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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The quality of Indigenous identification in administrative health data in Australia: insights from studies using data linkage
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2012
|
| DOI | 10.1186/1472-6947-12-133 |
| Pubmed ID | |
| Authors |
Sandra C Thompson, John A Woods, Judith M Katzenellenbogen |
| Abstract |
Missing or incorrect Indigenous status in health records hinders monitoring of Indigenous health indicators. Linkage of administrative data has been used to improve the ascertainment of Indigenous status. Data linkage was pioneered in Western Australia (WA) and is now being used in other Australian states. This systematic review appraises peer-reviewed Australian studies that used data linkage to elucidate the impact of under-ascertainment of Indigenous status on health indicators. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 59 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 15% |
| Researcher | 9 | 15% |
| Student > Master | 7 | 11% |
| Student > Bachelor | 7 | 11% |
| Student > Postgraduate | 4 | 7% |
| Other | 9 | 15% |
| Unknown | 16 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 21% |
| Nursing and Health Professions | 8 | 13% |
| Social Sciences | 5 | 8% |
| Economics, Econometrics and Finance | 3 | 5% |
| Computer Science | 2 | 3% |
| Other | 11 | 18% |
| Unknown | 19 | 31% |
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 01 January 2016.
All research outputs
#7,547,727
of 24,289,456 outputs
Outputs from BMC Medical Informatics and Decision Making
#725
of 2,071 outputs
Outputs of similar age
#48,030
of 162,264 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#19
of 42 outputs
Altmetric has tracked 24,289,456 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,071 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 63% 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 162,264 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 68% 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 50% of its contemporaries.