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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Patient dumping, outlier payments, and optimal healthcare payment policy under asymmetric information
|
|---|---|
| Published in |
Health Economics Review, December 2016
|
| DOI | 10.1186/s13561-016-0135-1 |
| Pubmed ID | |
| Authors |
Tsuyoshi Takahara |
| Abstract |
We analyze a rationale for official authorization of patient dumping in the prospective payment policy framework. We show that when the insurer designs the healthcare payment policy to let hospitals dump high-cost patients, there is a trade-off between the disutility of dumped patients (changes in hospitals' rent extraction due to low-severity patients) and the shift in the level of cost reduction efforts for high-severity patients. We also clarify the welfare-improving conditions by allowing hospitals to dump high-severity patients. Finally, we show that if the efficiency of the cost reduction efforts varies extensively and the healthcare payment cost is substantial, or if there are many private hospitals, the patient dumping policy can improve social welfare in a wider environment. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 26% |
| Student > Doctoral Student | 2 | 11% |
| Student > Bachelor | 2 | 11% |
| Professor | 2 | 11% |
| Student > Postgraduate | 2 | 11% |
| Other | 2 | 11% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 7 | 37% |
| Medicine and Dentistry | 3 | 16% |
| Business, Management and Accounting | 2 | 11% |
| Social Sciences | 1 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 20 December 2016.
All research outputs
#17,837,681
of 22,914,829 outputs
Outputs from Health Economics Review
#302
of 430 outputs
Outputs of similar age
#293,383
of 420,738 outputs
Outputs of similar age from Health Economics Review
#13
of 15 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 430 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 22nd percentile – i.e., 22% 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 420,738 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.