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Design and implementation of electronic health record integrated clinical prediction rules (iCPR): a randomized trial in diverse primary care settings

Overview of attention for article published in Implementation Science, March 2017
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  • Above-average Attention Score compared to outputs of the same age (63rd percentile)

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Title
Design and implementation of electronic health record integrated clinical prediction rules (iCPR): a randomized trial in diverse primary care settings
Published in
Implementation Science, March 2017
DOI 10.1186/s13012-017-0567-y
Pubmed ID
Authors

David A. Feldstein, Rachel Hess, Thomas McGinn, Rebecca G. Mishuris, Lauren McCullagh, Paul D. Smith, Michael Flynn, Joseph Palmisano, Gheorghe Doros, Devin Mann

Abstract

Clinical prediction rules (CPRs) represent a method of determining individual patient risk to help providers make more accurate decisions at the point of care. Well-validated CPRs are underutilized but may decrease antibiotic overuse for acute respiratory infections. The integrated clinical prediction rules (iCPR) study builds on a previous single clinic study to integrate two CPRs into the electronic health record and assess their impact on practice. This article discusses study design and implementation of a multicenter cluster randomized control trial of the iCPR clinical decision support system, including the tool adaptation, usability testing, staff training, and implementation study to disseminate iCPR at multiple clinical sites across two health care systems. The iCPR tool is based on two well-validated CPRs, one for strep pharyngitis and one for pneumonia. The iCPR tool uses the reason for visit to trigger a risk calculator. Provider completion of the risk calculator provides a risk score, which is linked to an order set. Order sets guide evidence-based care and include progress note documentation, tests, prescription medications, and patient instructions. The iCPR tool was refined based on interviews with providers, medical assistants, and clinic managers, and two rounds of usability testing. "Near live" usability testing with simulated patients was used to ensure that iCPR fit into providers' clinical workflows. Thirty-three Family Medicine and General Internal Medicine primary care clinics were recruited at two institutions. Clinics were randomized to academic detailing about strep pharyngitis and pneumonia diagnosis and treatment (control) or academic detailing plus use of the iCPR tool (intervention). The primary outcome is the difference in antibiotic prescribing rates between the intervention and control groups with secondary outcomes of difference in rapid strep and chest x-ray ordering. Use of the components of the iCPR will also be assessed. The iCPR study uses a strong user-centered design and builds on the previous initial study, to assess whether CPRs integrated in the electronic health record can change provider behavior and improve evidence-based care in a broad range of primary care clinics. Clinicaltrials.gov ( NCT02534987 ).

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X Demographics

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 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
Canada 1 <1%
Unknown 192 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 38 20%
Researcher 25 13%
Student > Ph. D. Student 19 10%
Student > Bachelor 15 8%
Professor 9 5%
Other 37 19%
Unknown 51 26%
Readers by discipline Count As %
Medicine and Dentistry 67 35%
Nursing and Health Professions 14 7%
Psychology 7 4%
Engineering 5 3%
Computer Science 5 3%
Other 29 15%
Unknown 67 35%
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 05 June 2017.
All research outputs
#6,910,207
of 22,959,818 outputs
Outputs from Implementation Science
#1,159
of 1,722 outputs
Outputs of similar age
#110,973
of 307,966 outputs
Outputs of similar age from Implementation Science
#37
of 47 outputs
Altmetric has tracked 22,959,818 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th 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 14.8. This one is in the 32nd percentile – i.e., 32% 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 307,966 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 63% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.