Error types with use of medication-related technology

A mixed methods research study

Research output: Contribution to journalArticle

Abstract

Background: Health information technology has been integrated throughout the medication use process to enhance safety, quality, and care efficiency. However, technologies have the potential to eliminate or reduce, but also create some new types of errors. Objective: Assess specific error types before and after the incorporation of two different health information technologies (HITs), e-prescribing and automated dispensing cabinets (ADCs), into pharmacists’ daily work. Methods: A mixed methods design guided use of a pre-existing database of pharmacist survey responses describing patient safety HIT-related issues in the form of errors prevented and errors observed. In vivo descriptive text responses were converted into error types. Descriptive analysis was performed to characterize the error types associated with each HIT. Results: Four error types were eliminated with the use of e-prescribing, three new error types emerged, and three error types persisted. With ADC use, four error types were eliminated, three new error types emerged, and three error types persisted. Conclusion: Each technology has its own error types, and some persist regardless of HIT use. There is a need to determine optimal risk reduction approaches for each unique HIT introduced, and design safety practice improvement for error types unaffected by the introduction of HIT use.

Original languageEnglish (US)
JournalResearch in Social and Administrative Pharmacy
DOIs
StateAccepted/In press - Jan 1 2019
Externally publishedYes

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Medical Informatics
Technology
Research
Information technology
Health
Pharmacists
Safety
Quality of Health Care
Risk Reduction Behavior
Patient Safety
Databases

All Science Journal Classification (ASJC) codes

  • Pharmacy
  • Pharmaceutical Science

Cite this

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title = "Error types with use of medication-related technology: A mixed methods research study",
abstract = "Background: Health information technology has been integrated throughout the medication use process to enhance safety, quality, and care efficiency. However, technologies have the potential to eliminate or reduce, but also create some new types of errors. Objective: Assess specific error types before and after the incorporation of two different health information technologies (HITs), e-prescribing and automated dispensing cabinets (ADCs), into pharmacists’ daily work. Methods: A mixed methods design guided use of a pre-existing database of pharmacist survey responses describing patient safety HIT-related issues in the form of errors prevented and errors observed. In vivo descriptive text responses were converted into error types. Descriptive analysis was performed to characterize the error types associated with each HIT. Results: Four error types were eliminated with the use of e-prescribing, three new error types emerged, and three error types persisted. With ADC use, four error types were eliminated, three new error types emerged, and three error types persisted. Conclusion: Each technology has its own error types, and some persist regardless of HIT use. There is a need to determine optimal risk reduction approaches for each unique HIT introduced, and design safety practice improvement for error types unaffected by the introduction of HIT use.",
author = "Shah, {Shweta R.} and Galt, {Kimberly A.} and Fuji, {Kevin T.}",
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AB - Background: Health information technology has been integrated throughout the medication use process to enhance safety, quality, and care efficiency. However, technologies have the potential to eliminate or reduce, but also create some new types of errors. Objective: Assess specific error types before and after the incorporation of two different health information technologies (HITs), e-prescribing and automated dispensing cabinets (ADCs), into pharmacists’ daily work. Methods: A mixed methods design guided use of a pre-existing database of pharmacist survey responses describing patient safety HIT-related issues in the form of errors prevented and errors observed. In vivo descriptive text responses were converted into error types. Descriptive analysis was performed to characterize the error types associated with each HIT. Results: Four error types were eliminated with the use of e-prescribing, three new error types emerged, and three error types persisted. With ADC use, four error types were eliminated, three new error types emerged, and three error types persisted. Conclusion: Each technology has its own error types, and some persist regardless of HIT use. There is a need to determine optimal risk reduction approaches for each unique HIT introduced, and design safety practice improvement for error types unaffected by the introduction of HIT use.

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