To adjust performance to ensure the success of a task and prevent error, it is necessary to anticipate, identify and respond to variations in the work system. The objectives of this study were to develop a framework for the analysis of signals, which provide an indication of variations in the system, in the healthcare environment and qualitatively investigate signals in the context of community-based
patient discharge. In addition to the signals, both traditional (Safety-I) and proactive safety (SafetyII)
elements were investigated with six expert groups, from the field of community-based patient discharge. The signals identified and the safety elements were analysed using the SEIPS 2.0 model. The sources of the signals were identified as originating from work system elements. The proposed
framework and method provide a preliminary basis for the investigation of signals and assists in highlighting the role that these can play in safety behaviour.
Funding
The project was commissioned as a result of a successful joint bid for funding by Health Partnerships, a Division within Nottinghamshire Health Care NHS Foundation Trust and Loughborough University Design School.
History
School
Design
Published in
The 13th International Conference on Naturalistic Decision Making
Pages
314 - 321
Citation
CARMAN, E-M., FRAY, M. and WATERSON, P., 2017. Weak signals in healthcare: A case study on community-based patient discharge. IN: Gore, J. and Ward, P. (eds). NDM13 Naturalistic Decision Making and Uncertainty. Proceedings of the 13th International Conference on Naturalistic Decision Making, Bath, UK, 20-23 June 2017, pp.314-321.
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