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Evaluation of Digital Health Interventions

Evaluation of Digital Health Interventions

This course is part of Digital Health Specialization

Instructor: Ana Luisa Neves

6,962 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

64 reviews

Intermediate level

Some related experience required

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

64 reviews

Intermediate level

Some related experience required

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments¹

AI Graded see disclaimer

Taught in English

91% of learners achieved a positive career outcome

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This course is part of the Digital Health Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

This course focuses on data, evaluation methods and the economic evaluation of digital health interventions. This module focuses on key data considerations for digital health including data management, data visualisation and methods for evaluating digital health interventions. The key focus is on experimental and quasi-experimental design approaches that can be applied to evaluating digital health interventions and key considerations for the economic evaluation of digital health interventions.

Module details

During this week, the focus will be on data considerations for digital health. This will be illustrated through examples around electronic disease surveillance and strategies for the extraction of medical data and how to present it. We will get you to think about what aspects of this would be challenging in your own context. The focus of the module then moves onto data visualisation with key case studies and examples of how to interrogate large datasets to examples of data visualisation. There will be a specific activity for you to do in this module in Tableau on visualising data.

What's included

2 videos17 readings1 assignment4 discussion prompts1 plugin

2 videosTotal 11 minutes

Interrogating Large Healthcare datasets8 minutes
Interview with James Scott-Brown: Data Visualisation4 minutes

17 readingsTotal 420 minutes

About Imperial College London10 minutes
About the digital health team10 minutes
How to be successful in this course?10 minutes
Grading Policy 10 minutes
Glossary10 minutes
Introductory reading on Evaluating Digital Heath Interventions20 minutes
Data and Digital Health — Why is it important? 40 minutes
Types of Data in Digital Health30 minutes
Data Requirements and Considerations for Digital Health40 minutes
Data Management 15 minutes
(Video) Visualising big data to tackle antimicrobial resistance10 minutes
Infection in Hospitals: Using individual patient movement data20 minutes
Big Data and the real world75 minutes
(Video) Optional: Are we entering a Post-Antibiotic World?15 minutes
Text Mining to Track Outbreaks45 minutes
Hans Rosling Data Presentation and Summary of Examples40 minutes
Visualisation using Tableau20 minutes

1 assignmentTotal 30 minutes

Data considerations, uses, and visualisations30 minutes

4 discussion promptsTotal 40 minutes

Nice to meet you!10 minutes
Data Considerations in Practice10 minutes
Visualisation Activity10 minutes
Data visualisations: your examples10 minutes

1 pluginTotal 15 minutes

Pre-Course Survey15 minutes

In this week, you will learn about real world case studies to improve real-time data collection and monitoring for Ebola building and the use of process evaluation to evaluate this intervention. You will then hear about interesting ways that data can be routinely used in healthcare with examples from the UK National Health Service.

What's included

4 videos5 readings2 assignments

4 videosTotal 25 minutes

Introduction to the Ebola Contact Tracing Study5 minutes
The Ebola Contact Tracing Study5 minutes
Process evaluation in Digital Health4 minutes
Interview with Ben Glampson: Routinely captured data11 minutes

5 readingsTotal 187 minutes

Pre-reading - Digital approaches to contact tracing15 minutes
Design, development and implementation of the Ebola Contact Tracing Study2 minutes
Follow-up reading90 minutes
NHS Data and Translational research 20 minutes
Appraisal of Digital Health intervention evaluation60 minutes

2 assignmentsTotal 60 minutes

Summative Quiz30 minutes
Follow up from previous reading30 minutes

This module focuses on methods for evaluating digital health interventions and you will focus on experimental and quasi-experimental evaluation approaches that can be applied to evaluating digital health interventions. You will then be introduced to real-world examples of some of these approaches and key considerations for randomised control trials. You will then focus on a specific example of methodological concerns of an evaluation of a digital medicine system, the limitations of this study and the NICE Evidence Framework.

What's included

3 videos8 readings1 assignment2 discussion prompts

3 videosTotal 15 minutes

Evaluating Digital Health Interventions3 minutes
Economic Evaluation in Healthcare 5 minutes
Health Economics and Digital Health interventions7 minutes

8 readingsTotal 365 minutes

Evaluation Methods for Digital Health Interventions10 minutes
Monitoring and Evaluating Digital Health Interventions45 minutes
Key considerations for Randomised Control Trials 10 minutes
Adaptive Designs and designing efficient RCTs 60 minutes
Natural Experiments 45 minutes
Reviewing the Babylon study60 minutes
NICE evidence standard framework60 minutes
Optional: Cost Benefit Analysis75 minutes

1 assignmentTotal 30 minutes

Knowledge on Randomised Control Trials 30 minutes

2 discussion promptsTotal 50 minutes

Limitations of the Babylon study25 minutes
NICE evidence framework in context25 minutes

In this week, you will learn about frameworks and models for evaluation, what robust trials are and examples of these, logic models and how to design a statistical analysis plan.