Abstract
Blood transfusion is usually considered to be safe and high-quality. Improvement measures have concentrated on assessing adherence to evidence-based guidelines, but this may fail to understand adaptations staff make in a complex, dynamic environment. Three hospitals in England were visited to trial a method for assessing adaptations in the complete vein to vein transfusion process. An open narrative question encouraged staff to describe adaptations voluntarily and a follow up question scored the level of support received from management. Adaptations can be categorised into: (1) preferred adaptations - developments expected to improve the process; (2) forced adaptations - workarounds and coping strategies when ideal solutions are outside of their control. Preferred adaptations indicate the surrounding system is adequate, but performance/well-being can be improved by adapting. Such adaptations may be good practices and lessons are to be shared. Forced adaptations indicate the surrounding system is inadequate, so people need to adapt to get work done. These may not be desirable, so are unlikely to be suitable for shared learning. Instead the surrounding system probably needs to be assessed or changed. Adaptations are made within staff members’ sphere of influence and although managers may have opportunities to make more resilient changes, frontline staff may be forced to make adaptations to get things done. To facilitate the design of more efficient and safer blood transfusion processes, there is a need for better understanding about how to carry out audit and incident investigation or reporting recognising the adaptations and resilience of healthcare staff.
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Watt, A., Jun, G.T., Waterson, P., Grant-Casey, J. (2019). Understanding Resilience and Adaptation in the Blood Transfusion Process Using Employee Accounts of Problem Resolution. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 818. Springer, Cham. https://doi.org/10.1007/978-3-319-96098-2_43
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DOI: https://doi.org/10.1007/978-3-319-96098-2_43
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