We look at the data life cycle and the roles and responsibilities of all stakeholders in the provision of quality healthcare. There are some case studies illustrating the consequences of poor quality data and we also look at the fundamentals of digital health legislation and policy. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation.

What's included

8 videos3 readings4 assignments1 discussion prompt

8 videosTotal 42 minutes
  • Introduction to Module 21 minute
  • What is health data? An introduction to health data classification 4 minutes
  • Overview of the data life cycle6 minutes
  • Quality health data: What is it and why is it important?6 minutes
  • What happens when we get it wrong? The impact of poor data quality4 minutes
  • Data governance and privileges 8 minutes
  • Terminology and  key statistical concepts for interpreting data11 minutes
  • Module 2 conclusion1 minute
3 readingsTotal 130 minutes
  • Activity: Data governance and privileges60 minutes
  • Terminology and key concepts for interpreting data30 minutes
  • Module 2 readings40 minutes
4 assignmentsTotal 55 minutes
  • Data governance and privileges10 minutes
  • Terminology and key concepts for interpreting data20 minutes
  • Practice: Overview of the data life cycle10 minutes
  • Practice: Dimensions of quality data15 minutes
1 discussion promptTotal 15 minutes
  • Data quality - experiences and impacts15 minutes

In this module, we look at the use of health data and basic data analysis to inform and improve decision making and practice. We explore some common methods and tools used in the analysis of health data. There is an opportunity to develop a data query and to practice working with data. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation.

What's included

8 videos3 readings3 assignments1 peer review

8 videosTotal 44 minutes
  • Introduction to Module 31 minute
  • From information to insight – Overview of analytics impacting healthcare 6 minutes
  • Key steps in the analysis of health data4 minutes
  • Make sense of a data report8 minutes
  • Everyday data queries common to decision making in healthcare5 minutes
  • Carry out a simple (guided) health data analysis task 14 minutes
  • Top tips for your analytics journey3 minutes
  • Module 3 conclusion2 minutes
3 readingsTotal 50 minutes
  • Data tools10 minutes
  • Data analysis task - instructions and worksheet30 minutes
  • Module 3 readings10 minutes
3 assignmentsTotal 70 minutes
  • Data tools20 minutes
  • Data analysis task20 minutes
  • Practice: Types of analytics30 minutes
1 peer reviewTotal 90 minutes
  • Compose a data query90 minutes

In the final module, we look at the various modes of communication appropriate for sharing the results produced by data analysis. We consider how effective communication of digital health data contributes to greater consumer engagement and well-being as well as more effective, evidence-based decision making within the healthcare system. Note: Materials used are for learning purposes and content may not reflect your organisation’s policies. When working with data, make sure you act within the guidelines and policies of your organisation.

What's included

9 videos2 readings1 assignment1 discussion prompt

9 videosTotal 40 minutes
  • Introduction to Module 42 minutes
  • Make data meaningful: Best practice for the communication of health data7 minutes
  • Use of data visualisations for collaborative decision making 8 minutes
  • Collaborating around data for healthcare improvement4 minutes
  • Sharing data for research purposes8 minutes
  • Case example: Digital health tools powered by shared health data Digital Health Co-operative Research Centre and Lorica Health4 minutes
  • Case study: Real time data use. Pascal Metrics Project, NSW Health3 minutes
  • Module 4 conclusion1 minute
  • Course wrap-up1 minute
2 readingsTotal 70 minutes
  • Data Visualisation – Making data meaningful30 minutes
  • Module 4 readings40 minutes
1 assignmentTotal 30 minutes
  • Data Visualisation – Making data meaningful30 minutes
1 discussion promptTotal 30 minutes
  • Medicine as data science30 minutes

Instructor

Instructor ratings
4.8 (40 ratings)
The University of Sydney
2 Courses37,729 learners

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MP
·

Reviewed on Oct 25, 2020

I strongly recommend this course for those who are interested in data analysis.

JC
·

Reviewed on Mar 23, 2020

I thought that it was a great course. Very interesting and informative, relevant to the coursework and placement I am doing for my PhD and pitched at my level. Thank-you :-)

SE
·

Reviewed on Aug 31, 2021

Really it was a great experience for me Such informative and practical course

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