Evidence map›Paper›PMID 23759409›Full record

ReviewJournal of diabetes science and technology2013

The current status of mHealth for diabetes: will it be the next big thing?

David C Klonoff

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of diabetes science and technology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 6 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

57 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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

1 author.

David C KlonoffMills-Peninsula Health Services, 100 S. San Mateo Dr., San Mateo, CA 94401, USA. dklonoff@diabetestechnology.org

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

mHealth is an emerging concept in health care and uses mobile communications devices for health services and information. Mobile phones, patient monitoring devices, tablets, personal digital assistants, and other wireless devices can be part of mHealth systems. With mHealth systems, glucose data can now be automatically collected, transmitted, aggregated with other physiologic data, analyzed, stored, and presented as actionable information. mHealth systems use mobile decision support software applications (or apps) to assist or direct health care professionals to make decisions, or they can assist or direct patients to make decisions without waiting for input from a clinician. With real-time decision support for patients, appropriate actions can be taken in real time without waiting to see a clinician. Decisions can be personalized if individual treatment goals and personal preferences for treatment are inputted into an app. Few mHealth apps for diabetes have been rigorously tested. Outcome studies of the use of mHealth for diabetes from the literature have shown the potential for benefits, but higher-quality studies are needed. Regulatory approval of mHealth products will require demonstration of safety and effectiveness, especially where information and trends are not just presented to patients, but used to make treatment recommendations. Three additional hurdles must be overcome to facilitate widespread adoption of this technology, including demonstration of the following: (1) privacy to satisfy regulators, (2) clinical benefit to satisfy clinicians, and (3) economic benefit to satisfy payers. mHealth for diabetes is making rapid strides and is expected to be a transforming technology that will be the next big thing.

Indexed as

Diabetes MellitusCell PhoneHumansMobile ApplicationsTelemedicine

Identifiers

PMID23759409
PMCPMC3869144

What OpenQuestion holds

Textmetadata
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.