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Information exchange networks of health care providers and evidence-based cardiovascular risk management: an observational study

Overview of attention for article published in Implementation Science, January 2017
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)

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Title
Information exchange networks of health care providers and evidence-based cardiovascular risk management: an observational study
Published in
Implementation Science, January 2017
DOI 10.1186/s13012-016-0532-1
Pubmed ID
Authors

Naomi Heijmans, Jan van Lieshout, Michel Wensing

Abstract

Although a wide range of preventive and clinical interventions has targeted cardiovascular risk management (CVRM), outcomes remain suboptimal. Therefore, the question is what additional determinants of CVRM and outcomes can be identified and addressed to optimize CVRM. In this study, we aimed to identify new perspectives for improving healthcare delivery and explored associations between information exchange networks of health care providers and evidence-based CVRM. This observational study was performed parallel to a randomized clinical trial which aimed to improve professional performance of practice nurses in the Netherlands. Information exchange on medical policy for CVRM ("general information networks") and CVRM for individual patients ("specific information networks") of 180 health professionals in 31 general practices was measured with personalized questionnaires. Medical record audit was performed concerning 1620 patients in these practices to document quality of care delivery and two risk factors (systolic blood pressure (SBP) and LDL cholesterol level). Hypothesized effects of five network characteristics (density, frequency of contact, centrality of CVRM-coordinators, homophily on positive attitudes for treatment target achievement, and presence of an opinion leader for CVRM) constructed on both general and specific information exchange networks were tested and controlled for practice and patient factors using logistic multilevel analyses. Odds for adequate performance were enhanced in practices with an opinion leader for CVRM (OR 2.75, p < .05). Odds for achievement of SBP targets were reduced in practices who had networks with low homophily on positive attitudes for SBP and LDL targets (homophily for SBP targets OR 0.57, p < .05 and OR 0.60, p < .05, homophily for LDL targets OR 0.59, p < .05 and OR 0.61, p < .05 in general and specific information networks, respectively). No effects of network characteristics on cholesterol were found. Delivery of evidence-based CVRM is associated with homophily of clinical attitudes and presence of opinion leaders in primary care teams. These results signal the potential of social networks to be taken into account in further attempts to improve the implementation of evidence-based care for CVRM. Future research is needed to identify and formulate optimal strategies for using opinion leaders to improve CVRM. Future interventions may be more effective if they target a common vision on CVRM within practices.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 99 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 15%
Researcher 14 14%
Student > Bachelor 11 11%
Other 8 8%
Student > Ph. D. Student 8 8%
Other 15 15%
Unknown 28 28%
Readers by discipline Count As %
Medicine and Dentistry 19 19%
Nursing and Health Professions 14 14%
Social Sciences 12 12%
Psychology 4 4%
Business, Management and Accounting 3 3%
Other 16 16%
Unknown 31 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 16 January 2017.
All research outputs
#12,712,540
of 22,940,083 outputs
Outputs from Implementation Science
#1,289
of 1,722 outputs
Outputs of similar age
#194,890
of 421,590 outputs
Outputs of similar age from Implementation Science
#28
of 37 outputs
Altmetric has tracked 22,940,083 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,722 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one is in the 23rd percentile – i.e., 23% 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 421,590 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 53% 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 is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.