| Title |
Do different clinical evidence bases lead to discordant health-technology assessment decisions? An in-depth case series across three jurisdictions
|
|---|---|
| Published in |
ClinicoEconomics and Outcomes Research: CEOR, January 2013
|
| DOI | 10.2147/ceor.s39624 |
| Pubmed ID | |
| Authors |
Daryl S Spinner, Julie Birt, Jeffrey W Walter, Lee Bowman, Josephine Mauskopf, Michael F Drummond, Catherine Copley-Merriman |
| Abstract |
Health-technology assessment (HTA) plays an important role in informing drug-reimbursement decision-making in many countries. HTA processes for the Pharmaceutical Benefits Advisory Committee (PBAC) in Australia, the Common Drug Review (CDR) in Canada, and the National Institute for Health and Clinical Excellence (NICE) in England and Wales are among the most established in the world. In this study, we performed nine in-depth case studies to assess whether different clinical evidence bases may have influenced listing recommendations made by PBAC, CDR, and NICE. |
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 % |
|---|---|---|
| Canada | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 69 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 23% |
| Student > Ph. D. Student | 10 | 14% |
| Researcher | 9 | 13% |
| Student > Bachelor | 7 | 10% |
| Student > Postgraduate | 5 | 7% |
| Other | 13 | 18% |
| Unknown | 11 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 25 | 35% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 11% |
| Social Sciences | 6 | 8% |
| Economics, Econometrics and Finance | 6 | 8% |
| Psychology | 2 | 3% |
| Other | 8 | 11% |
| Unknown | 16 | 23% |
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 13 February 2013.
All research outputs
#20,726,842
of 25,461,852 outputs
Outputs from ClinicoEconomics and Outcomes Research: CEOR
#445
of 525 outputs
Outputs of similar age
#229,246
of 289,411 outputs
Outputs of similar age from ClinicoEconomics and Outcomes Research: CEOR
#8
of 10 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 525 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.0. This one is in the 7th percentile – i.e., 7% 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 289,411 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.