UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Identifying risks areas related to medication administrations - text mining analysis using free-text descriptions of incident reports

Härkänen, M; Paananen, J; Murrells, T; Rafferty, AM; Franklin, BD; (2019) Identifying risks areas related to medication administrations - text mining analysis using free-text descriptions of incident reports. BMC Health Services Research , 19 , Article 791. 10.1186/s12913-019-4597-9. Green open access

[thumbnail of s12913-019-4597-9.pdf]
Preview
Text
s12913-019-4597-9.pdf - Published Version

Download (768kB) | Preview

Abstract

Background: Some medications carry increased risk of patient harm when they are given in error. In incident reports, names of the medications that are involved in errors could be found written both in a specific medication field and/or within the free text description of the incident. Analysing only the names of the medications implicated in a specific unstructured medication field does not give information of the associated factors and risk areas, but when analysing unstructured free text descriptions, the information about the medication involved and associated risk factors may be buried within other non-relevant text. Thus, the aim of this study was to extract medication names most commonly used in free text descriptions of medication administration incident reports to identify terms most frequently associated with risk for each of these medications using text mining. / Method: Free text descriptions of medication administration incidents (n = 72,390) reported in 2016 to the National Reporting and Learning System for England and Wales were analysed using SAS® Text miner. Analysis included text parsing and filtering free text to identify most commonly mentioned medications, followed by concept linking, and clustering to identify terms associated with commonly mentioned medications and the associated risk areas. / Results: The following risk areas related to medications were identified: 1. Allergic reactions to antibacterial drugs, 2. Intravenous administration of antibacterial drugs, 3. Fentanyl patches, 4. Checking and documenting of analgesic doses, 5. Checking doses of anticoagulants, 6. Insulin doses and blood glucose, 7. Administration of intravenous infusions. / Conclusions: Interventions to increase medication administration safety should focus on checking patient allergies and medication doses, especially for intravenous and transdermal medications. High-risk medications include insulin, analgesics, antibacterial drugs, anticoagulants, and potassium chloride. Text mining may be useful for analysing large free text datasets and should be developed further.

Type: Article
Title: Identifying risks areas related to medication administrations - text mining analysis using free-text descriptions of incident reports
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/s12913-019-4597-9
Publisher version: https://doi.org/10.1186/s12913-019-4597-9
Language: English
Additional information: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Keywords: Clustering, Incident reports, Medication administration, Risk, Text mining
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Practice and Policy
URI: https://discovery.ucl.ac.uk/id/eprint/10085877
Downloads since deposit
39Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item