Literature DB >> 34341981

An Analysis of the Safety of Medication Ordering Using Typo Correction within an Academic Medical System.

Alaina Brooks Darby1, Brittany Lee Karas2, Tina Wagner3.   

Abstract

OBJECTIVES: Spelling during medication ordering is prone to error, which can contribute to frustration, confusion, and, ultimately, errors. Typo correction can be utilized in an effort to mitigate the effects of misspellings by providing results even when no exact matches can be found. Although, typo correction can be beneficial in some scenarios, safety concerns have been raised when utilizing the functionality for medication ordering. Our primary objective was to analyze the effects of typo correction technology on medication errors within an academic medical system after implementation of the technology. Our secondary objective was to identify and provide additional recommendations to further improve the safety of the functionality.
METHODS: We analyzed 8 months of post-implementation data obtained from staff-reported medication errors and search query information obtained from the electronic health record. The reports were analyzed by two pharmacists in two phases: retrospective identification of errors occurring as a result of typo correction and prospective identification of potential errors with continued use of the functionality.
RESULTS: In retrospective review of 2,603 reported medication-related errors, 26 were identified as potentially involving typo correction as a contributing factor. Six of these orders invoked typo correction, but none of the errors could be attributed to typo correction. In prospective review, a list of 40 error-prone words and terms were identified to be added as stop words and 407 medication synonyms were identified for removal from their associated medication records.
CONCLUSION: Our results indicate, when properly implemented, typo correction does not cause additional medication errors. However, there may be benefit in implementing further precautions for preventing future errors. Thieme. All rights reserved.

Entities:  

Mesh:

Year:  2021        PMID: 34341981      PMCID: PMC8328746          DOI: 10.1055/s-0041-1731745

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.762


  14 in total

1.  Matching controlled vocabulary words.

Authors:  Natalia Grabar; Pierre Zweigenbaum; Lina Soualmia; Stéfan Darmoni
Journal:  Stud Health Technol Inform       Date:  2003

2.  U.S. adoption of computerized physician order entry systems.

Authors:  David M Cutler; Naomi E Feldman; Jill R Horwitz
Journal:  Health Aff (Millwood)       Date:  2005 Nov-Dec       Impact factor: 6.301

3.  Reasons for computerised provider order entry (CPOE)-based inpatient medication ordering errors: an observational study of voided orders.

Authors:  Joanna Abraham; Thomas G Kannampallil; Alan Jarman; Shivy Sharma; Christine Rash; Gordon Schiff; William Galanter
Journal:  BMJ Qual Saf       Date:  2017-07-11       Impact factor: 7.035

4.  Risk factors associated with medication ordering errors.

Authors:  Joanna Abraham; William L Galanter; Daniel Touchette; Yinglin Xia; Katherine J Holzer; Vania Leung; Thomas Kannampallil
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

5.  Improving the Effectiveness of Health Information Technology: The Case for Situational Analytics.

Authors:  Laurie Lovett Novak; Shilo Anders; Kim M Unertl; Daniel J France; Matthew B Weinger
Journal:  Appl Clin Inform       Date:  2019-10-09       Impact factor: 2.342

6.  Role of computerized physician order entry systems in facilitating medication errors.

Authors:  Ross Koppel; Joshua P Metlay; Abigail Cohen; Brian Abaluck; A Russell Localio; Stephen E Kimmel; Brian L Strom
Journal:  JAMA       Date:  2005-03-09       Impact factor: 56.272

7.  An unsupervised and customizable misspelling generator for mining noisy health-related text sources.

Authors:  Abeed Sarker; Graciela Gonzalez-Hernandez
Journal:  J Biomed Inform       Date:  2018-11-13       Impact factor: 6.317

Review 8.  The problem of look-alike, sound-alike name errors: Drivers and solutions.

Authors:  Rachel Bryan; Jeffrey K Aronson; Alison Williams; Sue Jordan
Journal:  Br J Clin Pharmacol       Date:  2020-04-20       Impact factor: 4.335

Review 9.  Nominal ISOMERs (Incorrect Spellings Of Medicines Eluding Researchers)-variants in the spellings of drug names in PubMed: a database review.

Authors:  Robin E Ferner; Jeffrey K Aronson
Journal:  BMJ       Date:  2016-12-14

10.  Matching health information seekers' queries to medical terms.

Authors:  Lina F Soualmia; Elise Prieur-Gaston; Zied Moalla; Thierry Lecroq; Stéfan J Darmoni
Journal:  BMC Bioinformatics       Date:  2012-09-07       Impact factor: 3.169

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