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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol
|
|---|---|
| Published in |
Systematic Reviews, February 2017
|
| DOI | 10.1186/s13643-017-0431-9 |
| Pubmed ID | |
| Authors |
Sepideh Souri, Nicola E. Symonds, Azin Rouhi, Brendan C. Lethebe, Stephanie Garies, Paul E. Ronksley, Tyler S. Williamson, Gabriel E. Fabreau, Richard Birtwhistle, Hude Quan, Kerry A. McBrien |
| Abstract |
Primary care electronic medical record (EMR) data are being used for research, surveillance, and clinical monitoring. To broaden the reach and usability of EMR data, case definitions must be specified to identify and characterize important chronic conditions. The purpose of this study is to identify all case definitions for a set of chronic conditions that have been tested and validated in primary care EMR and EMR-linked data. This work will provide a reference list of case definitions, together with their performance metrics, and will identify gaps where new case definitions are needed. We will consider a set of 40 chronic conditions, previously identified as potentially important for surveillance in a review of multimorbidity measures. We will perform a systematic search of the published literature to identify studies that describe case definitions for clinical conditions in EMR data and report the performance of these definitions. We will stratify our search by studies that use EMR data alone and those that use EMR-linked data. We will compare the performance of different definitions for the same conditions and explore the influence of data source, jurisdiction, and patient population. EMR data from primary care providers can be compiled and used for benefit by the healthcare system. Not only does this work have the potential to further develop disease surveillance and health knowledge, EMR surveillance systems can provide rapid feedback to participating physicians regarding their patients. Existing case definitions will serve as a starting point for the development and validation of new case definitions and will enable better surveillance, research, and practice feedback based on detailed clinical EMR data. PROSPERO CRD42016040020. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 63 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 16% |
| Student > Master | 7 | 11% |
| Student > Ph. D. Student | 7 | 11% |
| Student > Doctoral Student | 6 | 10% |
| Other | 4 | 6% |
| Other | 8 | 13% |
| Unknown | 21 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 25% |
| Nursing and Health Professions | 6 | 10% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Engineering | 2 | 3% |
| Economics, Econometrics and Finance | 2 | 3% |
| Other | 9 | 14% |
| Unknown | 26 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 02 March 2017.
All research outputs
#13,542,613
of 22,958,253 outputs
Outputs from Systematic Reviews
#1,431
of 2,005 outputs
Outputs of similar age
#162,314
of 311,192 outputs
Outputs of similar age from Systematic Reviews
#41
of 56 outputs
Altmetric has tracked 22,958,253 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,005 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.7. This one is in the 26th percentile – i.e., 26% 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 311,192 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.