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Relationship between health-related quality of life, comorbidities and acute health care utilisation, in adults with chronic conditions

Overview of attention for article published in Health and Quality of Life Outcomes, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

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2 policy sources
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1 X user
facebook
1 Facebook page

Citations

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48 Dimensions

Readers on

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179 Mendeley
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Title
Relationship between health-related quality of life, comorbidities and acute health care utilisation, in adults with chronic conditions
Published in
Health and Quality of Life Outcomes, May 2015
DOI 10.1186/s12955-015-0260-2
Pubmed ID
Authors

Anastasia F. Hutchinson, Marnie Graco, Tshepo Mokuedi Rasekaba, Sumit Parikh, David John Berlowitz, Wen Kwang Lim

Abstract

There is increased interest in developing multidisciplinary ambulatory care models of service delivery to manage patients with complex chronic diseases. These programs are expensive and given limited resources it is important that care is targeted effectively. One potential screening strategy is to identify individuals who report the greatest decrement in health related quality of life (HRQoL) and thus greater need. The aim of this study was to explore the relationship between HRQoL, comorbid conditions and acute health care utilisation. A prospective, longitudinal cohort design was used to evaluate the impact of HRQoL on acute care utilisation rates over three-years of follow-up. Participants were enrolled in chronic disease management programs run by a metropolitan health service in Australia. Baseline data was collected from 2007-2009 and follow-up data until 2012. Administrative data was used to classify patients' primary reasons for enrolment, number of comorbidities (Charlson Score) and presentations to acute care. At enrolment, HRQoL was measured using the Assessment of Quality of Life (AQoL) instrument, for analysis AQoL scores were dichotomised at two standard deviations below the population norm. There were 1999 participants (54 % male) with a mean age of 63 years (range 18-101), enrolled in the study. Participants' primary health conditions at enrolment were: diabetes 915 (46 %), chronic respiratory disease 463 (23 %), cardiac disease 260 (13 %), peripheral vascular disease, and 181 (9 %) and aged care 180 (9 %). At 1-year multivariate logistic regression models demonstrated that AQOL utility score was not predictive of acute care presentations after adjusting for comorbidities. Over 3-years an AQoL utility score in the lowest quartile was predictive of both ED presentation (OR 1.58, 95 % CI, 1.16-2.13, p = 0.003) and admissions (OR 1.67, 95 % CI.1.21 to 2.30, p = 0.002) after adjusting for differences in age and comorbidities. This study found that both HRQoL and comorbidities were predictive of subsequent acute care attendance over 3-years of follow-up. At 1-year, comorbidities was a better predictor of acute care representation than HRQoL. To maximise benefits, programs should initially focus on medical disease management, but subsequently switch to strategies that enhance health independence and raise HRQoL.

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 179 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Spain 1 <1%
Canada 1 <1%
Unknown 176 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 15%
Student > Master 22 12%
Student > Bachelor 21 12%
Student > Doctoral Student 12 7%
Other 12 7%
Other 30 17%
Unknown 56 31%
Readers by discipline Count As %
Medicine and Dentistry 46 26%
Nursing and Health Professions 24 13%
Social Sciences 11 6%
Psychology 10 6%
Biochemistry, Genetics and Molecular Biology 5 3%
Other 18 10%
Unknown 65 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 13 January 2019.
All research outputs
#4,517,083
of 22,807,037 outputs
Outputs from Health and Quality of Life Outcomes
#572
of 2,159 outputs
Outputs of similar age
#57,613
of 265,918 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#7
of 46 outputs
Altmetric has tracked 22,807,037 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,159 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 73% 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 265,918 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 78% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.