Evidence map›Paper›PMID 37485467›Full record

ArticleJAMIA open2023

CardinalKit: open-source standards-based, interoperable mobile development platform to help translate the promise of digital health.

Oliver Aalami, Mike Hittle, Vishnu Ravi, Ashley Griffin, Paul Schmiedmayer, Varun Shenoy, Santiago Gutierrez, Ross Venook

Abstract read
In one paragraph

Article in JAMIA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. 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

8 authors.

Oliver AalamiStanford Byers Center for Biodesign, Stanford University School of Medicine, Palo Alto, California, USA.
Mike HittleDepartment of Epidemiology, Stanford University School of Medicine, Palo Alto, California, USA.
Vishnu RaviStanford Byers Center for Biodesign, Stanford University School of Medicine, Palo Alto, California, USA.
Ashley GriffinDepartment of Health Policy, Stanford University School of Medicine; VA Palo Alto Health Care System, Palo Alto, California, USA.ORCID https://orcid.org/0000-0002-1535-0797
Paul SchmiedmayerStanford Byers Center for Biodesign, Stanford University School of Medicine, Palo Alto, California, USA.ORCID https://orcid.org/0000-0002-8607-9148
Varun ShenoyStanford Byers Center for Biodesign, Stanford University School of Medicine, Palo Alto, California, USA.
Santiago GutierrezStanford Byers Center for Biodesign, Stanford University School of Medicine, Palo Alto, California, USA.
Ross VenookStanford Byers Center for Biodesign, Stanford University School of Medicine, Palo Alto, California, USA.

Funding

Stanford BSSR Pre-Doctoral Training Program at the Intersection of Data Sciences with Behavioral, Social, and Population Health ResearchT32HL151323 · NHLBI · STANFORD UNIVERSITY · PI Michelle Christina Odden, David H Rehkopf · 2020 to 2026
$1.6M
NHLBI NIH HHS T32 HL151323
6 · The paper itself

Abstract

Smartphone devices capable of monitoring users' health, physiology, activity, and environment revolutionize care delivery, medical research, and remote patient monitoring. Such devices, laden with clinical-grade sensors and cloud connectivity, allow clinicians, researchers, and patients to monitor health longitudinally, passively, and persistently, shifting the paradigm of care and research from low-resolution, intermittent, and discrete to one of persistent, continuous, and high resolution. The collection, transmission, and storage of sensitive health data using mobile devices presents unique challenges that serve as significant barriers to entry for care providers and researchers alike. Compliance with standards like HIPAA and GDPR requires unique skills and practices. These requirements make off-the-shelf technologies insufficient for use in the digital health space. As a result, budget, timeline, talent, and resource constraints are the largest barriers to new digital technologies. The CardinalKit platform is an open-source project addressing these challenges by focusing on reducing these barriers and accelerating the innovation, adoption, and use of digital health technologies. CardinalKit provides a mobile template application and web dashboard to enable an interoperable foundation for developing digital health applications. We demonstrate the applicability of CardinalKit to a wide variety of digital health applications across 18 innovative digital health prototypes.

Indexed as

androiddigital healthiOSmobile app developmentopen-source software

Identifiers

PMID37485467
PMCPMC10356573

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.