Performance improvement theory and models: Blood transfusion errors
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Performance improvement theory and models: Blood transfusion errors
In the provision of care in acute healthcare settings, blood administration is one of the most common practices. However, it is also accompanied by blood transfusion errors, resulting in morbidity or mortality of the patients. When these blood administration errors occur, the patients may be seriously injured or even incur lifelong injuries. There are several causes of blood administration errors, such as man errors, blood typing, and cross-matching. Mostly, human errors have been identified as a critical contributor to blood administration errors. Occasionally, the acute care physicians or nurses may assign blood to the wrong patients or send the wrong batches of blood to the wrong units. However, there are several theories or models developed to address these blood administration errors. Some of the common models are the FMEA, probabilistic model, and root-cause analysis approach. The failure mode and effect analysis FMEA may be applied to prevent these errors. It is used for risk analysis and management to promote the quality of care and patient safety. The root cause analysis model identifies the actual origin of the errors, such as human errors, and provides a risk assessment and compliance guideline to minimize the mistakes. The FMEA model is time-consuming but effective in evaluating blood transfusion and failures and identifying other clinical obstacles. (Najafpour et al., 2017).
In conclusion, it is essential to be careful while administering blood to avoid wrong blood transfusion challenges. Research shows that it has contributed to some hospital-acquired infections and even contributed to most patients’ death across numerous acute healthcare settings. Therefore, practitioners need to be careful and comply with the blood transfusion guidelines specific to their clinical setting.
References
Najafpour, Z., Hasoumi, M., Behzadi, F., Mohamadi, E., Jafary, M., & Saeedi, M. (2017). Preventing blood transfusion failures: FMEA, an effective assessment method. BMC Health Services Research, 17(1), 453.
Question
Your unit data reflects an upward trend in blood administration errors. Is this likely an individual failure or a system failure? Which theory or model would you use to address it?
Base this writing on an acute care hospital setting, please with good command of English.