Investigating the incidence, nature, severity and potential causality of medication errors in hospital settings in Qatar.

Causes Error reporting Incidence Medication errors Qatar Reason’s accident causation model Severity

Journal

International journal of clinical pharmacy
ISSN: 2210-7711
Titre abrégé: Int J Clin Pharm
Pays: Netherlands
ID NLM: 101554912

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 22 03 2020
accepted: 22 07 2020
pubmed: 9 8 2020
medline: 12 10 2021
entrez: 9 8 2020
Statut: ppublish

Résumé

Background Medication errors are a major public health concern that negatively impact patient safety and health outcomes. Effective and efficient medication error reporting systems and practices are imperative in reducing error incidence and severity. Objective The objectives were to quantify the incidence, nature and severity of medication errors, and to explore potential causality using a theoretical framework. Setting The study was conducted at Hamad Medical Corporation, the largest public funded academic healthcare center in the state of Qatar. Methods A retrospective review of medication error reports submitted to the Hamad Medical Corporation incident reporting system during 2015 to 2017. Data related to number of reports, reporter, medication, severity and outcomes were extracted. Reason's Accident Causation Model was used as a theoretical framework for identifying potential causality. Two researchers independently categorized errors as: active failures (e.g. forgetting to administer medication at scheduled time); error provoking conditions (e.g. medication prescribed by an unauthorized physician and administered to the patient); and latent failures (e.g. organizational factors, lack of resources). Main outcome measures Incidence, classes of medications, reporter, error severity and outcomes, potential causality. Results A total of 5103 reports provided sufficient information to be included in the study giving an estimated error incidence of 0.044% of prescribed medication items. Most of the reports (91.5%, n = 4667) were submitted by pharmacists and majority (87.9%, n = 4485) were prescribing errors. The most commonly reported medications were anti-infectives for systemic use (22.0%, n = 1123) followed by medications to treat nervous system disorders (17.2%, n = 876). Only three errors reported to have caused temporary harm requiring intervention while one contributed to or resulted in temporary harm requiring initial or prolonged hospitalization. In terms of potential causality of medication errors, the majority (91.5%, n = 4671) were classified as active failures. Conclusion Almost all reports were submitted by pharmacists, indicating likely under-reporting affecting the actual incidence. Effort is required to increase the effectiveness and efficiency of the reporting system. The use of the theoretical framework allowed identification of potential causality, largely in relation to active failures, which can inform the basis of interventions to improve medication safety.

Identifiants

pubmed: 32767219
doi: 10.1007/s11096-020-01108-y
pii: 10.1007/s11096-020-01108-y
pmc: PMC7878234
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

77-84

Subventions

Organisme : Hamad Medical Corporation
ID : MRC-01-18-109

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Auteurs

Binny Thomas (B)

Women's Wellness and Research Center, Hamad Medical Corporation, Doha, Qatar.

Abdulrouf Pallivalapila (A)

Women's Wellness and Research Center, Hamad Medical Corporation, Doha, Qatar.

Wessam El Kassem (W)

Women's Wellness and Research Center, Hamad Medical Corporation, Doha, Qatar.

Moza Al Hail (M)

Corporate Pharmacy Executive Office, Hamad Medical Corporation, Doha, Qatar.

Vibhu Paudyal (V)

School of Pharmacy, University of Birmingham, Birmingham, UK.

James McLay (J)

Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK.

Katie MacLure (K)

School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen, UK.

Derek Stewart (D)

College of Pharmacy, QU Health, Qatar University, Doha, Qatar. d.stewart@qu.edu.qa.

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Classifications MeSH