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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*
  • *Tämän työn vastaava kirjoittaja

Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

23 Sitaatiot (Scopus)
49 Lataukset (Pure)

Abstrakti

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.

AlkuperäiskieliEnglanti
Artikkelie49208
JulkaisuJournal of Medical Internet Research
Vuosikerta26
Numero1
DOI - pysyväislinkit
TilaJulkaistu - 2024
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

We want to thank Dr Kenneth Freedland for providing expert consultation and review of earlier versions of this manuscript. This study is supported by the National Library of Medicine (R01LM013107) and the National Cancer Institute (R01CA244777) of the National Institute of Health. CN was supported by the Patient-Centered Outcomes Research Institute (PCORI; award ME-2020C3-21310) and the Altman Clinical and Translational Research Institute (ACTRI) at the University of California, San Diego. The ACTRI is funded from awards issued by the National Center for Advancing Translational Sciences (NIH UL1TR001442). PK is supported by the National Cancer Institute (1U01CA229445) of the National Institute of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or PCORI.

RahoittajatRahoittajan numero
Altman Clinical and Translational Research Institute
National Institutes of Health1U01CA229445, UL1TR001442
National Cancer InstituteR01CA244777
U.S. National Library of MedicineR01LM013107
Patient-Centered Outcomes Research InstituteME-2020C3-21310
National Center for Advancing Translational Sciences
University of California, San Diego

    YK:n kestävän kehityksen tavoitteet

    Tämä tuotos edistää seuraavia kestävän kehityksen tavoitteita:

    1. SDG 3 – Hyvä terveys ja hyvinvointi
      SDG 3 – Hyvä terveys ja hyvinvointi

    Julkaisufoorumi-taso

    • Jufo-taso 2

    !!ASJC Scopus subject areas

    • Health Informatics

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