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The contribution of staffing to medication administration errors: A text mining analysis of incident report data.

Härkänen M, Vehviläinen-Julkunen K, Murrells T, Paananen J, Franklin BD, Rafferty AM. The contribution of staffing to medication administration errors: a text mining analysis of incident report data. J Nurs Scholarsh. 2020;52(1):113–123. doi:10.1111/jnu.12531

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December 18, 2019
Härkänen M, Vehviläinen‐Julkunen K, Murrells T, et al. Journal of Nursing Scholarship. 2019;52(1).

This retrospective study used descriptive statistics, manual analysis, and text mining of medication-related incident reports and staffing (N = 72,390) in England and Wales. The text mining was conducted with SAS Text Minor tool.  Effective trigger terms included “short staffing”, “workload”, and “extremely busy”.  The authors concluded that inadequate staffing, workload, and working in haste may increase the risk for errors.  The key importance of this article is the use of an automated system to analyze incident reports.

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Härkänen M, Vehviläinen-Julkunen K, Murrells T, Paananen J, Franklin BD, Rafferty AM. The contribution of staffing to medication administration errors: a text mining analysis of incident report data. J Nurs Scholarsh. 2020;52(1):113–123. doi:10.1111/jnu.12531