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Your unit data reflect an upward trend in blood administration errors

Your unit data reflect an upward trend in blood administration errors

NUR 630 Topic 3 DQ 1

The increase in the number of blood transfusion errors indicates that the problem is not limited to a single individual or a one-time occurrence. Therefore, in order to address this issue, it is important to examine the entire process. Healthcare delivery is a complex and dynamic environment with numerous variables, and critical decisions are often made in a short amount of time. This is why analyzing the systems and processes is the most appropriate approach to take when looking at errors (Singh et al., 2023, para. 3). By conducting a thorough analysis of the standard procedures, we can identify the actions that are taken and determine where the opportunities lie for refining the process. Root cause analysis (RCA) is a method that focuses on understanding the how and why behind the error rather than the who. By analyzing the processes involved, we can determine the next steps needed to mitigate errors.

According to Fondahn et al. (2016, p.211), a reliable analysis of an adverse situation must include leadership representing the area being analyzed, providing a detailed explanation, answering appropriate questions related to the event, and considering applicable literature. When we consider the act of administering a blood transfusion, we recognize that errors can occur at multiple stages. Errors can stem from the doctor’s order, cross-matching in the lab, patient identifier missteps, mismanagement of adverse reactions, and documentation errors. Depending on the type of error, many different departments may be involved.

 

It is crucial to involve the right people in the situational analysis to ensure the best possible review and understanding of the true root of the issue. By doing so, we can work towards preventing future errors and improving patient safety.

Reference

Fondahn, E., Lane, M., & Vannucci, A. (2016). Washington manual of patient safety and quality improvement. Wolters Kluwer. ISBN-13: 9781451193558

Singh, G., Patel, R., & Booster, J. (2023). Root cause analysis and medical error prevention. National Library of Medicinehttps://www.ncbi.nlm.nih.gov/books/NBK570638/

 

A rising trend in blood administration errors is likely to be an individual failure since clerical errors primarily contribute to transfusion errors.  The common clerical errors include mislabeled blood samples, blood samples collected from the wrong patient, reversal of specimen samples in the laboratory, and incorrect blood component administration (Vahidi et al., 2021). Besides, individual errors in identification and verification at the patient bedside result in increased blood transfusion errors. Blood administration errors mainly occur if the administering nurse does not confirm the right patient, right blood product, and ABO compatibility in the patient (Vahidi et al., 2021). As a result, even if the blood is labeled appropriately, it is transfused to someone other than the correct recipient. The nurses could be failing to follow blood administration procedures, including identifying a patient with two unique identifiers.

The Rapid improvement model (RIM) can address individual failures in blood administration.  RIM is a quick method of enhancing work processes, which enables teams to implement a small change, test and evaluate it, and then accept if effective or reject if ineffective (Smith & Johnson, 2019). It is a quality improvement approach that identifies, executes, and evaluates changes made to enhance a process or a system. The model proposes implementing and testing changes over three months or less. RIM can be used to improve the process of blood administration by first establishing the improvements desired and defining how we want to change the process of administering blood (Smith & Johnson, 2019). The next step will be to identify the measures to assess whether the changes made have improved the blood administration process. The last step will be to establish the changes that will help reduce blood administration errors. We will evaluate the options that are most likely to work and identify what other organizations have done to minimize the errors.

References

Smith, C. M., & Johnson, C. S. (2019). Preparing nurse leaders in nursing professional development: Quality improvement in nursing professional development. Journal for nurses in professional development35(4), 222-224. doi: 10.1097/NND.0000000000000540

Vahidi, S., Mirhashemi, S. H., Hashemi, B., Noorbakhsh, M., & Molavi-Taleghani, Y. (2021). Improvement in Blood Transfusion Safety: Using Root Cause Analysis. Journal of Comprehensive Pediatrics, (In Press). DOI : 10.5812/compreped.99088

 

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Intravenous medication errors have a high rate if occurring for many reasons. Blood product administration errors are just as serious, if not more. The error can produce a serious negative outcome for both the patient as well as the nurse.  In my experience it has been noted that the errors that have occurred were due to the nurse failing to verify the order such as the rate as well as verify if the blood type and product were compatible (Westbrook et al., 2011). In this case, I would utilize the Chaos change theory to address this situation. The Chaos change theory was developed by Edward Lorenz. A meteorologist and mathematician in the 1960’s as a way of showing that even a small change can have a great impact (Oestreicher, 2007). I would utilize this theory as indicated that when we make a shift in our practice or mindset, even the smallest action can make a world of difference. In the scenario, if the nurse is comfortable in their practice of administering blood products or overworked due to the shortage of nurses, they may be lacks in their routine especially following procedure. Review of the errors and incident reports can help determine where the changes are needed. Often times the change that is needed may be just as simple as revamping the flow sheet and reeducating on the policies and procedures.

 

References:

Oestreicher, C. (2007). A history of chaos theory. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3202497/

Westbrook, J., Rob, M., Woods, A., & Parry, D. (2011). Original research errors in the administration of intravenous … https://qualitysafety.bmj.com/content/qhc/20/12/1027.full.pdf

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