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Protocol for the “Implementation, adoption, and utility of family history in diverse care settings” study

Overview of attention for article published in Implementation Science, November 2015
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  • Average Attention Score compared to outputs of the same age and source

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Title
Protocol for the “Implementation, adoption, and utility of family history in diverse care settings” study
Published in
Implementation Science, November 2015
DOI 10.1186/s13012-015-0352-8
Pubmed ID
Authors

R. Ryanne Wu, Rachel A. Myers, Catherine A. McCarty, David Dimmock, Michael Farrell, Deanna Cross, Troy D. Chinevere, Geoffrey S. Ginsburg, Lori A. Orlando, for the Family Health History Network

Abstract

Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study's protocol. MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff. This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness. NCT01956773.

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The data shown below were collected from the profiles of 11 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 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 160 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 28 18%
Student > Ph. D. Student 19 12%
Researcher 17 11%
Student > Bachelor 14 9%
Student > Postgraduate 10 6%
Other 26 16%
Unknown 46 29%
Readers by discipline Count As %
Medicine and Dentistry 39 24%
Nursing and Health Professions 19 12%
Social Sciences 12 8%
Biochemistry, Genetics and Molecular Biology 7 4%
Computer Science 6 4%
Other 27 17%
Unknown 50 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 12 January 2016.
All research outputs
#6,155,043
of 22,834,308 outputs
Outputs from Implementation Science
#1,059
of 1,721 outputs
Outputs of similar age
#95,370
of 386,693 outputs
Outputs of similar age from Implementation Science
#40
of 59 outputs
Altmetric has tracked 22,834,308 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,721 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 37th percentile – i.e., 37% 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 386,693 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 74% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.