Your unit data reflect an upward trend in blood administration errors. Is this likely an individual failure or a system failure? Which performance improvement theory or model would you use to address it?
Solution
The upward trend in blood administration errors is more likely to be a systemic issue rather than an individual failure, as mistakes in healthcare often arise from underlying system vulnerabilities such as inefficient workflows, unclear protocols, inadequate training, or communication gaps (Brown & Brown, 2023). This aligns with James Reason’s Swiss Cheese Model, which highlights how errors occur when multiple layers of defense (e.g., protocols, training, safety checks) fail simultaneously (Howard & Dimick, 2024). To address this, the Model for Improvement using PDSA (Plan-Do-Study-Act) cycles is a robust framework, as it emphasizes iterative, data-driven testing of systemic changes—such as standardizing workflows, enhancing barcode scanning systems, or redesigning error-prone steps—while measuring their impact over time (Hill et al., 2020). Complementary approaches like Root Cause Analysis (RCA) can uncover specific process gaps. At the same time, SEIPS (Systems Engineering Initiative for Patient Safety) helps map interactions between tools, tasks, and environmental factors contributing to errors. Simultaneously, fostering a blame-free reporting culture, simplifying complex processes, and integrating automated safeguards (e.g., EHR alerts) can reduce risks. Organizations can improve safety, reduce errors, and create resilient workflows that protect patients and staff by focusing on system-level solutions rather than individual blame (Sampson et al., 2021).
References:
Brown, C., & Brown, M. (2023). Blood and blood products transfusion errors: What can we do to improve patient safety? British Journal of Nursing, 32(7), 326–332. https://doi.org/10.12968/bjon.2023.32.7.326
Hill, J. E., Stephani, A. M., Sapple, P., & Clegg, A. J. (2020). The effectiveness of continuous quality improvement for developing professional practice and improving health care outcomes: A systematic review. Implementation Science, 15, 1-14. https://doi.org/10.1186/s13012-020-0975-2
Howard, R., & Dimick, J. B. (2024). Human factors and principles of patient safety: The James Reason Model. In Springer eBooks (pp. 3–15). https://doi.org/10.1007/978-3-031-41089-5_1
Sampson, P., Back, J., & Drage, S. (2021). Systems-based models for investigating patient safety incidents. BJA education, 21(8), 307.https://doi.org/10.1016/j.bjae.2021.03.004