Evidence map›Paper›PMID 30861531›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2019

Investigating data accessibility of personal health apps.

Yoojung Kim, Bongshin Lee, Eun Kyoung Choe

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Updating HIPAA for the electronic medical record era.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  6. Not the medical informatics of our founding mothers and fathers, or is it?Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  7. Sleep apps: current limitations and challenges.Sleep science (Sao Paulo, Brazil)
    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

3 authors.

Yoojung KimGraduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea.
Bongshin LeeMicrosoft Research, Redmond, USA.
Eun Kyoung ChoeCollege of Information Studies, University of Maryland, College Park, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDespite the potential values self-tracking data could offer, we have little understanding of how much access people have to "their" data. Our goal of this article is to unveil the current state of the data accessibility-the degree to which people can access their data-of personal health apps in the market. MATERIALS AND

methodsWe reviewed 240 personal health apps from the App Store and selected 45 apps that support semi-automated tracking. We characterized the data accessibility of these apps using two dimensions-data access methods and data types.

resultsMore than 90% of our sample apps (n = 41) provide some types of data access support, which include synchronizing data with a health platform (ie, Apple Health), file download, and application program interfaces. However, the two approachable data access methods for laypeople-health platform and file download-typically put a significant limit on data format, granularity, and amount, which constrains people from easily repurposing the data. DISCUSSION: Personal data should be accessible to the people who collect them, but existing methods lack sufficient support for people in accessing the fine-grained data. Lack of standards in personal health data schema as well as frequent changes in market conditions are additional hurdles to data accessibility.

conclusionsMany stakeholders including patients, healthcare providers, researchers, third-party developers, and the general public rely on data accessibility to utilize personal data for various goals. As such, improving data accessibility should be considered as an important factor in designing personal health apps and health platforms.

Indexed as

Health Records, PersonalMobile ApplicationsPatient Access to RecordsAccess to InformationConsumer Health InformaticsHumansconsumer health informaticsdata accessibilitymobile appspersonal health dataself-tracking

Identifiers

PMID30861531
PMCPMC6433179

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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.