Health Care Transformation

  • Executive Education
Businesspeople and health care providers in a meeting.
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Registration Deadline: August 22

This multi-program learning journey is designed to offer an integrated experience of two Harvard Medical School executive programs—AI in Health Care: From Strategies to Implementation and Leading Digital Transformation in Health Care—along with additional learning modules to deliver a highly impactful curriculum on digital transformation and AI in health care.

  • Online; Self-Paced

Self-paced learning complemented by live sessions with faculty and weekly office hours conducted by program leaders.

$5,150

Flexible payment and team-based learning options are available.

Certificate

Upon completion of this program, you will receive a digital certificate from Harvard Medical School.

18 Weeks, 4-6 Hours/Week

Each week you will engage with recorded video lectures from faculty, attend webinars and office hours, complete quizzes and required activities, engage in moderated discussion groups with, and work on your final project, if required.

On This Page

Overview

The 18-week Health Care Transformation program is designed to offer an integrated experience of two online executive programs from Harvard Medical School —AI in Health Care and Leading Digital Transformation in Health Care— along with additional learning modules to deliver a highly impactful curriculum on digital transformation and AI in health care. Participants will gain the expertise to implement forward-looking digital strategies, establish robust AI adoption frameworks, and leverage the potential of scaling AI technologies for innovation.

Learning Objectives

  • Develop a comprehensive framework for implementing AI at scale within health care organizations to enhance operational efficiency and patient care.
  • Strategize and manage the adoption of emerging digital technologies effectively to drive innovation and streamline health care processes.
  • Demonstrate a thorough understanding of the challenges involved in scaling AI solutions, and devise strategies to overcome these obstacles in health care settings.
  • Create detailed tactical and strategic plans for integrating and implementing advanced technologies, ensuring their transformative impact on health care delivery.
  • Identify new opportunities for AI in health care to address unmet needs.
  • Assess the ethical implications and potential biases of AI technologies in health care settings.
  • Recognize the lessons learned from real-world digital health transformation experiences and pilots, and create your own action plan through the capstone project.
  • Identify the elements of effective change management as well as the critical success factors for implementing digital transformation within your organization.
  • Apply best practices and program insights to day-to-day operations and long-term strategic priorities.
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Questions?

Contact one of our program advisors at learner.success@emeritus.org.

This Harvard Medical School Executive Education program is taught by HMS faculty and is promoted by Emeritus. Emeritus is responsible for advertising, marketing, registration, and collecting payment.

Curriculum

This learning journey offers an all-encompassing, in-depth exploration of digital transformation and AI in health care, enabling professionals to acquire new knowledge and develop advanced skills. Participants will complete two executive programs—AI in Health Care and the Leading Digital Transformation in Health Care—with additional learning modules.

  • Module 1: The History and Foundations of AI
  • Module 2: A Framework for the AI Development Pipeline
  • Module 3: From the Lab to the Real World
  • Module 4: Transparency, Reproducibility, and Generalizability in AI
  • Module 5: The Potential for Bias and Harm in AI
  • Module 6: AI for Startups
  • Module 7: AI for Wearable Data
  • Module 8: Live Session — Capstone Presentations
  • Module 1: Transforming, Disrupting, or Staying Competitive
  • Module 2: Enabling Technologies
  • Module 3: Transformation Management Skills and Practices — Fostering Change Management
  • Module 4: Transformation Management Skills and Practices — Establishing Digital Transformation and Innovation
  • Module 5: Transformation Management Skills and Practices — Creating a Digital Culture
  • Module 6: Creating the Transformation Plan
  • Module 0: Program Orientation
    Explore the program's objectives and expected learning outcomes, and gain an overview of the health care industry, focusing on the transformative role of AI and digital technologies.
  • Module 1: Management Education
    Delve into the fundamental concepts of management education in health care, and discuss various leadership styles and effective management practices.
  • Module 2: Organizational Learning
    Discover strategies for fostering a learning organization within the health care sector, emphasizing the importance of continuous professional development, and describing the potential business value for AI pilots.
  • Module 3: Innovation Management
    Examine the process of innovation in health care, and gain tools and techniques for managing innovation effectively by proposing an approach for integrating an AI innovation group.
  • Module 4: Framework Analysis 1
    Analyze techniques for evaluating AI implementation frameworks and their applicability in health care. Analyze the elements of a peer's framework for implementing AI, and integrate peer feedback.
  • Module 5: Dealing with Vendors
    Delve into best practices for selecting and managing AI vendors, including critical considerations for vendor evaluation and relationship management. Describe diligence activities associated with examining an AI-based product or service.
  • Module 6: Managing AI Limitations and Potential Problems
    Identify and manage potential challenges in AI implementation, and develop strategies for mitigating risks and addressing limitations.
  • Module 7: Framework Analysis 2
    Refine AI implementation frameworks, incorporating feedback to enhance framework effectiveness. Analyze the elements of a peer's framework for implementing AI, and integrate peer feedback.
  • Module 8: Mid-Program Summary
    Discuss the application of AI insights in real-world health care settings, and reflect on the learnings gained in approaching AI solutions in health care.
  • Module 9: Strategic Context
    Set the strategic context for AI in health care by aligning AI initiatives with organizational strategy. Defend the AI strategic context selected for an organization.
  • Module 10: Governance
    Explore governance frameworks for AI implementation, and outline a charter for an AI governance committee.
  • Module 11: Talent Management
    Examine the potential impact of AI on organizational talent management in health care, and describe the potential impact of AI on an organization's talent needs.
  • Module 12: Data Management
    Delve into best practices for managing data in AI projects by analyzing data management practices to ensure data quality, security, and compliance.
  • Module 13: Technology Architecture
    Assess the impact of AI on technology architecture, and describe methods used to assess the impact of an AI-based application on an organization’s infrastructure.
  • Module 14: Framework Analysis 3
    Discover advanced techniques for framework analysis, enhancing the effectiveness of AI implementation frameworks. Analyze the elements of a peer's framework for implementing AI, and integrate that feedback into your framework.
  • Module 15: Implementation Issues
    Compare successful and unsuccessful AI implementation projects, and learn from failures and best practices.
  • Module 16: Industry Participation
    Explore and discuss the importance of participating in AI-centered industry forums and communities.
  • Module 17: Framework Analysis 4
    Finalize and refine AI implementation frameworks, preparing them for real-world application. Analyze the elements of a peer's framework for implementing AI, and integrate that feedback into your framework.
  • Module 18: Program Wrap-Up
    Summarize program learnings, and engage in final discussions while exploring future directions in AI for health care. Develop a comprehensive framework for implementing AI.

Teaching Team

Andrew Beam.

Andrew Beam

PhD

  • Chief Technology Officer, Lila Sciences, Inc.
  • Associate Professor of Epidemiology, Harvard T.H. Chan School of Public Health
John Glaser.

John Glaser

PhD

  • Executive-in-Residence, Harvard Medical School Executive Education

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