The Digital Therapeutics Real-World Evidence Framework: An Approach for Guiding Evidence-Based Digital Therapeutics Design, Development, Testing, and Monitoring

Meelim Kim, Kevin Patrick, Camille Nebeker, Job Godino, Spencer Stein, Predrag Klasnja, Olga Perski, Clare Viglione, Aaron Coleman, Eric Hekler

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
1 Downloads (Pure)

Abstract

Digital therapeutics (DTx) are a promising way to provide safe, effective, accessible, sustainable, scalable, and equitable approaches to advance individual and population health. However, developing and deploying DTx is inherently complex in that DTx includes multiple interacting components, such as tools to support activities like medication adherence, health behavior goal-setting or self-monitoring, and algorithms that adapt the provision of these according to individual needs that may change over time. While myriad frameworks exist for different phases of DTx development, no single framework exists to guide evidence production for DTx across its full life cycle, from initial DTx development to long-term use. To fill this gap, we propose the DTx real-world evidence (RWE) framework as a pragmatic, iterative, milestone-driven approach for developing DTx. The DTx RWE framework is derived from the 4-phase development model used for behavioral interventions, but it includes key adaptations that are specific to the unique characteristics of DTx. To ensure the highest level of fidelity to the needs of users, the framework also incorporates real-world data (RWD) across the entire life cycle of DTx development and use. The DTx RWE framework is intended for any group interested in developing and deploying DTx in real-world contexts, including those in industry, health care, public health, and academia. Moreover, entities that fund research that supports the development of DTx and agencies that regulate DTx might find the DTx RWE framework useful as they endeavor to improve how DTxcan advance individual and population health.

Original languageEnglish
Article numbere49208
JournalJournal of Medical Internet Research
Volume26
Issue number1
DOIs
Publication statusPublished - 2024
Publication typeA1 Journal article-refereed

Keywords

  • accessible
  • decision
  • decision making
  • decision-based evidence-making
  • development
  • digital therapeutics
  • medication adherence
  • monitoring
  • pharmaceuticals
  • public health
  • real-world data
  • real-world evidence
  • safe
  • testing
  • therapeutics

Publication forum classification

  • Publication forum level 2

ASJC Scopus subject areas

  • Health Informatics

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