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A mixed methods evaluation of the maternal-newborn dashboard in Ontario: dashboard attributes, contextual factors, and facilitators and barriers to use: a study protocol

Overview of attention for article published in Implementation Science, May 2016
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  • Good Attention Score compared to outputs of the same age (65th percentile)

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Title
A mixed methods evaluation of the maternal-newborn dashboard in Ontario: dashboard attributes, contextual factors, and facilitators and barriers to use: a study protocol
Published in
Implementation Science, May 2016
DOI 10.1186/s13012-016-0427-1
Pubmed ID
Authors

Sandra Dunn, Ann E. Sprague, Jeremy M. Grimshaw, Ian D. Graham, Monica Taljaard, Deshayne Fell, Wendy E. Peterson, Elizabeth Darling, JoAnn Harrold, Graeme N. Smith, Jessica Reszel, Andrea Lanes, Carolyn Truskoski, Jodi Wilding, Deborah Weiss, Mark Walker

Abstract

There are wide variations in maternal-newborn care practices and outcomes across Ontario. To help institutions and care providers learn about their own performance, the Better Outcomes Registry & Network (BORN) Ontario has implemented an audit and feedback system, the Maternal-Newborn Dashboard (MND), for all hospitals providing maternal-newborn care. The dashboard provides (1) near real-time feedback, with site-specific and peer comparison data about six key performance indicators; (2) a visual display of evidence-practice gaps related to the indicators; and (3) benchmarks to provide direction for practice change. This study aims to evaluate the effects of the dashboard, dashboard attributes, contextual factors, and facilitation/support needs that influence the use of this audit and feedback system to improve performance. The objectives of this study are to (1) evaluate the effect of implementing the dashboard across Ontario; (2) explore factors that potentially explain differences in the use of the MND among hospitals; (3) measure factors potentially associated with differential effectiveness of the MND; and (4) identify factors that predict differences in hospital performance. A mixed methods design includes (1) an interrupted time series analysis to evaluate the effect of the intervention on six indicators, (2) key informant interviews with a purposeful sample of directors/managers from up to 20 maternal-newborn care hospitals to explore factors that influence the use of the dashboard, (3) a provincial survey of obstetrical directors/managers from all maternal-newborn hospitals in the province to measure factors that influence the use of the dashboard, and (4) a multivariable generalized linear mixed effects regression analysis of the indicators at each hospital to quantitatively evaluate the change in practice following implementation of the dashboard and to identify factors most predictive of use. Study results will provide essential data to develop knowledge translation strategies for facilitating practice change, which can be further evaluated through a future cluster randomized trial.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 1%
United Kingdom 1 <1%
Unknown 134 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 18%
Researcher 23 17%
Student > Ph. D. Student 14 10%
Student > Bachelor 11 8%
Other 6 4%
Other 21 15%
Unknown 38 28%
Readers by discipline Count As %
Medicine and Dentistry 38 28%
Nursing and Health Professions 12 9%
Computer Science 10 7%
Social Sciences 6 4%
Business, Management and Accounting 5 4%
Other 21 15%
Unknown 45 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 20 October 2017.
All research outputs
#7,146,076
of 22,867,327 outputs
Outputs from Implementation Science
#1,190
of 1,722 outputs
Outputs of similar age
#101,399
of 298,972 outputs
Outputs of similar age from Implementation Science
#32
of 38 outputs
Altmetric has tracked 22,867,327 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
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 30th percentile – i.e., 30% 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 298,972 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 38 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.