Source: Health Catalyst | 2019
Presenter: Jason Jones, PhD
Table of Contents
Introduction 0:19
3 Levels of Predictive Model Understanding 21:57
Functional Sample Questions 26:46
Contextual Sample Questions 38:26
Operational Sample Questions 48:55
Q&A 57:13
In healthcare we tend to think of predictive or prescriptive model building and deployment as technical challenges. We do not put enough emphasis on the importance of change management. This disorientation leads to uneven adoption and results. In this webinar Jason Jones discusses and demonstrates three perspectives, accompanied by tools, to help you drive action and deliver better outcomes.
We develop predictive and prescriptive models in healthcare to improve Quadruple Aim outcomes—population health, patient experience, reduced cost, and positive provider work life. Successful adoption of predictive and prescriptive models heavily depends upon behavior change. This requires more than technical accuracy. While prediction algorithms abound, tools to facilitate change management remain scarce. During this webinar, we will discuss how to achieve model understanding using three perspectives: functional, contextual, and operational. View the webinar to learn: – Why a predictive or prescriptive model endeavor is more a change management challenge than a technical one – How to apply three types of model understanding to a use case in your own organization In this webinar, Jason Jones, PhD, Chief Data Scientist at Health Catalyst discusses and provides examples of our work using three perspectives of understanding to help clinical and operational leaders achieve value from predictive and prescriptive models. Investing time and effort to ensure model understanding is necessary for broad scale adoption.