À propos de ce cours
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Approx. 10 heures pour terminer

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

Anglais

Sous-titres : Anglais

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau intermédiaire

Approx. 10 heures pour terminer

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

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
3 heures pour terminer

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 vidéos (Total 58 min), 1 lecture, 1 quiz
10 vidéos
Module 1 Introduction52s
What is a Data Model?6 min
Speaking the Same Language and Capturing the Context6 min
The Uniqueness of Data Models as Used in Healthcare6 min
Path to Value: Operational Systems to Actionable Information, Part 17 min
Path to Value: Operational Systems to Actionable Information, Part 26 min
Data Flows among Systems and Keeping Systems Connected7 min
What We're Measuring in Healthcare Data Models, Part 17 min
What We're Measuring in Healthcare Data Models, Part 25 min
1 lecture
A Note From UC Davis10 min
1 exercice pour s'entraîner
Module 1 Quiz30 min
Semaine
2
2 heures pour terminer

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 vidéos (Total 33 min), 1 quiz
6 vidéos
Selecting a Data Model9 min
The Hierarchical Model and Supported Use Cases5 min
The Relational Schema and Supported Use Cases6 min
The Star Schema and Supported Use Cases6 min
Comparing and Contrasting Healthcare Data Models5 min
1 exercice pour s'entraîner
Module 2 Quiz30 min
Semaine
3
3 heures pour terminer

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 vidéos (Total 41 min), 1 quiz
5 vidéos
Purpose, Use Cases, and Measurements in Healthcare Data8 min
Normalization of Healthcare Data6 min
Integrating Healthcare Data Across Sources and Systems10 min
Common Identifiers and The Master Patient Index (MPI)14 min
1 exercice pour s'entraîner
Module 3 Quiz30 min
Semaine
4
5 heures pour terminer

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 vidéos (Total 27 min), 3 lectures, 2 quiz
5 vidéos
Data Quality: Driven by Questions We Ask and Levels of Use8 min
Verification and Validation of Data for Consistency: Finding Data Errors8 min
Data Mapping7 min
Course Summary1 min
3 lectures
Data Mapping article from AHIMA30 min
What Mapping and Modeling Means to the Health Information Management Professional30 min
Welcome to Peer Review Assignments!10 min
1 exercice pour s'entraîner
Module 4 Quiz30 min
3.8
3 avisChevron Right

Principaux examens pour Healthcare Data Models

par RTMar 5th 2019

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

Enseignant

Avatar

Doug Berman

Director, Data Acquisition and Architecture
UC Davis Health System

À propos de Université de Californie à Davis

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....

À propos de la Spécialisation Health Information Literacy for Data Analytics

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

Foire Aux Questions

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  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

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