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Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review

Overview of attention for article published in Systematic Reviews, October 2017
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Title
Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review
Published in
Systematic Reviews, October 2017
DOI 10.1186/s13643-017-0597-1
Pubmed ID
Authors

Kate Sabot, Deepthi Wickremasinghe, Karl Blanchet, Bilal Avan, Joanna Schellenberg

Abstract

Social network analysis quantifies and visualizes relationships between and among individuals or organizations. Applications in the health sector remain underutilized. This systematic review seeks to analyze what social network methods have been used to study professional communication and performance among healthcare providers. Ten databases were searched from 1990 through April 2016, yielding 5970 articles screened for inclusion by two independent reviewers who extracted data and critically appraised each study. Inclusion criteria were study of health care worker professional communication, network methods used, and patient outcomes measured. The search identified 10 systematic reviews. The final set of articles had their citations prospectively and retrospectively screened. We used narrative synthesis to summarize the findings. The six articles meeting our inclusion criteria described unique health sectors: one at primary healthcare level and five at tertiary level; five conducted in the USA, one in Australia. Four studies looked at multidisciplinary healthcare workers, while two focused on nurses. Two studies used mixed methods, four quantitative methods only, and one involved an experimental design. Four administered network surveys, one coded observations, and one used an existing survey to extract network data. Density and centrality were the most common network metrics although one study did not calculate any network properties and only visualized the network. Four studies involved tests of significance, and two used modeling methods. Social network analysis software preferences were evenly split between ORA and UCINET. All articles meeting our criteria were published in the past 5 years, suggesting that this remains in clinical care a nascent but emergent research area. There was marked diversity across all six studies in terms of research questions, health sector area, patient outcomes, and network analysis methods. Network methods are underutilized for the purposes of understanding professional communication and performance among healthcare providers. The paucity of articles meeting our search criteria, lack of studies in middle- and low-income contexts, limited number in non-tertiary settings, and few longitudinal, experimental designs, or network interventions present clear research gaps. PROSPERO CRD42015019328.

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The data shown below were collected from the profiles of 7 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 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 184 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 32 17%
Student > Ph. D. Student 22 12%
Researcher 15 8%
Other 13 7%
Student > Bachelor 12 7%
Other 38 21%
Unknown 52 28%
Readers by discipline Count As %
Nursing and Health Professions 28 15%
Social Sciences 28 15%
Medicine and Dentistry 27 15%
Computer Science 7 4%
Business, Management and Accounting 5 3%
Other 28 15%
Unknown 61 33%
Attention Score in Context

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 02 October 2020.
All research outputs
#6,807,817
of 23,006,268 outputs
Outputs from Systematic Reviews
#1,231
of 2,005 outputs
Outputs of similar age
#110,711
of 327,882 outputs
Outputs of similar age from Systematic Reviews
#23
of 46 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 2,005 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one is in the 38th percentile – i.e., 38% 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 327,882 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 65% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.