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Towards successful coordination of electronic health record based-referrals: a qualitative analysis

Overview of attention for article published in Implementation Science, July 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

twitter
1 tweeter
wikipedia
1 Wikipedia page

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
150 Mendeley
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Title
Towards successful coordination of electronic health record based-referrals: a qualitative analysis
Published in
Implementation Science, July 2011
DOI 10.1186/1748-5908-6-84
Pubmed ID
Authors

Sylvia J Hysong, Adol Esquivel, Dean F Sittig, Lindsey A Paul, Donna Espadas, Simran Singh, Hardeep Singh

Abstract

Successful subspecialty referrals require considerable coordination and interactive communication among the primary care provider (PCP), the subspecialist, and the patient, which may be challenging in the outpatient setting. Even when referrals are facilitated by electronic health records (EHRs) (i.e., e-referrals), lapses in patient follow-up might occur. Although compelling reasons exist why referral coordination should be improved, little is known about which elements of the complex referral coordination process should be targeted for improvement. Using Okhuysen & Bechky's coordination framework, this paper aims to understand the barriers, facilitators, and suggestions for improving communication and coordination of EHR-based referrals in an integrated healthcare system.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 150 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Malaysia 1 <1%
Ireland 1 <1%
Indonesia 1 <1%
Canada 1 <1%
Sierra Leone 1 <1%
Unknown 141 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 38 25%
Researcher 32 21%
Student > Ph. D. Student 21 14%
Student > Postgraduate 9 6%
Student > Doctoral Student 8 5%
Other 23 15%
Unknown 19 13%
Readers by discipline Count As %
Medicine and Dentistry 58 39%
Social Sciences 20 13%
Computer Science 13 9%
Nursing and Health Professions 12 8%
Psychology 7 5%
Other 19 13%
Unknown 21 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 June 2019.
All research outputs
#4,138,910
of 15,211,297 outputs
Outputs from Implementation Science
#942
of 1,463 outputs
Outputs of similar age
#84,183
of 329,582 outputs
Outputs of similar age from Implementation Science
#1
of 3 outputs
Altmetric has tracked 15,211,297 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,463 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 329,582 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them