Evidence map›Paper›PMID 40502275›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2025

A Method for Enabling Digital Health Technologies in Clinical and Translational Research at an Academic Medical Center.

Cindy Chen, Laura R Bradford, Melissa A Epstein, J Travis Gossey, Mohammad N Mansour, Christy M O'Connor, Brian J Tschinkel, Thomas R Campion

Abstract read
PubMed Full text at PMC
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Cindy ChenInformation Technologies and Services Department, Weill Cornell Medicine, New York, NY.
Laura R BradfordOffice of General Counsel, Weill Cornell Medicine, New York, NY.
Melissa A EpsteinOffice of Human Research Protections, Weill Cornell Medicine, New York, NY.
J Travis GosseyPhysician Organization Information Services, Weill Cornell Medicine, New York, NY.
Mohammad N MansourInformation Technologies and Services Department, Weill Cornell Medicine, New York, NY.
Christy M O'ConnorOffice of Compliance, Weill Cornell Medicine, New York, NY.
Brian J TschinkelInformation Technologies and Services Department, Weill Cornell Medicine, New York, NY.
Thomas R CampionInformation Technologies and Services Department, Weill Cornell Medicine, New York, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Federal- and state-level governance as well as local institutional oversight are changing rapidly to address the accelerated growth in the usage of digital health technologies (DHT) -such as apps, wearables, and websites-to enable clinical and translational research. While studies have described frameworks for assessing and/or implementing individual DHTs, to our knowledge there are none describing how to implement and support multiple DHTs at an academic medical center (AMC). A multi-disciplinary team including information technology, institutional review board, legal, and privacy professionals identified 33 items to evaluate as part of onboarding studies using DHTs. In a one-year period at one AMC, we applied the novel instrument to review 98 requests for research (93) and non-research (5) use of DHTs. The 33-item instrument may be valuable to researchers and practitioners in other settings seeking to scale institutional support for DHTs.

Identifiers

PMID40502275
PMCPMC12150704

What OpenQuestion holds

Textmetadata
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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.