Acerca de este Curso

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. 23 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. 23 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

This week describes clinical data models and explains the need for and use of common data models in national and international data networks. We will also cover the features of Entity-Relationship Diagrams (ERDs) to describe the key technical features of data models. ...
9 videos (Total 54 minutos), 4 readings, 1 quiz
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 1s
1 ejercicio de práctica
Clinical Data Models and Common Data Models30m
Semana
2
3 horas para completar

Tools: Querying Clinical Data Models

We take a deep dive into the technical features of clinical data models using MIMIC3 as our example and research common data models using OMOP as our example....
6 videos (Total 59 minutos), 1 reading, 1 quiz
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 230m
1 ejercicio de práctica
Tools: Querying Clinical Data Models30m
Semana
3
3 horas para completar

Techniques: Extract-Transform-Load and Terminology Mapping

This module teaches learners about the processes and challenges with extracting, transforming and loading (ETL) data with real-world examples in data and terminology mapping. ...
6 videos (Total 53 minutos), 1 reading, 1 quiz
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 3s
1 ejercicio de práctica
Techniques: Extract-Transform-Load and Terminology Mapping30m
Semana
4
3 horas para completar

Techniques: Data Quality Assessments

We explore the dimensions of data quality by reviewing its challenges, data quality measurements used to measure it, and data quality rules to assess its acceptability for use....
5 videos (Total 52 minutos), 1 reading, 1 quiz
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 430m
1 ejercicio de práctica
Techniques: Data Quality Assessments30m

Instructores

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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 del 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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