Predictive Modeling and Transforming Clinical Practice

University of Colorado System

This comprehensive course from the University of Colorado System equips learners with the essential knowledge and skills to revolutionize clinical practice through the use of predictive modeling. Through a series of engaging modules, participants will delve into the foundational principles and practical applications of predictive modeling in the clinical setting. The course explores specific challenges and methods crucial for successful clinical implementation, ensuring that clinical data scientists are well-prepared and informed in developing predictive models.

  • Learn the fundamentals of transforming clinical practice using predictive models
  • Gain insight into the specific challenges and methods of clinical implementation
  • Explore the various types of clinical prediction models, including operational and financial models
  • Understand the importance of qualitative methods, data selection, model building, and evaluation in ensuring model usability
  • Discover techniques for model implementation and sustainability, including clinical decision support and changing clinical practice

By the end of the course, participants will have the knowledge and confidence to effectively develop and implement predictive models in clinical practice, ultimately contributing to improved patient care and outcomes.

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Predictive Modeling and Transforming Clinical Practice
Course Modules

Explore the fundamentals of predictive modeling in clinical practice, encompassing topics such as clinical prediction models, model usability, implementation and sustainability techniques, data selection, model building, evaluation, and practical applications.

Introduction: Clinical Prediction Models

Welcome to Predictive Modeling and Transforming Clinical Practice, where you'll embark on a journey to understand the essentials of clinical prediction models. Gain insights into the various types of clinical prediction models, including operational and financial models, and learn how to develop them effectively. This module provides a solid foundation for the subsequent modules and the practical application of predictive modeling in clinical practice.

Tools: Ensuring Model Usability

Delve into the crucial aspect of ensuring model usability through qualitative methods. Learn to choose the right tools, select the appropriate population, collect and analyze data, and observe workflows. This module equips participants with the knowledge and skills necessary to ensure the practical application and usability of predictive models within the clinical setting.

Techniques: Model Implementation and Sustainability

Gain an understanding of the methods for implementing and sustaining clinical prediction models. Explore the fundamentals of clinical decision support and the various techniques for changing clinical practice. This module provides essential insights into the successful implementation and sustainability of predictive models in clinical settings.

Techniques: Data Selection, Model Building, and Evaluation

Explore the intricate process of data selection, model building, and evaluation in the context of clinical prediction models. Understand the significance of clinical data such as encounters, billing data, laboratory data, medications, and more in building effective predictive models. Participants will also engage in practical exercises to apply their knowledge and skills in building and evaluating clinical prediction models.

Practical Application: Developing a Clinical Prediction Model

Embark on practical applications by diving into the development of a clinical prediction model. This module provides a comprehensive overview of the practical aspects of building and implementing predictive models in clinical practice, allowing participants to gain hands-on experience and insights into the real-world application of predictive modeling.

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