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中級

完成時間大約為9 小時

建議:4 weeks of study, 2-5 hours/week...

英語(English)

字幕:英語(English)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為9 小時

建議:4 weeks of study, 2-5 hours/week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 3 小時

Introduction to Healthcare Data Models

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. ...
10 個視頻 (總計 58 分鐘), 1 個閱讀材料, 1 個測驗
10 個視頻
Module 1 Introduction52
What is a Data Model?6分鐘
Speaking the Same Language and Capturing the Context6分鐘
The Uniqueness of Data Models as Used in Healthcare6分鐘
Path to Value: Operational Systems to Actionable Information, Part 17分鐘
Path to Value: Operational Systems to Actionable Information, Part 26分鐘
Data Flows among Systems and Keeping Systems Connected7分鐘
What We're Measuring in Healthcare Data Models, Part 17分鐘
What We're Measuring in Healthcare Data Models, Part 25分鐘
1 個閱讀材料
A Note From UC Davis10分鐘
1 個練習
Module 1 Quiz30分鐘
2
完成時間為 2 小時

Data Models and Use Cases They Support

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....
6 個視頻 (總計 33 分鐘), 1 個測驗
6 個視頻
Selecting a Data Model9分鐘
The Hierarchical Model and Supported Use Cases5分鐘
The Relational Schema and Supported Use Cases6分鐘
The Star Schema and Supported Use Cases6分鐘
Comparing and Contrasting Healthcare Data Models5分鐘
1 個練習
Module 2 Quiz30分鐘
3
完成時間為 3 小時

Working with Data across Systems

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. ...
5 個視頻 (總計 41 分鐘), 1 個測驗
5 個視頻
Purpose, Use Cases, and Measurements in Healthcare Data8分鐘
Normalization of Healthcare Data6分鐘
Integrating Healthcare Data Across Sources and Systems10分鐘
Common Identifiers and The Master Patient Index (MPI)14分鐘
1 個練習
Module 3 Quiz30分鐘
4
完成時間為 5 小時

Improving the Quality of Healthcare Data

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. ...
5 個視頻 (總計 27 分鐘), 3 個閱讀材料, 2 個測驗
5 個視頻
Data Quality: Driven by Questions We Ask and Levels of Use8分鐘
Verification and Validation of Data for Consistency: Finding Data Errors8分鐘
Data Mapping7分鐘
Course Summary1分鐘
3 個閱讀材料
Data Mapping article from AHIMA30分鐘
What Mapping and Modeling Means to the Health Information Management Professional30分鐘
Welcome to Peer Review Assignments!10分鐘
1 個練習
Module 4 Quiz30分鐘

講師

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Doug Berman

Director, Data Acquisition and Architecture
UC Davis Health System

關於 加州大学戴维斯分校

UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact....

關於 Health Information Literacy for Data Analytics 專項課程

This Specialization is intended for data and technology professionals with no previous healthcare experience who are seeking an industry change to work with healthcare data. Through four courses, you will identify the types, sources, and challenges of healthcare data along with methods for selecting and preparing data for analysis. You will examine the range of healthcare data sources and compare terminology, including administrative, clinical, insurance claims, patient-reported and external data. You will complete a series of hands-on assignments to model data and to evaluate questions of efficiency and effectiveness in healthcare. This Specialization will prepare you to be able to transform raw healthcare data into actionable information....
Health Information Literacy for Data Analytics

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