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The Impact of Disability and Social Determinants of Health on Condition-Specific Readmissions beyond Medicare Risk Adjustments: A Cohort Study

Overview of attention for article published in JGIM: Journal of General Internal Medicine, November 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
4 news outlets
twitter
10 tweeters

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
76 Mendeley
Title
The Impact of Disability and Social Determinants of Health on Condition-Specific Readmissions beyond Medicare Risk Adjustments: A Cohort Study
Published in
JGIM: Journal of General Internal Medicine, November 2016
DOI 10.1007/s11606-016-3869-x
Pubmed ID
Authors

Jennifer Meddings, Heidi Reichert, Shawna N. Smith, Theodore J. Iwashyna, Kenneth M. Langa, Timothy P. Hofer, Laurence F. McMahon

Abstract

Readmission rates after pneumonia, heart failure, and acute myocardial infarction hospitalizations are risk-adjusted for age, gender, and medical comorbidities and used to penalize hospitals. To assess the impact of disability and social determinants of health on condition-specific readmissions beyond current risk adjustment. Retrospective cohort study of Medicare patients using 1) linked Health and Retirement Study-Medicare claims data (HRS-CMS) and 2) Healthcare Cost and Utilization Project State Inpatient Databases (Florida, Washington) linked with ZIP Code-level measures from the Census American Community Survey (ACS-HCUP). Multilevel logistic regression models assessed the impact of disability and selected social determinants of health on readmission beyond current risk adjustment. Outcomes measured were readmissions ≤30 days after hospitalizations for pneumonia, heart failure, or acute myocardial infarction. HRS-CMS models included disability measures (activities of daily living [ADL] limitations, cognitive impairment, nursing home residence, home healthcare use) and social determinants of health (spouse, children, wealth, Medicaid, race). ACS-HCUP model measures were ZIP Code-percentage of residents ≥65 years of age with ADL difficulty, spouse, income, Medicaid, and patient-level and hospital-level race. For pneumonia, ≥3 ADL difficulties (OR 1.61, CI 1.079-2.391) and prior home healthcare needs (OR 1.68, CI 1.204-2.355) increased readmission in HRS-CMS models (N = 1631); ADL difficulties (OR 1.20, CI 1.063-1.352) and 'other' race (OR 1.14, CI 1.001-1.301) increased readmission in ACS-HCUP models (N = 27,297). For heart failure, children (OR 0.66, CI 0.437-0.984) and wealth (OR 0.53, CI 0.349-0.787) lowered readmission in HRS-CMS models (N = 2068), while black (OR 1.17, CI 1.056-1.292) and 'other' race (OR 1.14, CI 1.036-1.260) increased readmission in ACS-HCUP models (N = 37,612). For acute myocardial infarction, nursing home status (OR 4.04, CI 1.212-13.440) increased readmission in HRS-CMS models (N = 833); 'other' patient-level race (OR 1.18, CI 1.012-1.385) and hospital-level race (OR 1.06, CI 1.001-1.125) increased readmission in ACS-HCUP models (N = 17,496). Disability and social determinants of health influence readmission risk when added to the current Medicare risk adjustment models, but the effect varies by condition.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Unknown 74 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 22%
Unspecified 12 16%
Student > Master 11 14%
Student > Bachelor 10 13%
Researcher 9 12%
Other 17 22%
Readers by discipline Count As %
Unspecified 20 26%
Medicine and Dentistry 19 25%
Nursing and Health Professions 17 22%
Social Sciences 8 11%
Psychology 3 4%
Other 9 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 25 January 2018.
All research outputs
#400,802
of 12,416,981 outputs
Outputs from JGIM: Journal of General Internal Medicine
#353
of 4,357 outputs
Outputs of similar age
#15,215
of 231,103 outputs
Outputs of similar age from JGIM: Journal of General Internal Medicine
#8
of 67 outputs
Altmetric has tracked 12,416,981 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,357 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has done particularly well, scoring higher than 91% 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 231,103 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.