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中級レベル

英語

字幕:英語

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自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

英語

字幕:英語

シラバス - 本コースの学習内容

1
3時間で修了

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.

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10件のビデオ (合計58分), 1 reading, 1 quiz
10件のビデオ
Module 1 Introduction52
What is a Data Model?6 分
Speaking the Same Language and Capturing the Context6 分
The Uniqueness of Data Models as Used in Healthcare6 分
Path to Value: Operational Systems to Actionable Information, Part 17 分
Path to Value: Operational Systems to Actionable Information, Part 26 分
Data Flows among Systems and Keeping Systems Connected7 分
What We're Measuring in Healthcare Data Models, Part 17 分
What We're Measuring in Healthcare Data Models, Part 25 分
1件の学習用教材
A Note From UC Davis10 分
1の練習問題
Module 1 Quiz30 分
2
2時間で修了

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件のビデオ (合計33分), 1 quiz
6件のビデオ
Selecting a Data Model9 分
The Hierarchical Model and Supported Use Cases5 分
The Relational Schema and Supported Use Cases6 分
The Star Schema and Supported Use Cases6 分
Comparing and Contrasting Healthcare Data Models5 分
1の練習問題
Module 2 Quiz30 分
3
3時間で修了

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.

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5件のビデオ (合計41分), 1 quiz
5件のビデオ
Purpose, Use Cases, and Measurements in Healthcare Data8 分
Normalization of Healthcare Data6 分
Integrating Healthcare Data Across Sources and Systems10 分
Common Identifiers and The Master Patient Index (MPI)14 分
1の練習問題
Module 3 Quiz30 分
4
5時間で修了

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.

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5件のビデオ (合計27分), 3 readings, 2 quizzes
5件のビデオ
Data Quality: Driven by Questions We Ask and Levels of Use8 分
Verification and Validation of Data for Consistency: Finding Data Errors8 分
Data Mapping7 分
Course Summary1 分
3件の学習用教材
Data Mapping article from AHIMA30 分
What Mapping and Modeling Means to the Health Information Management Professional30 分
Welcome to Peer Review Assignments!10 分
1の練習問題
Module 4 Quiz30 分
3.8
3件のレビューChevron Right

Healthcare Data Models からの人気レビュー

by RTMar 5th 2019

Great examples and reinforces what the goals of each module are.

講師

Avatar

Doug Berman

Director, Data Acquisition and Architecture
UC Davis Health System

カリフォルニア大学デービス校(University of California, Davis)について

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....

Health Information Literacy for Data Analyticsの専門講座について

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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