Evidence map›Paper›PMID 35982593›Full record

ArticleHealthcare informatics research2022

Clinical Evaluation of Digital Therapeutics: Present and Future.

Ki Young Huh, Jaeseong Oh, SeungHwan Lee, Kyung-Sang Yu

Abstract read
In one paragraph

Article in Healthcare informatics research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Digital Therapeutics in China: Comprehensive Review.Journal of medical Internet research · 2025
    Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Trial
  7. Article
  8. Article
  9. Diving into the Regulatory Landscape of Digital Therapeutics.Therapeutic innovation & regulatory science · 2026
    Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Co-Creation in the Development of Digital Therapeutics: A Narrative Review.International journal of environmental research and public health · 2024
    Review
  18. Review
  19. Article
  20. Adoption of Digital Therapeutics in Europe.Therapeutics and clinical risk management · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ki Young HuhDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Korea.
Jaeseong OhDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Korea.
SeungHwan LeeDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Korea.
Kyung-Sang YuDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Korea.

Funding

Ministry of Health and Welfare
6 · The paper itself

Abstract

objectivesDigital therapeutics (DTx) are software-based therapeutic interventions based on clinical evidence. Randomized clinical trials (RCTs) are often the source of clinical evidence, similar to conventional drugs or medical devices. However, novel approaches such as the use of real-world data or digital biomarkers are also utilized. This article aimed to review how DTx products have been clinically evaluated.

methodsDTx products approved by the US Food and Drug Administration as of 2020 were reviewed and products with sufficient published information were selected. Pivotal clinical trials were analyzed according to the elements of the Consolidated Standards of Reporting Trials (CONSORT) guideline. Case reviews were presented for other clinical evaluation strategies, considering the small number of publications.

resultsMost approved DTx products used RCTs for clinical evaluations. Similar to conventional RCTs, parallel-group designs with statistical hypothesis testing were adopted. However, DTx trials were often not blinded due to practical issues and involved various comparator groups. In addition, DTx products could be readily evaluated in home-based settings and delivered through the internet. Other evaluation approaches included retrospective analyses using insurance claims data or usage data, which enabled long-term evaluations of effectiveness. Digital biomarkers obtained from real-time and continuous log data were also used to improve the objectiveness of endpoints.

conclusionsRCTs accounted for the majority of DTx evaluations. The designs of DTx trials were comparable to those of drug or device trials, but blinding and comparator elements were often different. Furthermore, the use of real-world data and digital biomarkers are also being tried.

Indexed as

BiomarkersDigital TechnologyRandomized Controlled TrialTherapeuticsWearable Electronic Devices

Identifiers

PMID35982593
PMCPMC9388922

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.