Towards Transformative Analytics for Palliative Care
2020
- 249Usage
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
- Usage249
- Abstract Views212
- Downloads36
- Plays1
Artifact Description
Models of care for life limiting illnesses are changing. Drivers of this change include an ageing population, increased cancer incidence, and increased palliative care needs in chronic illnesses. Currently, specialist palliative care in the community operates by delivering a “one size fits all” service which is no longer fit for purpose to meet the growing demand while maintaining a holistic approach that meets the needs of patients and their families. To tackle this challenge, we propose an analytics solution to better support new models of specialist palliative care in the community. This article outlines the first step in this research which investigates the state of the art in analytics technology in the home healthcare and palliative care domain. This research supports our understanding of the technology currently available in order to develop a novel solution to enable data-based decision making in a specialist healthcare service.
Bibliographic Details
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