| Title |
Medication safety research by observational study design
|
|---|---|
| Published in |
International Journal of Clinical Pharmacy, March 2016
|
| DOI | 10.1007/s11096-016-0285-6 |
| Pubmed ID | |
| Authors |
Kim S. J. Lao, Celine S. L. Chui, Kenneth K. C. Man, Wallis C. Y. Lau, Esther W. Chan, Ian C. K. Wong |
| Abstract |
Observational studies have been recognised to be essential for investigating the safety profile of medications. Numerous observational studies have been conducted on the platform of large population databases, which provide adequate sample size and follow-up length to detect infrequent and/or delayed clinical outcomes. Cohort and case-control are well-accepted traditional methodologies for hypothesis testing, while within-individual study designs are developing and evolving, addressing previous known methodological limitations to reduce confounding and bias. Respective examples of observational studies of different study designs using medical databases are shown. Methodology characteristics, study assumptions, strengths and weaknesses of each method are discussed in this review. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Curaçao | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 14 | 19% |
| Researcher | 10 | 14% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Other | 5 | 7% |
| Other | 12 | 17% |
| Unknown | 17 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 24 | 33% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Sports and Recreations | 4 | 6% |
| Nursing and Health Professions | 3 | 4% |
| Social Sciences | 3 | 4% |
| Other | 14 | 19% |
| Unknown | 19 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 14 July 2016.
All research outputs
#15,505,321
of 25,359,594 outputs
Outputs from International Journal of Clinical Pharmacy
#821
of 1,279 outputs
Outputs of similar age
#159,628
of 307,093 outputs
Outputs of similar age from International Journal of Clinical Pharmacy
#12
of 23 outputs
Altmetric has tracked 25,359,594 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,279 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one is in the 33rd percentile – i.e., 33% 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 307,093 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.