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Conditions potentially sensitive to a Personal Health Record (PHR) intervention, a systematic review

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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23 X users

Citations

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178 Mendeley
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Title
Conditions potentially sensitive to a Personal Health Record (PHR) intervention, a systematic review
Published in
BMC Medical Informatics and Decision Making, April 2015
DOI 10.1186/s12911-015-0159-1
Pubmed ID
Authors

Morgan Price, Paule Bellwood, Nicole Kitson, Iryna Davies, Jens Weber, Francis Lau

Abstract

Personal Health Records (PHRs) are electronic health records controlled, shared or maintained by patients to support patient centered care. The potential for PHRs to transform health care is significant; however, PHRs do not always achieve their potential. One reason for this may be that not all health conditions are sensitive to the PHR as an intervention. The goal of this review was to discover which conditions were potentially sensitive to the PHR as an intervention, that is, what conditions have empirical evidence of benefit from PHR-enabled management. A systematic review of Medline and CINAHL was completed to find articles assessing PHR use and benefit from 2008 to 2014 in specific health conditions. Two researchers independently screened and coded articles. Health conditions with evidence of benefit from PHR use were identified from the included studies. 23 papers were included. Seven papers were RCTs. Ten health conditions were identified, seven of which had documented benefit associated with PHR use: asthma, diabetes, fertility, glaucoma, HIV, hyperlipidemia, and hypertension. Reported benefits were seen in terms of care quality, access, and productivity, although many benefits were measured by self-report through quasi-experimental studies. No study examined morbidity/mortality. No study reported harm from the PHR. There is a small body of condition specific evidence that has been published. Conditions with evidence of benefit when using PHRs tended to be chronic conditions with a feedback loop between monitoring in the PHR and direct behaviours that could be self-managed. These findings can point to other potentially PHR sensitive health conditions and guide PHR designers, implementers, and researchers. More research is needed to link PHR design, features, adoption and health outcomes to better understand how and if PHRs are making a difference to health outcomes.

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X Demographics

The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
United States 3 2%
Netherlands 1 <1%
Unknown 171 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 17%
Researcher 29 16%
Student > Master 28 16%
Student > Doctoral Student 16 9%
Student > Bachelor 8 4%
Other 27 15%
Unknown 39 22%
Readers by discipline Count As %
Medicine and Dentistry 47 26%
Computer Science 29 16%
Nursing and Health Professions 20 11%
Social Sciences 13 7%
Business, Management and Accounting 5 3%
Other 19 11%
Unknown 45 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 May 2019.
All research outputs
#2,214,311
of 24,149,630 outputs
Outputs from BMC Medical Informatics and Decision Making
#127
of 2,063 outputs
Outputs of similar age
#28,610
of 269,071 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 37 outputs
Altmetric has tracked 24,149,630 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,063 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 269,071 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.