CoChat
Sign Up
Cited by 508Mobile Health and mHealth ApplicationsHealth, Technology, Consumer BehaviorArtificial Intelligence in Healthcare and Education

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Digital health: a path to validation

Open access
Mathews, Simon C., McShea, Michael J., Hanley, Casey L., Ravitz, Alan, Labrique, Alain B., Cohen, Adam B.·2019·npj Digital Medicine
DOI 10.1038/s41746-019-0111-3PMC PMC6550273
Open this paper in CoChat — free accountOpen PDF

Abstract

Digital health solutions continue to grow in both number and capabilities. Despite these advances, the confidence of the various stakeholders — from patients and clinicians to payers, industry and regulators — in medicine remains quite low. As a result, there is a need for objective, transparent, and standards-based evaluation of digital health products that can bring greater clarity to the digital health marketplace. We believe an approach that is guided by end-user requirements and formal assessment across technical, clinical, usability, and cost domains is one possible solution. For digital health solutions to have greater impact, quality and value must be easier to distinguish. To that end, we review the existing landscape and gaps, highlight the evolving responses and approaches, and detail one pragmatic framework that addresses the current limitations in the marketplace with a path toward implementation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41746-019-0111-3

Cites

24 of 24 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Regulatory–Clinical–Technology risk paradigm. Examples of increasingly complex clinical applications of technology and their corresponding regulatory contexts are presented in this figure
Fig. 1 Regulatory–Clinical–Technology risk paradigm. Examples of increasingly complex clinical applications of technology and their corresponding regulatory contexts are presented in this figureCC BY · PubMed Central
Fig. 2 Traditional Product Lifecycle with Proposed Digital Health Scorecard Added. A representative depiction of the steps within a traditional product development lifecycle is presented in the top half of the figure. The role of an independent evaluator and its relationship with the broader marketplace and product lifecycle is also presented
Fig. 2 Traditional Product Lifecycle with Proposed Digital Health Scorecard Added. A representative depiction of the steps within a traditional product development lifecycle is presented in the top half of the figure. The role of an independent evaluator and its relationship with the broader marketplace and product lifecycle is also presentedCC BY · PubMed Central
Fig. 3 Components of Digital Health Scorecard. The four domains of a digital health scorecard with example considerations are detailed in this figure. Their relationship to an assessment of stakeholder requirements is also presented
Fig. 3 Components of Digital Health Scorecard. The four domains of a digital health scorecard with example considerations are detailed in this figure. Their relationship to an assessment of stakeholder requirements is also presentedCC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 24 references

Cited by

Sorted by citations

Items 201–300 of 508

Related

See all

Metadata

Authors
Mathews, S. C., McShea, M. J., Hanley, C. L., Ravitz, A., Labrique, A. B., & Cohen, A. B.
Affiliations
Johns Hopkins University (US)
Corresponding author
Mathews, Simon C.
ORCID
Venue
npj Digital Medicine
Publisher
Springer Science and Business Media LLC
Published
2019-05-13
Volume
2
Issue
1
Pages
38-38
ISSN
2398-6352 (ISSN-L)
DOI
10.1038/s41746-019-0111-3
PMC
PMC6550273
OpenAlex
W2946661638
Cited by
508
References
24
Citations by year
2026: 52 · 2025: 81 · 2024: 107 · 2023: 85 · 2022: 73 · 2021: 60 · 2020: 44 · 2019: 6
FWCI
8.41
Type
journal article
Language
en
Open access
Licence
Locations
  • npj Digital Medicine (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
digital health, validation framework, end-user needs, clinical evaluation, usability, cost evaluation, standards-based evaluation, stakeholder confidence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review