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中級レベル
約12時間で修了
英語
字幕:英語
共有できる証明書
修了時に証明書を取得
100%オンライン
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
約12時間で修了
英語
字幕:英語

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

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

シラバス - 本コースの学習内容

1

1

2時間で修了

Solving the Business Problems

2時間で修了
8件のビデオ (合計61分), 1 reading, 1 quiz
8件のビデオ
Module 1 Introduction3 分
Provider Profiling10 分
How to Make Fairer Comparisons Using Risk Adjustment6 分
How Risk Adjustment is Performed8 分
Patient Safety: Measuring Adverse Events7 分
Super-Utilizers of Health Resources10 分
Fraud Detection10 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

2時間で修了

Algorithms and "Groupers"

2時間で修了
7件のビデオ (合計51分)
7件のビデオ
Clinical Identification Algorithms (CIA)9 分
HEDIS and AHRQ Quality Measures7 分
Analytical Groupers6 分
Open Source Groupers - Grouping Diagnoses and Procedures7 分
Open Source Groupers - Comorbidity, Patient Risk, and Drugs8 分
Commercial Groupers10 分
1の練習問題
Module 2 Quiz30 分
3

3

3時間で修了

ETL (Extract, Transform, and Load)

3時間で修了
6件のビデオ (合計49分)
6件のビデオ
Analytical Processes and Planning10 分
Data Mining and Predictive Modeling - Part 16 分
Data Mining and Predictive Modeling - Part 26 分
Extracting Data for Analysis10 分
Transforming Data for Analytical Structures11 分
1の練習問題
Module 3 Quiz30 分
4

4

5時間で修了

From Data to Knowledge

5時間で修了
7件のビデオ (合計49分), 1 reading, 2 quizzes
7件のビデオ
Solving Analytical Problems with Risk Stratification8 分
Risk Stratification: Variables, Groupers, Predictors8 分
Risk Stratification: Model Creation/Evaluation and Deployment of Strata9 分
Medicare Claims Data - Source and Documentation8 分
Final Tips to Help Understand and Interpret Healthcare Data8 分
Course Summary2 分
1件の学習用教材
Welcome to Peer Review Assignments!10 分
1の練習問題
Module 4 Quiz30 分

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Health Information Literacy for Data Analytics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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