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“In the next ten years, data science and software will do more for medicine than all of the biological sciences together”

Vinod Khosla

Founder, Khosla Ventures


Course Description

Gartner recently named Decision Intelligence (DI) one of the Top Trends for Data and Analytics. DI helps organizations make better decisions. DI brings the best of Artificial Intelligence (AI), machine learning, applied data science, social psychology, behavioral economics, management science, and complex systems analysis to help bridge the gap from “what do we know?” to “what should we do?”   

This master class is designed to improve your ability to create greater impact with data, AI, and human-centered design in healthcare. This course empowers data and analytics professionals to understand and design analytic-centric processes and business models to support automated and semi-automated decisions.

Through a combination of eLearning, structured problem sets, live-web classes, and instructor coaching, you will develop the competencies to take a business challenge through a structured process of problem framing, analytical thinking, systems design, change management, and measurement to improve the use of data for decision making and impact. Using examples from across healthcare, you will build skills needed to lead decision intelligence (DI) projects responsibly and design objectives, metrics, and safety nets for data-driven decisions at scale.


Objectives

By the end of the course, students should have a strong understanding of decision intelligence.    Specifically, you will be able to:

  • Incorporate analytics insights into business workflow such that a continual, positive benefit is seen, and the learning health paradigm is realized based on the economic value  
  • Champion the value of analytics products as well as a multidisciplinary triage team in improving and innovating business processes 
  • Demonstrate the integration of applicable human-centered design techniques throughout the development, implementation, and continual optimization of analytics across healthcare settings
  • Critique results of measurable outcomes from the implementation of analytics for usability, accuracy, equity, and ensure robust engineering methodologies (goal to increase positive and decrease adverse effects)
  • Capture business requirements for decision automation and model the design of those processes using techniques such as Business Process Model and Notation (BPMN), Case Management Model and Notation (CMMN), and Decision Model and Notation (DMN.)
  • Propose health information technology (HIT) enabled communication methods incorporating human factors and human-centered workflows enhancing communication of interprofessional clinical and non-clinical teams and settings
  • Create solutions to mitigate unintended negative consequences (output) of healthcare analytics and information technology (HIT) after evaluation of inputs (cognition, usability, and human factors) and potential failure modes such as change management and responsible AI
  • Design visualizations and information presentation methods enhancing cognitive reasoning, comprehension of complex relationships, and decision support all while optimizing cognitive load
  • Select and use a wide variety of statistical and machine learning tools that are fit for use to analyze data, build automation, and promote interoperability while demonstrating agility in adopting and working across different analytic toolsets

 

Master Class Format

This course occurs over 12 weeks and is comprised of both content learning and practical problem-solving. Each week we will use one or more modalities delivered through this site: Curated microlearning, coached eLearning, or live virtual class.

Audience

This course is designed for seasoned professionals who have experience in workflow design, interoperability, quantitative data analysis, or data management.  While expert-level proficiency in these areas is not a prerequisite, knowledge of healthcare and caregiver workflows is suggested.

  • Advanced statistical or machine learning methods are not required.
  • Learners should have basic proficiency in a data visualization tool such as Tableau, Python, Excel, R, or SAS.
  • Learners who lack the healthcare or analytics experience can expect to spend 3+ additional hours a week.

 

Time Commitment

Learn: 

  • 2 hours per week for live instructor-led workshops
  • 5-7+ hours per week to consume instructional content

Practice: 

  • 3+ hours per week to complete assignments

Engage: 

It’s up to you. Opportunities include:

  • A private Discussion Forum to network with instructors and other learners
  • Team-based project work (2 – 4 hours during the second part of the course for the capstone project)


Experience blended learning

  • Learn through videos, activities, and discussion assignments

  • Practice what you have learned by completing detailed problem sets
  • Earn a certification of completion based upon submitted assignments and completing a final assessment with a passing score of over 80%







Course curriculum

  • 1

    Getting Started

    • Course & Community Introduction

    • Executive Perspective (Dr. Mark Briesacher) on the importance of decision intelligence

    • Welcome to the course

    • Course Syllabus

    • Executive Perspective (Marguerite Samms) on Leadership Development and your role in the future of healthcare

    • How This Course Works

    • Navigating the eLearning Platform

    • How to prepare for this course

    • Video Introduction from your instructor

    • Introduce yourself!

    • Getting started with your Disqus account

    • Before we begin...
  • 2

    Week 1: Welcome and Overview

    • Pretest

    • Overview

    • Executive Perspective (Albert Marinez) Your role in Analytics

    • The Product Mindset

    • DESIGN: Design Thinking for Data-Driven Digital Innovation

    • STRATEGY: Read: Strategy Process for Data Products

    • STRATEGY: Watch - Strategic Choices

    • What is a Data Product?

    • PRODUCT: A Brief History of Product Management

    • PRODUCT - Introducing the Product Lifecycle

    • Discussion: Designing Data Products

    • Slides

    • Live Class

    • Knowledge Check

    • Explore More
  • 3

    Week 2: The Culture and Context of Healthcare

    • Pretest

    • Overview

    • WATCH: If Restaurants Behaved Like Healthcare

    • DISCUSS: What if Restaurants Billed Like Hospitals?

    • READ: Healthcare Incentives and the Impact of the EHR

    • READ: ​How Healthcare Services Are Paid​

    • READ: ​Electronic Health Records: More Than Just a Way to Bill

    • READ: How National and State Healthcare Policy Drives Health Informatics Investment

    • READ: Health IT Policy and Impact on Data Champions

    • The Role of Design in Reducing Physician Burnout

    • Introduction to our Product, Design, & Strategy GPS

    • Intermountain Decision Intelligence Curriculum Design - Decision Intelligence MasterClass Map

    • A day in the life of Decision Intelligence Analyst

    • CONSIDER: How can we design systems of intelligence that augment understanding?

