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An organisation without a memory: A qualitative study of hospital staff perceptions on reporting and organisational learning for patient safety

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  • Sujan, Mark

Abstract

Following the Public Enquiry into avoidable deaths and poor standards of care at Mid Staffordshire NHS Foundation Trust, the English National Health Service (NHS) is aiming to become a system devoted to continual learning and improvement of patient care. The paper aims to explore current perceptions of healthcare staff towards reporting and organisational learning for improving patient safety. Based on a Thematic Analysis of semi-structured interviews with 35 healthcare professionals in two NHS organisations, the paper argues that previously identified barriers to incident reporting remain problematic, and that less centralised processes that aim to learn from everyday clinical work might be better suited to generate actionable learning and change in the local work environment. The findings might support healthcare organisations in understanding better the practical processes of organisational learning at the local level. The findings might also support researchers in developing new approaches and strategies for integrating learning about risk at the local level with effective organisational change to improve patient safety.

Suggested Citation

  • Sujan, Mark, 2015. "An organisation without a memory: A qualitative study of hospital staff perceptions on reporting and organisational learning for patient safety," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 45-52.
  • Handle: RePEc:eee:reensy:v:144:y:2015:i:c:p:45-52
    DOI: 10.1016/j.ress.2015.07.011
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    References listed on IDEAS

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    1. Sujan, Mark A., 2012. "A novel tool for organisational learning and its impact on safety culture in a hospital dispensary," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 21-34.
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    Cited by:

    1. Raben, Ditte Caroline & Viskum, Birgit & Mikkelsen, Kim L. & Hounsgaard, Jeanette & Bogh, Søren Bie & Hollnagel, Erik, 2018. "Application of a non-linear model to understand healthcare processes: using the functional resonance analysis method on a case study of the early detection of sepsis," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 1-11.
    2. Sujan, Mark A. & Habli, Ibrahim & Kelly, Tim P. & Gühnemann, Astrid & Pozzi, Simone & Johnson, Christopher W., 2017. "How can health care organisations make and justify decisions about risk reduction? Lessons from a cross-industry review and a health care stakeholder consensus development process," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 1-11.
    3. Mari Liukka & Alison Steven & M Flores Vizcaya Moreno & Arja M Sara-aho & Jayden Khakurel & Pauline Pearson & Hannele Turunen & Susanna Tella, 2020. "Action after Adverse Events in Healthcare: An Integrative Literature Review," IJERPH, MDPI, vol. 17(13), pages 1-18, June.
    4. Patriarca, Riccardo & Bergström, Johan & Di Gravio, Giulio, 2017. "Defining the functional resonance analysis space: Combining Abstraction Hierarchy and FRAM," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 34-46.
    5. Raben, Ditte Caroline & Bogh, Søren Bie & Viskum, Birgit & Mikkelsen, Kim L. & Hollnagel, Erik, 2018. "Learn from what goes right: A demonstration of a new systematic method for identification of leading indicators in healthcare," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 187-198.
    6. Hernandez-Perdomo, Elvis & Guney, Yilmaz & Rocco, Claudio M., 2019. "A reliability model for assessing corporate governance using machine learning techniques," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 220-231.
    7. Antonovsky, A. & Pollock, C. & Straker, L., 2016. "System reliability as perceived by maintenance personnel on petroleum production facilities," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 58-65.
    8. Ilaria Tocco Tussardi & Francesca Moretti & Mario Capasso & Valentina Niero & Donatella Visentin & Livio Dalla Barba & Stefano Tardivo, 2022. "Improving the culture of safety among healthcare workers: Integration of different instruments to gain major insights and drive effective changes," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 429-451, January.
    9. Sujan, Mark A. & Embrey, David & Huang, Huayi, 2020. "On the application of Human Reliability Analysis in healthcare: Opportunities and challenges," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    10. Simsekler, Mecit Can Emre & Rodrigues, Clarence & Qazi, Abroon & Ellahham, Samer & Ozonoff, Al, 2021. "A comparative study of patient and staff safety evaluation using tree-based machine learning algorithms," Reliability Engineering and System Safety, Elsevier, vol. 208(C).

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