|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/evaluation-of-digital-health-interventions
课程评论：没有评论
课程名称：数字健康干预的评估 概述：本课程侧重于数字健康干预的数据、评估方法及经济评估。模块重点关注数字健康的数据管理、数据可视化及数字健康干预的评估方法，特别是实验设计和准实验设计在数字健康干预评估中的应用，以及经济评估的关键考虑事项。 课程大纲： 1. **数字健康的数据考虑** - 课程描述：本周将重点讨论数字健康的数据问题，通过电子疾病监测的案例，探讨医疗数据提取与展示的策略。学员将思考在自身情境中可能面临的挑战。接着，课程将转向数据可视化，通过关键案例研究和大数据集的分析实例，学习数据可视化的技巧，本模块将包括在Tableau中进行数据可视化的具体活动。 2. **现实世界研究：概念验证研究与转化研究** - 课程描述：这一周，学员将学习现实案例研究，以改善埃博拉的实时数据收集和监测，并利用过程评估来评估这一干预。课程还将展示数据在医疗保健中常规使用的有趣方式，举例说明来自英国国家医疗服务体系（NHS）的实例。 3. **数字健康干预的评估方法** - 课程描述：本模块专注于数字健康干预的评估方法，重点学习实验和准实验评估方法的应用。学员将接触到一些真实世界的案例和随机对照试验的关键考虑事项。此外，还将关注数字医疗系统评估中的方法论问题及其限制，以及NICE证据框架。 4. **评估框架与模型** - 课程描述：本周，学员将学习评估的框架和模型，包括稳健试验的定义和实例，逻辑模型，以及如何设计统计分析计划。 本课程通过理论与实践相结合，旨在提高学员在数字健康干预领域进行评估的能力，为将来的研究和实践提供指导。
Name:Data considerations for Digital Health
Description: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.
Name:Real world research: A Proof-of-concept study and translational research
Description: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.
Name:Methods for evaluating Digital Health interventions
Description: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.
Name:Frameworks and Models for Evaluation
Description: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.
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.
