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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/healthcare-data-models
课程评论：没有评论
课程名称：医疗数据模型 概述：医疗数据分析的职业前景十分广阔。如果您在数据分析领域工作，考虑转向医疗行业以改善人们的生活质量，那么本课程将为您提供该领域的重要性、您的工作职责以及数据从患者那里采集到护理点、进入数据仓库进行分析准备，然后沿数据管道转化为可拯救生命、降低成本、改善医疗服务并使之更具可及性和经济性的重要洞察的路径概览。如果您在医疗行业工作并考虑转型，本课程将帮助您判断这一职业道路是否适合您。您将了解常见的数据模型及其用途，学习各种系统如何整合数据、确保清晰沟通、测量和改善数据质量。医疗领域的数据分析服务于医生、临床医生、患者、护理提供者以及改善健康结果的相关业务。本课程将为您提供现代快速变化的医疗领域的数据分析清晰图景和多种机会。 课程大纲： 1. **医疗数据模型介绍**：定义医疗数据模型中的基础术语，描述数据从操作流向分析的概念模型，比较医疗数据系统中常见的数据模型，并识别医疗数据分析中使用的常见衡量标准。 2. **数据模型及其支持的用例**：描述星形架构数据模型，区分其与层次模型和关系模型的不同，列出其优缺点，并解释适用场景，识别其他类型数据模型在特定用例中的适用性。 3. **跨系统的数据处理**：解释信息如何在数据模型中存储，如何组装相关信息以分析有助于改善医疗系统的问题，回顾数据标准化及其分析便利性，讨论如何整合来自不同来源和各功能系统的信息，以及如何准确衡量。 4. **提高医疗数据质量**：检查进入模型的数据，解释如何处理来自医学实践和商业的信息，专注于通过验证和核实找到和纠正数据错误，提高数据质量的几种方法。 该课程将为您提供一个全面的医疗数据分析视角，帮助您在这一领域的职业发展中作出明智的选择。
Name:Introduction to Healthcare Data Models
Description:In this module, you will be able to define the foundational terms used in discussing and building healthcare data models. You'll be able to describe the conceptual model showing how data flows from operations to analysis. You will compare and contrast common data models used in healthcare data systems. You will also be able to identify common measures used in healthcare data analysis.
Name:Data Models and Use Cases They Support
Description:In this module, you'll be able to describe the Star Schema Data Model, distinguish it from the hierarchical and relational model, list some pros and cons and explain situations in which it could be appropriately used. You should also recognize when another type of data model might be better suited to a particular use case.
Name:Working with Data across Systems
Description:In this module, you'll be able to explain how information is stored in data models and how we assemble relevant information to analyze an interesting problem that can improve our healthcare systems. We'll review how we normalize data and how that facilitates analysis. We'll go on to discuss how to bring together information from different sources and across various functional systems. We will also consider how to measure it accurately.
Name:Improving the Quality of Healthcare Data
Description:In this module, you will be able to examine the data that goes into these models and explain how we work with the information that comes from the practice and business of medicine. We will transition from raising the data quality to focusing on finding and correcting data errors by validation and verification. You will also be able to describe several ways data is checked to eliminate errors and improve data quality.
Career prospects are bright for those qualified to work in healthcare data analytics. Perhaps you work in data analytics, but are considering a move into healthcare where your work can improve people’s quality of life. If so, this course gives you a glimpse into why this work matters, what you’d be doing in this role, and what takes place on the Path to Value where data is gathered from patients at the point of care, moves into data warehouses to be prepared for analysis, then moves along the data pipeline to be transformed into valuable insights that can save lives, reduce costs, to improve healthcare and make it more accessible and affordable. Perhaps you work in healthcare but are considering a transition into a new role. If so, this course will help you see if this career path is one you want to pursue. You’ll get an overview of common data models and their uses. You’ll learn how various systems integrate data, how to ensure clear communication, measure and improve data quality. Data analytics in healthcare serves doctors, clinicians, patients, care providers, and those who carry out the business of improving health outcomes. This course of study will give you a clear picture of data analysis in today’s fast-changing healthcare field and the opportunities it holds for you.
