Norm-Based Approach to Incorporate Human Factors into Clinical Pathway: Reducing Human Error and Improving Patient Safety

Tehrani, Jasmine, Michell, Vaughan and Pan, Yu-Chun ORCID: https://orcid.org/0000-0002-8637-8930 (2018) Norm-Based Approach to Incorporate Human Factors into Clinical Pathway: Reducing Human Error and Improving Patient Safety. In: The 18th International Conference on Informatics and Semiotics in Organisations (ICISO), 16-18 July 2018, Reading, UK. (In Press)

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Abstract

Patient safety and accidental harm or iatrogenic errors are increasingly important healthcare issues resulting in high costs and mortality. The way clinical workflow and actions are communicated can impact patient safety. Although much work has been done to identify the individual human factors and recommendations are made to control and reduce human factor errors, little work has been done to provide a structured methodology to analyse and control human factor influencing patient safety outcomes. In this paper, we build on the previous work on automatic development of clinical pathways, semiotic approach to modelling norm-base clinical pathways and propose a Human Factor Failure Modes and Effects Analysis (HFMA) which offers a systematic approach to define, design and incorporation of human factors in-to formal design of clinical pathways. Organisational semiotics methods specifically NAM and SAM are applied to identify and analyse controls to reduce the adverse impact of human factors in healthcare settings. This is achieved through modelling and integration of human factors into clinical pathways. This will result in more rigorous control the care process ensuring completeness, consistency and patient safety by enabling the mapping of formal and informal/safety controls into clinical pathways.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computing > Information management
Depositing User: Yu-Chun Pan
Date Deposited: 12 May 2018 12:21
Last Modified: 28 Aug 2021 07:09
URI: https://repository.uwl.ac.uk/id/eprint/4962

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