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Barriers to the routine collection of health outcome data in an Australian community care organization

Overview of attention for article published in Journal of Multidisciplinary Healthcare, January 2013
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Article details
Title
Barriers to the routine collection of health outcome data in an Australian community care organization
Published in
Journal of Multidisciplinary Healthcare, January 2013
DOI 10.2147/jmdh.s37727
Pubmed ID
Authors
Abstract

For over a decade, organizations have attempted to include the measurement and reporting of health outcome data in contractual agreements between funders and health service providers, but few have succeeded. This research explores the utility of collecting health outcomes data that could be included in funding contracts for an Australian Community Care Organisation (CCO). An action-research methodology was used to trial the implementation of outcome measurement in six diverse projects within the CCO using a taxonomy of interventions based on the International Classification of Function. The findings from the six projects are presented as vignettes to illustrate the issues around the routine collection of health outcomes in each case. Data collection and analyses were structured around Donabedian's structure-process-outcome triad. Health outcomes are commonly defined as a change in health status that is attributable to an intervention. This definition assumes that a change in health status can be defined and measured objectively; the intervention can be defined; the change in health status is attributable to the intervention; and that the health outcomes data are accessible. This study found flaws with all of these assumptions that seriously undermine the ability of community-based organizations to introduce routine health outcome measurement. Challenges were identified across all stages of the Donabedian triad, including poor adherence to minimum dataset requirements; difficulties standardizing processes or defining interventions; low rates of use of outcome tools; lack of value of the tools to the service provider; difficulties defining or identifying the end point of an intervention; technical and ethical barriers to accessing data; a lack of standardized processes; and time lags for the collection of data. In no case was the use of outcome measures sustained by any of the teams, although some quality-assurance measures were introduced as a result of the project.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 1 2%
Unknown 44 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 9 20%
Researcher 4 9%
Student > Bachelor 3 7%
Other 2 4%
Professor 2 4%
Other 8 18%
Unknown 17 38%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 9 20%
Nursing and Health Professions 3 7%
Social Sciences 3 7%
Business, Management and Accounting 2 4%
Psychology 2 4%
Other 7 16%
Unknown 19 42%
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 23 January 2013.
All research outputs
#21,949,766
of 27,782,313 outputs
Outputs from Journal of Multidisciplinary Healthcare
#811
of 1,102 outputs
Outputs of similar age
#233,973
of 299,176 outputs
Outputs of similar age from Journal of Multidisciplinary Healthcare
#8
of 9 outputs
Altmetric has tracked 27,782,313 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,102 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 23rd percentile – i.e., 23% 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 299,176 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one.