You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 9 | 41% |
| Ireland | 2 | 9% |
| United States | 1 | 5% |
| United Arab Emirates | 1 | 5% |
| France | 1 | 5% |
| Unknown | 8 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 50% |
| Scientists | 6 | 27% |
| Practitioners (doctors, other healthcare professionals) | 5 | 23% |
Mendeley readers
The data shown below were compiled from readership statistics for 222 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | <1% |
| Unknown | 220 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 47 | 21% |
| Student > Master | 36 | 16% |
| Student > Ph. D. Student | 20 | 9% |
| Student > Bachelor | 16 | 7% |
| Other | 13 | 6% |
| Other | 38 | 17% |
| Unknown | 52 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 52 | 23% |
| Computer Science | 26 | 12% |
| Nursing and Health Professions | 25 | 11% |
| Social Sciences | 10 | 5% |
| Business, Management and Accounting | 9 | 4% |
| Other | 37 | 17% |
| Unknown | 63 | 28% |
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
#1,864,448
of 22,880,691 outputs
Outputs from BMC Medical Informatics and Decision Making
#99
of 1,994 outputs
Outputs of similar age
#36,226
of 354,681 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 42 outputs
Altmetric has tracked 22,880,691 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,994 research outputs from this source. They receive a mean Attention Score of 4.9. 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 354,681 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 42 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.