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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Will the Need‐Based Planning of Health Human Resources Currently Undertaken in Several Countries Lead to Excess Supply and Inefficiency? A Comment on Basu and Pak
|
|---|---|
| Published in |
Health economics (Online), June 2016
|
| DOI | 10.1002/hec.3370 |
| Pubmed ID | |
| Authors |
Stephen Birch, Gail Tomblin Murphy, Adrian MacKenzie, William Whittaker, Thomas Mason |
| Abstract |
Basu and Pak (2014) argue that need-based workforce planning models would not maximize social welfare, and use of need-based models would result in inefficiency. They propose that planning be based on service utilization to incorporate preferences or other socioeconomic factors. We show that the analysis is based on inappropriate considerations of the nature of healthcare demand, a misrepresentation of need-based approaches and misunderstanding publicly funded healthcare system objectives. We explain how current levels of utilization emerge from workload and income interests of providers that underlie utilization-based models and are incompatible with public goals of maximizing health gains. Copyright © 2016 John Wiley & Sons, Ltd. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 24% |
| Other | 5 | 15% |
| Researcher | 5 | 15% |
| Student > Ph. D. Student | 3 | 9% |
| Student > Doctoral Student | 1 | 3% |
| Other | 4 | 12% |
| Unknown | 7 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 24% |
| Business, Management and Accounting | 5 | 15% |
| Social Sciences | 3 | 9% |
| Nursing and Health Professions | 2 | 6% |
| Economics, Econometrics and Finance | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 10 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 16 June 2016.
All research outputs
#8,277,187
of 25,411,814 outputs
Outputs from Health economics (Online)
#1,568
of 2,667 outputs
Outputs of similar age
#128,381
of 368,476 outputs
Outputs of similar age from Health economics (Online)
#21
of 31 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 2,667 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 368,476 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.