Health information system implementation: A qualitative meta-analysis
Journal of Medical Systems, ISSN: 0148-5598, Vol: 33, Issue: 5, Page: 359-368
2009
- 62Citations
- 278Captures
Metric Options: Counts1 Year3 YearSelecting 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.
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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
- Citations62
- Citation Indexes61
- 61
- CrossRef29
- Policy Citations1
- Policy Citation1
- Captures278
- Readers278
- 278
Article Description
Healthcare information systems (HISs) are often implemented to enhance the quality of care and the degree to which it is patient-centered, as well as to improve the efficiency and safety of services. However, the outcomes of HIS implementations have not met expectations. We set out to organize the knowledge gained in qualitative studies performed in association with HIS implementations and to use this knowledge to outline an updated structure for implementation planning. A multi-disciplinary team performed the analyses in order to cover as many aspects of the primary studies as possible. We found that merely implementing an HIS will not automatically increase organizational efficiency. Strategic, tactical, and operational actions have to be taken into consideration, including management involvement, integration in healthcare workflow, establishing compatibility between software and hardware and, most importantly, user involvement, education and training. The results should be interpreted as a high-order scheme, and not a predictive theory. © 2008 Springer Science+Business Media, LLC.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=72349083080&origin=inward; http://dx.doi.org/10.1007/s10916-008-9198-9; http://www.ncbi.nlm.nih.gov/pubmed/19827262; http://link.springer.com/10.1007/s10916-008-9198-9; http://www.springerlink.com/index/10.1007/s10916-008-9198-9; http://www.springerlink.com/index/pdf/10.1007/s10916-008-9198-9; https://dx.doi.org/10.1007/s10916-008-9198-9; https://link.springer.com/article/10.1007/s10916-008-9198-9
Springer Science and Business Media LLC
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