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Feasibility of extracting data from electronic medical records for research: an international comparative study

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
23 tweeters
wikipedia
1 Wikipedia page

Citations

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31 Dimensions

Readers on

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180 Mendeley
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Title
Feasibility of extracting data from electronic medical records for research: an international comparative study
Published in
BMC Medical Informatics and Decision Making, July 2016
DOI 10.1186/s12911-016-0332-1
Pubmed ID
Authors

Michelle Helena van Velthoven, Nikolaos Mastellos, Azeem Majeed, John O’Donoghue, Josip Car

Abstract

Electronic medical records (EMR) offer a major potential for secondary use of data for research which can improve the safety, quality and efficiency of healthcare. They also enable the measurement of disease burden at the population level. However, the extent to which this is feasible in different countries is not well known. This study aimed to: 1) assess information governance procedures for extracting data from EMR in 16 countries; and 2) explore the extent of EMR adoption and the quality and consistency of EMR data in 7 countries, using management of diabetes type 2 patients as an exemplar. We included 16 countries from Australia, Asia, the Middle East, and Europe to the Americas. We undertook a multi-method approach including both an online literature review and structured interviews with 59 stakeholders, including 25 physicians, 23 academics, 7 EMR providers, and 4 information commissioners. Data were analysed and synthesised thematically considering the most relevant issues. We found that procedures for information governance, levels of adoption and data quality varied across the countries studied. The required time and ease of obtaining approval also varies widely. While some countries seem ready for secondary uses of data from EMR, in other countries several barriers were found, including limited experience with using EMR data for research, lack of standard policies and procedures, bureaucracy, confidentiality, data security concerns, technical issues and costs. This is the first international comparative study to shed light on the feasibility of extracting EMR data across a number of countries. The study will inform future discussions and development of policies that aim to accelerate the adoption of EMR systems in high and middle income countries and seize the rich potential for secondary use of data arising from the use of EMR solutions.

Twitter Demographics

The data shown below were collected from the profiles of 23 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Unknown 178 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 42 23%
Student > Master 32 18%
Student > Bachelor 17 9%
Student > Ph. D. Student 16 9%
Student > Postgraduate 11 6%
Other 31 17%
Unknown 31 17%
Readers by discipline Count As %
Medicine and Dentistry 49 27%
Computer Science 24 13%
Nursing and Health Professions 20 11%
Social Sciences 9 5%
Business, Management and Accounting 7 4%
Other 30 17%
Unknown 41 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 24 November 2018.
All research outputs
#1,222,221
of 16,187,330 outputs
Outputs from BMC Medical Informatics and Decision Making
#79
of 1,475 outputs
Outputs of similar age
#26,705
of 261,776 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 6 outputs
Altmetric has tracked 16,187,330 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 94% 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 261,776 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them