Digitally Driven Behavioral Interventions: From Design to Health

Digital health technologies are increasingly being used to support behavior change, improve patient engagement, and enhance long-term health outcomes. This course explores how digitally driven behavioral interventions can be designed, implemented, and evaluated within healthcare and health economics and outcomes research (HEOR). Learners will examine the role of behavioral science in digital health, including how behavioral determinants, self-monitoring, feedback systems, motivation, and habit formation influence technology adoption and sustained engagement. The course also explores major technology acceptance frameworks, such as the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM), and demonstrates how these concepts apply to real-world healthcare interventions. Through practical case studies and healthcare examples, learners will explore how digital interventions can influence behavioral outcomes, support clinical improvements, and contribute to broader healthcare and economic value. The course concludes by examining how behavioral outcomes can be integrated into HEOR, reimbursement discussions, and future value-based healthcare models.

After the completion of this course participants will be able to:

• Explain the role of digital health technologies as behavioral interventions within healthcare and HEOR.
• Describe how behavioral science principles support engagement, self-management, and sustained health behavior change.
• Identify key factors that influence adoption and sustained use of digital health technologies.
• Differentiate between major technology adoption frameworks, including UTAUT and the Technology Acceptance Model (TAM).
• Describe the stages of behavioral change, including attitude formation, habit formation, and reinforced habit formation.
• Analyze how digital behavioral interventions influence behavioral, clinical, and economic outcomes.
• Recognize the importance of self-monitoring, feedback loops, personalization, and goal setting in supporting sustained behavior change.
• Discuss the growing role of behavioral outcomes in value assessment, healthcare decision-making, and future HEOR frameworks.

LEVEL: Introductory TRACK: Patient-Centered Research HEOR Competency: 13.3 Prospective and Retrospective Observational Studies (Real-World Evidence) Including Digital Health HEOR Competencies: A resource for HEOR Professionals

The access period once enrolled into the course is 30 days from the date of purchase. After this duration, you will need to re-enroll if you wish to re-enter the course.

Time to complete – approximately 1 hour