Evidence map›Paper›PMID 28875056›Full record

ArticleHealthcare informatics research2017

Blogs as Channels for Disseminating Health Technology Innovations.

Ashish Joshi, Rinzin Wangmo, Chioma Amadi

Abstract read
In one paragraph

Article in Healthcare informatics research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Ashish JoshiCUNY Graduate School of Public Health and Health Policy, New York, NY, USA.
Rinzin WangmoCUNY Graduate School of Public Health and Health Policy, New York, NY, USA.
Chioma AmadiCUNY Graduate School of Public Health and Health Policy, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe objective of this study was to describe the features of health informatics blogs on the Internet.

methodsA search was conducted in August, 2016 using the search engine, Google, and key words: 'mobile health blog,' 'telehealth/telemedicine blog,' 'Electronic Health Record blog,' 'personalized health record blog,' 'population health decision support system blog,' and 'public/population health dashboard blog.' The first 24 blogs resulting from each key word search were recorded, generating 144 blogs. A total of 109 unique blogs resulted after removing duplicates and non-functional sites.

resultsBlogs with '.com' extensions were most prevalent (72%, n = 79). More than half of the blogs (79%, n = 86) were created by industries. Mobile health (88%, n = 96), telehealth (82%, n = 89), and health IT (78%, n = 85) were the predominant topics covered. Health providers (44%, n = 48), industries (33%, n = 36), patients/consumers (25%, n = 27) and payers/insurance providers (19%, n = 21) constituted the most common target audience. Blogs catering to payers commonly used '.org' extension (n = 10 out of 21), compared to '.com' (n = 7) or '.gov' (n = 2) (

conclusionsFurther research is needed to examine the use of blogs as channels of communication of best evidence in health informatics research among diverse stakeholders. The role of blogs as policy informatics tools need to be evaluated in order for stakeholders to collaborate, coordinate and share opportunities and challenges of various public health programs and policies.

Indexed as

BlogsElectronic Health RecordsmHealthPersonal Health RecordsTelehealth

Identifiers

PMID28875056
PMCPMC5572525

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.