Taxonomy Development in Health-IT
2013
- 579Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage579
- Abstract Views389
- Downloads190
Artifact Description
Health-IT is attracting increasing attention in the research community. To understand the relevant constructs and the relationships among them, many authors present taxonomies or typologies for classifying different things in health-IT. Even with much attention to health-IT, there is still limited theoretical knowledge in this field. This may be attributed to our observation that the process of developing taxonomies has not been adequately addressed in the health-IT literature. In this paper we address this challenge by (a) a comprehensive literature survey that shows a high diversity in the field and that the related discussion of the structural nature has largely been ad hoc, (b) presenting methods for developing health-IT taxonomies, and, (c) contributing to the theoretical foundations of the field by a taxonomy for health-IT applications.
Bibliographic Details
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know