↓ Skip to main content

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments

Overview of attention for article published in BMC Public Health, May 2020
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet
twitter
20 X users

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
85 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
Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments
Published in
BMC Public Health, May 2020
DOI 10.1186/s12889-020-08735-0
Pubmed ID
Authors

Jeremy A. Irvin, Andrew A. Kondrich, Michael Ko, Pranav Rajpurkar, Behzad Haghgoo, Bruce E. Landon, Robert L. Phillips, Stephen Petterson, Andrew Y. Ng, Sanjay Basu

X Demographics

X Demographics

The data shown below were collected from the profiles of 20 X users 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 85 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 15%
Student > Ph. D. Student 10 12%
Student > Bachelor 6 7%
Student > Doctoral Student 5 6%
Other 5 6%
Other 13 15%
Unknown 33 39%
Readers by discipline Count As %
Medicine and Dentistry 12 14%
Nursing and Health Professions 9 11%
Social Sciences 7 8%
Agricultural and Biological Sciences 4 5%
Computer Science 4 5%
Other 14 16%
Unknown 35 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 08 July 2022.
All research outputs
#1,659,507
of 25,363,685 outputs
Outputs from BMC Public Health
#1,905
of 17,484 outputs
Outputs of similar age
#45,785
of 408,801 outputs
Outputs of similar age from BMC Public Health
#49
of 431 outputs
Altmetric has tracked 25,363,685 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,484 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 well, scoring higher than 89% 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 408,801 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 88% of its contemporaries.
We're also able to compare this research output to 431 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.