    • PRODUCT: Understanding the Problem Space

    • MIRO: Getting to know you

    • Live Class

    • Knowledge Check

    • Explore More
  • 4

    Week 3: Human-Centered Design for Data Products

    • Pretest

    • Overview

    • Watch: Developing Empathy for Your Target Audience

    • DESIGN: Stage 1 in the Design Thinking Process: Empathize with Your Users

    • TRY: Design Thinking Process for Empathy

    • STRATEGY: How to define your strategic problem

    • Try: Define your strategic problem

    • TRY: Reducing Cognitive Biases

    • Live Class

    • Evaluation

    • Nystrom - How Should Risks Posed by Decision Support Be Managed?

    • Nystrom (2018) - Methods for patient centered interface design of test result display

    • James J. Gibson From: The Ecological Approach to Visual Perception Chapter 8 THE THEORY OF  AFFORDANCES

    • Knowledge Check

    • Summary: Developing Empathy for our User

    • Explore More
  • 5

    Week 4: Discovery Day

    • Pretest

    • Overview

    • Read: Wicked Problems in Healthcare

    • Watch: Wicked Problems

    • Try: What makes a wicked problem?

    • DESIGN: Stage 2 in the Design Thinking Process: Define

    • TRY: Problem Framing (Creating a POV)

    • READ: Framing a "How Might We" Question

    • Watch: How Might We?

    • TRY: How might we

    • Watch: Google Using "How might we's"

    • Live Class

    • Watch: Discovery Day Introduction from Dr. Mark Briesacher

    • Watch: Discovery Day Introduction from Dr. Shannon Phillips

    • Watch: Discovery Day Introduction from Adam Freebairn

    • Watch: Discovery Day Introduction from Mike Woodruff

    • Knowledge Check

    • Explore More
  • 6

    Week 5: Systems and Process Design

    • Pretest

    • Overview

    • Watch: Using Stories to Build Empathy

    • Watch: How to make toast

    • Try: How to make toast

    • READ: The Interoperability Crisis

    • Watch: Conducting User Interviews

    • Watch: Business Process Modeling Using BPMN

    • Try: Business Process Modeling

    • Read: Interoperability and the learning health system

    • Interoperability to the Rescue

    • Slides: Levels of Interoperability

    • Live class

    • Knowledge Check

    • Explore More
  • 7

    Week 6: Define Day

    • Pretest

    • Overview

    • DESIGN: Stage 3 in the Design Thinking Process: Ideate

    • Watch: Build a tower, build a team

    • Try: What we can learn from the marshmallow challenge?

    • Read: A simple introduction to personas

    • Try: Creating your customer

    • Read: Creating User Stories for Clinical Decision Support

    • Try: User Stories

    • Live Class

    • Knowledge Check

    • Explore More
  • 8

    Week 7: Workflow and Operations

    • Pretest

    • Overview

    • Read: How to Generate Strategic Possibilities

    • Watch: STRATEGY - Generate possibilities

    • Try: Wicked Problem: Generate possibilities

    • Read: BJ Fogg’s B=MAP Behavior Model

    • Read: What would have to be true?

    • Watch: What Would Have to Be True?

    • Try: Wicked Problem What would have to be true?

    • Read: Hardwiring Best Practices

    • Live class

    • Knowledge Check

    • Explore More
  • 9

    Week 8: Design Constraints

    • Pretest

    • Overview

    • Read: Divergence as a Design Constraint

    • Read: The Power of Constraints. Don’t fight them...

    • Try: Design Constraints

    • Read: Identifying Barriers

    • Read: How to Identify Barriers

    • Try: Identifying Barriers

    • Live class

    • Knowledge Check

    • Explore More
  • 10

    Week 9: Design Sprint: Part 1

    • Pretest

    • Overview

    • Watch: Autonomous Delivery Robot

    • Read: Introduction to Sprint

    • Watch: How Relay® Robot Saves Hospital Labs Critical Minutes

    • Try: Sprint Planning

    • Read: Stage 4 in the Design Thinking Process: Prototype

    • Watch: Prototyping in Design Thinking

    • Read: Prototyping in Design Thinking - How to Avoid Six Common Pitfalls

    • Try: Prototyping

    • Watch: how to prototype inexpensively

    • Live class

    • Slides: UX Design Presentation on Prototyping

    • Knowledge Check

    • Explore More
  • 11

    Week 10: Design Sprint: Part 2

    • Pretest

    • Overview

    • Watch: The role of testing

    • Read: Stage 5 in the Design Thinking Process: Test

    • Try: Testing your idea

    • Download: Common Testing approaches

    • Watch: Testing to learn

    • Read: Tips on designing your tests

    • Try: Testing for your wicked problem

    • Live class

    • Evaluative Research (Slides)

    • Knowledge Check

    • Explore More
  • 12

    Week 11: Build, Release and Measurement

    • Pretest

    • Overview

    • Read: How to Make a Strategic Choice and Move Forward

    • Read: Product Launch Readiness

    • Nielsen Heuristic evaluation of user interfaces

    • SUS - A quick and dirty usability scale

    • Read: Determining what individual SUS scores mean

    • Read: Product Release

    • Try: Release Planning at AirBNB

    • Live class

    • Knowledge Check
  • 13

    Week 12: Demo Day

    • Pretest

    • Overview

    • Read: Product Roadmaps

    • Try: Different types of roadmaps

    • Read: Pivot or Persevere

    • Live class

    • Knowledge Check
  • 14

    Taking the next steps

    • Comprehensive Examination

    • Next Steps

    • Course Evaluation