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X Demographics
Mendeley readers
Attention Score in Context
| 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
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 25% |
| Italy | 1 | 5% |
| Philippines | 1 | 5% |
| Zimbabwe | 1 | 5% |
| New Zealand | 1 | 5% |
| Unknown | 11 | 55% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 70% |
| Practitioners (doctors, other healthcare professionals) | 4 | 20% |
| Scientists | 2 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 84 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 17% |
| Student > Ph. D. Student | 10 | 12% |
| Student > Bachelor | 6 | 7% |
| Student > Doctoral Student | 5 | 6% |
| Other | 5 | 6% |
| Other | 10 | 12% |
| Unknown | 34 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 15% |
| Nursing and Health Professions | 9 | 11% |
| Social Sciences | 7 | 8% |
| Agricultural and Biological Sciences | 4 | 5% |
| Computer Science | 4 | 5% |
| Other | 11 | 13% |
| Unknown | 36 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 02 May 2024.
All research outputs
#1,529,152
of 25,836,587 outputs
Outputs from BMC Public Health
#1,756
of 17,871 outputs
Outputs of similar age
#42,206
of 411,700 outputs
Outputs of similar age from BMC Public Health
#44
of 433 outputs
Altmetric has tracked 25,836,587 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,871 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has done particularly well, scoring higher than 90% 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 411,700 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 89% of its contemporaries.
We're also able to compare this research output to 433 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.