Loughborough University
Browse

Adopting system models for multiple incident analysis: Utility and usability

Download (1.32 MB)
journal contribution
posted on 2021-09-16, 14:41 authored by Jayne L Wheway, Gyuchan Thomas JunGyuchan Thomas Jun
ABSTRACT Background This study aims to present two system models widely used in Human Factors and Ergonomics (HF/E) and evaluate whether the models are adoptable to England’s national patient safety team in improving the exploration and understanding of multiple incident reports of an active patient safety issue and the development of the remedial actions for a potential National Patient Safety Alert. The existing process of examining multiple incidents is based on inductive thematic analysis and forming the remedial actions is based on barrier analysis of intelligence on potential solutions. However, no formal systems models evaluated in this study have been used.
Methods AcciMap and Systems Engineering Initiative for Patient Safety (SEIPS) were selected, applied and evaluated to the analysis of two different sets of patient safety incidents: i) incidents concerning ingestion of superabsorbent polymer granules; ii) incidents concerning the interruption in use of High Nasal Flow Oxygen. The first set was analysed by the first author and the utility and usability were reflected. The second set was analysed collectively by a purposeful sample of patient safety team members, who create the National Patient Safety Alerts from incident level data and information. All of them attended a 30min video-based training and a 1.5hr case-based online workshop. Post-workshop individual interviews were conducted to evaluate their perceived utility and usability of each model.
Results The patient safety team showed overwhelming support for the utility of the system models as a “framework” that provides a systematic, structured way of looking at an issue and examining the causes, whilst also sharing concerns regarding their usability. Accimap was viewed useful particularly in providing a visual comprehensive overview of the issue but considered chaotic by some participants due to many arrows between factors. SEIPS was perceived easier to understand due to the familiarity of the structure (Donbedian’s model), but the non-hierarchical format of SEIPS was considered less useful.
Conclusions The participants of the study agreed with the high level of utility of both models for their unique strengths, but shared some concern for the usability of them in terms of complexity and further training/coaching time would be required to adopt these models in their daily practices. It is recommended that the gap between HF/E practitioners and patient safety practitioners can be narrowed by strengthening education, coaching and mentoring relationships between the two groups, led by the increasing number of healthcare practitioners who embrace their membership to HF/E practice.

History

School

  • Design and Creative Arts

Department

  • Design

Published in

International Journal for Quality in Health Care

Volume

33

Issue

4

Pages

1-8

Publisher

Oxford University Press (OUP)

Version

  • AM (Accepted Manuscript)

Rights holder

© The Author(s) 2021. Published by Oxford University Press on behalf of International Society for Quality in Health Care.

Publisher statement

This is a pre-copyedited, author-produced version of an article accepted for publication in International Journal for Quality in Health Care following peer review. The version of record Wheway, J.L. and Jun, G.T., 2021. Adopting system models for multiple incident analysis: Utility and usability. International Journal for Quality in Health Care, In Press is available online at: https://doi.org/10.1093/intqhc/mzab135

Acceptance date

2021-09-09

Publication date

2021-09-11

Copyright date

2021

ISSN

1353-4505

eISSN

1464-3677

Language

  • en

Depositor

Dr Thomas Jun . Deposit date: 12 September 2021

Usage metrics

    Loughborough Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC