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Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2016
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

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6 X users

Citations

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32 Dimensions

Readers on

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178 Mendeley
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Title
Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study
Published in
BMC Medical Informatics and Decision Making, July 2016
DOI 10.1186/s12911-016-0328-x
Pubmed ID
Authors

Rebecca Grochow Mishuris, Jordan Yoder, Dan Wilson, Devin Mann

Abstract

Health information is increasingly being digitally stored and exchanged. The public is regularly collecting and storing health-related data on their own electronic devices and in the cloud. Diabetes prevention is an increasingly important preventive health measure, and diet and exercise are key components of this. Patients are turning to online programs to help them lose weight. Despite primary care physicians being important in patients' weight loss success, there is no exchange of information between the primary care provider (PCP) and these online weight loss programs. There is an emerging opportunity to integrate this data directly into the electronic health record (EHR), but little is known about what information to share or how to share it most effectively. This study aims to characterize the preferences of providers concerning the integration of externally generated lifestyle modification data into a primary care EHR workflow. We performed a qualitative study using two rounds of semi-structured interviews with primary care providers. We used an iterative design process involving primary care providers, health information technology software developers and health services researchers to develop the interface. Using grounded-theory thematic analysis 4 themes emerged from the interviews: 1) barriers to establishing healthy lifestyles, 2) features of a lifestyle modification program, 3) reporting of outcomes to the primary care provider, and 4) integration with primary care. These themes guided the rapid-cycle agile design process of an interface of data from an online diabetes prevention program into the primary care EHR workflow. The integration of external health-related data into the EHR must be embedded into the provider workflow in order to be useful to the provider and beneficial for the patient. Accomplishing this requires evaluation of that clinical workflow during software design. The development of this novel interface used rapid cycle iterative design, early involvement by providers, and usability testing methodology. This provides a framework for how to integrate external data into provider workflow in efficient and effective ways. There is now the potential to realize the importance of having this data available in the clinical setting for patient engagement and health outcomes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Ghana 1 <1%
Unknown 175 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 18%
Student > Master 31 17%
Student > Ph. D. Student 30 17%
Student > Doctoral Student 11 6%
Student > Bachelor 10 6%
Other 31 17%
Unknown 33 19%
Readers by discipline Count As %
Medicine and Dentistry 35 20%
Computer Science 20 11%
Nursing and Health Professions 19 11%
Social Sciences 16 9%
Business, Management and Accounting 11 6%
Other 34 19%
Unknown 43 24%
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 27 June 2017.
All research outputs
#6,257,126
of 22,880,691 outputs
Outputs from BMC Medical Informatics and Decision Making
#578
of 1,994 outputs
Outputs of similar age
#104,291
of 354,317 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#14
of 42 outputs
Altmetric has tracked 22,880,691 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 1,994 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 354,317 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 70% of its contemporaries.
We're also able to compare this research output to 42 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 66% of its contemporaries.