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.
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Spécialisation Santé numériqueImperial College LondonÀ propos de ce cours
3 952 consultations récentes
Dates limites flexibles
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Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Niveau intermédiaire
Approx. 32 heures pour terminer
Anglais
Sous-titres : Anglais
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Niveau intermédiaire
Approx. 32 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Imperial College London
Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges.
Programme de cours : ce que vous apprendrez dans ce cours
9 heures pour terminer
Data considerations for Digital Health
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.
9 heures pour terminer
2 vidéos (Total 11 min), 17 lectures, 1 quiz
5 heures pour terminer
Real world research: A Proof-of-concept study and translational research
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.
5 heures pour terminer
4 vidéos (Total 25 min), 5 lectures, 2 quiz
8 heures pour terminer
Methods for evaluating Digital Health interventions
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.
8 heures pour terminer
3 vidéos (Total 15 min), 8 lectures, 1 quiz
11 heures pour terminer
Frameworks and Models for Evaluation
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.
11 heures pour terminer
3 vidéos (Total 20 min), 9 lectures, 2 quiz
À propos du Spécialisation Santé numérique
This specialisation introduces students to the emerging and multidisciplinary field of digital health and the role and application of digital health technologies including mobile applications, wearable technologies, health information systems, telehealth, telemedicine, machine learning, artificial intelligence and big data. These digital health technologies are assessed in terms of their opportunities and challenges to address real-world public health and health care system challenges in order to improve the quality, safety and efficiency of these services. The aim of this specialisation is to prepare learners for the new era of digitalisation in public health and health care globally.
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