このコースについて
3,181

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6時間で修了

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

英語

字幕:英語

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6時間で修了

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

英語

字幕:英語

シラバス - 本コースの学習内容

1
2時間で修了

Why Data Quality Matters

In this module, you will be able to define data quality and what drives it. You'll be able to recall and describe four key aspects of data quality. You'll be able to explain why data quality is important for operations, for patient care, and for the finances of healthcare providers. You'll be able to discuss how data may change over time, and how finding those changes allows us to recognize and work with the issues the changes cause. You will be able to explain why requirements for data quality depend on how we intend to use that data and understand four levels of quality that may be applied for different kinds of analysis. You will also be able to discuss how all of this supports our ability to do our best work in the best ways possible....
6件のビデオ (合計34分), 2 readings, 1 quiz
6件のビデオ
Module 1 Introduction2 分
Why Data is Collected and Defining Quality3 分
Why Data Quality Matters, Part 17 分
Why Data Quality Matters, Part 29 分
How Data Quality Assessment Varies in Different Data Uses7 分
2件の学習用教材
A Note From UC Davis10 分
Data quality assessment for comparative effectiveness research in distributed data networks30 分
1の練習問題
Module 1 Quiz30 分
2
4時間で修了

Measuring Data Quality

This module focuses on measuring data quality. After this module, you will be able to describe metadata, list what metadata may include, give some examples of metadata and recall some of its uses as it relates to measuring data quality. We will describe data provenance to explains how knowing the origin of a data set can help data analysts determine if a data set is suitable for a particular use. We’ll also describe 5 components of data quality you can recall and use when evaluating data. You will also learn to be able to distinguish between data verification and validation, recalling 4 applicable data validation methods and 3 concepts useful to validate data. In addition to your video lessons, you will read and discuss a scholarly article on Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. We wrap up the module with a framework abbreviated as S-B-A-R that is often used in healthcare team situations to communicate about issues that must be solved....
7件のビデオ (合計34分), 1 reading, 1 quiz
7件のビデオ
Describing Metadata in Healthcare4 分
Data Provenance in Healthcare4 分
Components of Data Quality4 分
Data Validation Methods5 分
A Framework for Validating and Verifying Data6 分
The SBAR Methodology7 分
1件の学習用教材
Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research45 分
1の練習問題
Module 2 Quiz30 分
3
2時間で修了

Monitoring, Managing and Improving Data Quality

In this module, we focus on monitoring, managing, and improving data quality. You will be able to explain how to monitor data on a day-to-day basis to see that it remains consistent. You will explain how measures can help us monitor the patient health and the quality of care they receive over time. Also, you will be able to discuss establishing the culture of quality throughout the data lifecycle and improving data quality from the baseline by posing questions to determine a baseline of data quality. You will be able to manage data quality through expected and unexpected changes, along with tracking monitoring strategies along the data pipeline. After this module, you will be able to identify and fix common deficiencies in the data and implement change control systems as a monitoring tool. You’ll also recall several best practices you can apply on the job to monitor data quality in the healthcare field. ...
5件のビデオ (合計27分), 2 readings, 1 quiz
5件のビデオ
Establishing the Culture of Quality throughout the Data Lifecycle4 分
Improving Data Quality from the Baseline7 分
Managing Data Quality: Expected and Unexpected Changes5 分
Monitoring Strategies Along the Data Pipeline8 分
2件の学習用教材
Managing Chaos Part 1: Putting a Change Control Process in Place15 分
Managing Chaos Part 2: Change Control Decision Making15 分
1の練習問題
Module 3 Quiz30 分
4
5時間で修了

Sustaining Quality through Data Governance

IIn this module, we focus on sustaining quality through data governance. We will define data governance and consider why it matters in healthcare. You will discuss who makes up data governance committees, how these committees function relative to data analysts and describe how stakeholders work together to ensure data quality. You’ll be able to describe how high-quality data is a valuable asset for any business. You will also define data governance systems. You will recall several ways data can be repurposed and explain how data governance maintains data quality as it is repurposed for a use other than that for which it was originally gathered. In addition to your video lessons, you will read and discuss the article, Big Data, Bigger Outcomes and practice applying some of these important concepts....
6件のビデオ (合計28分), 3 readings, 2 quizzes
6件のビデオ
Defining Data Governance in Healthcare5 分
Why Data Governance Matters in Healthcare8 分
Data Governance Committees in Healthcare6 分
Data Governance Systems in Healthcare5 分
Course Summary58
3件の学習用教材
Big Data, Bigger Outcomes30 分
Welcome to Peer Review Assignments!10 分
Why Doctors Hate Their Computers50 分
1の練習問題
Module 4 Quiz30 分

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

よくある質問

  • 修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題(該当する場合)にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。

  • コースに登録する際、専門講座のすべてのコースにアクセスできます。コースの完了時には修了証を取得できます。電子修了証が成果のページに追加され、そこから修了証を印刷したり、LinkedInのプロフィールに追加したりできます。コースの内容の閲覧のみを希望する場合は、無料でコースを聴講できます。

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。