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Adding Social Determinant Data Changes Children's Hospitals' Readmissions Performance

Overview of attention for article published in Journal of Pediatrics, May 2017
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
4 news outlets
twitter
9 tweeters
facebook
1 Facebook page

Citations

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7 Dimensions

Readers on

mendeley
45 Mendeley
Title
Adding Social Determinant Data Changes Children's Hospitals' Readmissions Performance
Published in
Journal of Pediatrics, May 2017
DOI 10.1016/j.jpeds.2017.03.056
Pubmed ID
Authors

Sills, Marion R., Hall, Matthew, Cutler, Gretchen J., Colvin, Jeffrey D., Gottlieb, Laura M., Macy, Michelle L., Bettenhausen, Jessica L., Morse, Rustin B., Fieldston, Evan S., Raphael, Jean L., Auger, Katherine A., Shah, Samir S., Marion R. Sills, Matthew Hall, Gretchen J. Cutler, Jeffrey D. Colvin, Laura M. Gottlieb, Michelle L. Macy, Jessica L. Bettenhausen, Rustin B. Morse, Evan S. Fieldston, Jean L. Raphael, Katherine A. Auger, Samir S. Shah

Abstract

To determine whether social determinants of health (SDH) risk adjustment changes hospital-level performance on the 30-day Pediatric All-Condition Readmission (PACR) measure and improves fit and accuracy of discharge-level models. We performed a retrospective cohort study of all hospital discharges meeting criteria for the PACR from 47 hospitals in the Pediatric Health Information database from January to December 2014. We built four nested regression models by sequentially adding risk adjustment factors as follows: chronic condition indicators (CCIs); PACR patient factors (age and sex); electronic health record-derived SDH (race, ethnicity, payer), and zip code-linked SDH (families below poverty level, vacant housing units, adults without a high school diploma, single-parent households, median household income, unemployment rate). For each model, we measured the change in hospitals' readmission decile-rank and assessed model fit and accuracy. For the 458 686 discharges meeting PACR inclusion criteria, in multivariable models, factors associated with higher discharge-level PACR measure included age <1 year, female sex, 1 of 17 CCIs, higher CCI count, Medicaid insurance, higher median household income, and higher percentage of single-parent households. Adjustment for SDH made small but significant improvements in fit and accuracy of discharge-level PACR models, with larger effect at the hospital level, changing decile-rank for 17 of 47 hospitals. We found that risk adjustment for SDH changed hospitals' readmissions rate rank order. Hospital-level changes in relative readmissions performance can have considerable financial implications; thus, for pay for performance measures calculated at the hospital level, and for research associated therewith, our findings support the inclusion of SDH variables in risk adjustment.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 17 38%
Other 7 16%
Unspecified 4 9%
Researcher 4 9%
Student > Bachelor 3 7%
Other 10 22%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 15 33%
Medicine and Dentistry 13 29%
Unspecified 4 9%
Social Sciences 3 7%
Nursing and Health Professions 3 7%
Other 7 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 14 February 2018.
All research outputs
#320,748
of 11,603,984 outputs
Outputs from Journal of Pediatrics
#228
of 7,450 outputs
Outputs of similar age
#15,614
of 265,079 outputs
Outputs of similar age from Journal of Pediatrics
#9
of 185 outputs
Altmetric has tracked 11,603,984 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,450 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one has done particularly well, scoring higher than 96% 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 265,079 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 94% of its contemporaries.
We're also able to compare this research output to 185 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.