↓ Skip to main content

Administrative health data in Canada: lessons from history

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
64 Mendeley
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.
Title
Administrative health data in Canada: lessons from history
Published in
BMC Medical Informatics and Decision Making, August 2015
DOI 10.1186/s12911-015-0196-9
Pubmed ID
Authors

Kelsey Lucyk, Mingshan Lu, Tolulope Sajobi, Hude Quan

Abstract

Health decision-making requires evidence from high-quality data. As one example, the Discharge Abstract Database (DAD) compiles data from the majority of Canadian hospitals to form one of the most comprehensive and highly regarded administrative health databases available for health research, internationally. However, despite the success of this and other administrative health data resources, little is known about their history or the factors that have led to their success. The purpose of this paper is to provide an historical overview of Canadian administrative health data for health research to contribute to the institutional memory of this field. We conducted a qualitative content analysis of approximately 20 key sources to construct an historical narrative of administrative health data in Canada. Specifically, we searched for content related to key events, individuals, challenges, and successes in this field over time. In Canada, administrative health data for health research has developed in tangent with provincial research centres. Interestingly, the lessons learned from this history align with the original recommendations of the 1964 Royal Commission on Health Services: (1) standardization, and (2) centralization of data resources, that is (3) facilitated through governmental financial support. The overview history provided here illustrates the need for longstanding partnerships between government and academia, for classification, terminology and standardization are time-consuming and ever-evolving processes. This paper will be of interest to those who work with administrative health data, and also for countries that are looking to build or improve upon their use of administrative health data for decision-making.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 2%
Unknown 63 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 25%
Student > Master 9 14%
Other 6 9%
Student > Doctoral Student 5 8%
Student > Bachelor 5 8%
Other 12 19%
Unknown 11 17%
Readers by discipline Count As %
Medicine and Dentistry 20 31%
Nursing and Health Professions 7 11%
Mathematics 3 5%
Social Sciences 3 5%
Computer Science 3 5%
Other 11 17%
Unknown 17 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 August 2015.
All research outputs
#18,423,683
of 22,824,164 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,571
of 1,988 outputs
Outputs of similar age
#191,843
of 266,176 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#27
of 34 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,988 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% 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 266,176 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.