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Blood administration errors can happen due to the human factor, and can be associated with patient adverse reactions that are critical due to the pathophysiology of blood product. The blood administration process must be hands on with much human involvement rather than systematic processes. Blood administration errors can be associated with many different process issues as one must identify patient, place orders, and failure can happen at many levels such as ordering on wrong patient, mixed up tubes or phlebotomy errors, or even the blood products being delivered to the wrong unit. These potential errors are all created at a human level and not a system error. Failure to launce compliance with blood administration policies can decrease awareness on the units and lead to an increase in errors as awareness is of great importance. Through research we have learned that blood administration errors is more likely to be an individual failure and not a system failure.
If my unit was to reflect an upward trend in blood administration errors, I would use a root-cause analysis model to address the issue in blood administration error. With the root-cause analysis model, the causes of blood administration errors can be identified and addressed. Root cause analysis is the process of identifying the causes of the errors and responding to them. After one identifies the causes of the errors one can initiate measures, and policies that raise awareness such as training staff, updating the blood administration policies, and updating policies to ensure best practices are being followed in blood administration on the units.
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FYI, this is the question of this answer: 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?
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