Acerca de este Curso
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Nivel intermedio

Aprox. 21 horas para completar

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

Inglés (English)

Subtítulos: Inglés (English)

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Aprox. 21 horas para completar

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

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
4 horas para completar

Introduction: Clinical Data Models and Common Data Models

9 videos (Total 54 minutos), 4 lecturas, 1 cuestionario
9 videos
Clinical Research Data Warehouses9m
Entity Relationship Diagrams (ERDs)4m
Clinical Data Models4m
Why Common Data Models?10m
A Quick Tour of a Common Data Model: i2b26m
A Quick Tour of a Common Data Model: OMOP5m
A Quick Tour of a Common Data Model: Sentinel6m
A Quick Tour of a Common Data Model: PCORNet5m
4 lecturas
Introduction to Specialization Instructors5m
Course Policies5m
Accessing Course Data and Technology Platform15m
Readings and Course Materials for Module 12h
1 ejercicio de práctica
Clinical Data Models and Common Data Models30m
Semana
2
3 horas para completar

Tools: Querying Clinical Data Models

6 videos (Total 59 minutos), 1 lectura, 1 cuestionario
6 videos
Querying MIMIC-III9m
A Deep Dive into OMOP Data Model13m
Querying OMOP12m
Comparing the MIMIC and OMOP Data Models10m
The OHDSI Community Ecosystem7m
1 lectura
Readings and Course Materials for Module 21h 30m
1 ejercicio de práctica
Tools: Querying Clinical Data Models30m
Semana
3
3 horas para completar

Techniques: Extract-Transform-Load and Terminology Mapping

6 videos (Total 53 minutos), 1 lectura, 1 cuestionario
6 videos
Structural versus Terminology Mapping6m
Data Profiling with White Rabbit10m
Data Mapping with the Rabbit in a Hat Tool9m
Terminology Mapping10m
Example mapping of MIMIC Patient to OMOP Person8m
1 lectura
Readings and Course Materials for Module 32h
1 ejercicio de práctica
Techniques: Extract-Transform-Load and Terminology Mapping30m
Semana
4
3 horas para completar

Techniques: Data Quality Assessments

5 videos (Total 52 minutos), 1 lectura, 1 cuestionario
5 videos
Data profiling for data quality assessment10m
Data quality assessment using SQL13m
Callahan and Khare rules8m
OHDSI Achilles and Achilles Heel12m
1 lectura
Readings and Course Materials for Module 41h 30m
1 ejercicio de práctica
Techniques: Data Quality Assessments30m
4.4
10 revisionesChevron Right

Principales revisiones sobre Clinical Data Models and Data Quality Assessments

por MKNov 5th 2019

What a great course!! Kudos to the professor for being so detail oriented!! I learned a great deal about the clinical data models from this course!!

por VTSep 14th 2019

Good instructor who took time to explain and walked through each steps of the ETL process. Highly recommended.

Instructores

Avatar

Laura K. Wiley, PhD

Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus
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Michael G. Kahn, MD, PhD

Professor of Clinical Informatics
Department of Pediatrics, Anschutz Medical Campus

Acerca de Sistema Universitario de Colorado

The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond....

Acerca de Programa especializado Clinical Data Science

Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist! This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data. By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data. This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment....
Clinical Data Science

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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