The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study

Tolley, Clare L.; Watson, Neil W.; Heed, Andrew; Einbeck, Jochen; Medows, Suzanne; Wood, Linda; Campbell, Layla; Slight, Sarah P.

Abstract

Objective: The medication administration process is complex and consequently prone to errors. Closed Loop Medication Administration solutions aim to improve patient safety. We assessed the impact of a novel medication scanning device (MedEye) on the rate of medication administration errors in a large UK Hospital. Methods: We performed a feasibility before and after study on one ward at a tertiary-care teaching hospital that used a commercial electronic prescribing and medication administration system. We conducted direct observations of nursing drug administration rounds before and after the MedEye implementation. We calculated the rate and type (‘timing’, ‘omission’ or ‘other’ error) of medication administration errors (MAEs) before and after the MedEye implementation. Results: We observed a total of 1069 administrations before and 432 after the MedEye intervention was implemented. Data suggested that MedEye could support a reduction in MAEs. After adjusting for heterogeneity, we detected a decreasing effect of MedEye on overall errors (p = 0.0753). Non-timing errors (‘omission’ and ‘other’ errors) reduced from 51 (4.77%) to 11 (2.55%), a reduction of 46.5%, which had borderline significance at the 5% level, although this was lost after adjusting for confounders. Conclusions: This pilot study detected a decreasing effect of MedEye on overall errors and a reduction in non-timing error rates that was clinically important as such errors are more likely to be associated with harm. Further research is needed to investigate the impact on a larger sample of medications.

Citation

Tolley, C. L., Watson, N. W., Heed, A., Einbeck, J., Medows, S., Wood, L., Campbell, L., & Slight, S. P. (2022). The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study. BMC Medical Informatics and Decision Making, 22(1), Article 86. https://doi.org/10.1186/s12911-022-01828-3

• Journal Article Type: Article
• Acceptance Date: Mar 16, 2022
• Online Publication Date: Mar 29, 2022
• Publication Date: 2022
• Deposit Date: Apr 26, 2022
• Publicly Available Date: Jun 21, 2022
• Journal: BMC Medical Informatics and Decision Making
• Publisher: BioMed Central
• Peer Reviewed: Peer Reviewed
• Volume: 22
• Issue: 1
• Article Number: 86
• DOI: https://doi.org/10.1186/s12911-022-01828-3
• Public URL: https://durham-repository.worktribe.com/output/1208593
• Related Public URLs: https://pubmed.ncbi.nlm.nih.gov/35351096/