| Title |
Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure
|
|---|---|
| Published in |
Health Services and Outcomes Research Methodology, October 2012
|
| DOI | 10.1007/s10742-012-0102-1 |
| Pubmed ID | |
| Authors |
Frank J. DeFalco, Patrick B. Ryan, M. Soledad Cepeda |
| Abstract |
Observational healthcare databases represent a valuable resource for health economics, outcomes research, quality of care, drug safety, epidemiology and comparative effectiveness research. The methods used to identify a population for study in an observational healthcare database with the desired drug exposures of interest are complex and not consistent nor apparent in the published literature. Our research evaluates three drug classification systems and their impact on prevalence in the analysis of observational healthcare databases using opioids as a case in point. The standard terminologies compiled in the Observational Medical Outcomes Partnership's Common Data Model vocabulary were used to facilitate the identification of populations with opioid exposures. This study analyzed three distinct observational healthcare databases and identified patients with at least one exposure to an opioid as defined by drug codes derived through the application of three classification systems. Opioid code sets were created for each of the three classification systems and the number of identified codes was summarized. We estimated the prevalence of opioid exposure in three observational healthcare databases using the three defined code sets. In addition we compared the number of drug codes and distinct ingredients that were identified using these classification systems. We found substantial variation in the prevalence of opioid exposure identified using an individual classification system versus a composite method using multiple classification systems. To ensure transparent and reproducible research publications should include a description of the process used to develop code sets and the complete code set used in studies. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 3% |
| Unknown | 28 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 21% |
| Student > Master | 6 | 21% |
| Student > Doctoral Student | 4 | 14% |
| Student > Ph. D. Student | 3 | 10% |
| Other | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 5 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 21% |
| Computer Science | 4 | 14% |
| Nursing and Health Professions | 3 | 10% |
| Agricultural and Biological Sciences | 2 | 7% |
| Business, Management and Accounting | 1 | 3% |
| Other | 5 | 17% |
| Unknown | 8 | 28% |
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
#16,172,769
of 23,857,313 outputs
Outputs from Health Services and Outcomes Research Methodology
#76
of 118 outputs
Outputs of similar age
#118,368
of 185,384 outputs
Outputs of similar age from Health Services and Outcomes Research Methodology
#1
of 1 outputs
Altmetric has tracked 23,857,313 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 118 research outputs from this source. They receive a mean Attention Score of 4.9. 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 185,384 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them