Farrell C‐JL, Giannoutsos J. Int J Lab Hematol. 2022;44:497-503.
Wrong blood in tube (WBIT) errors can result in serious diagnostic and treatment errors, but may go unrecognized by clinical staff. In this study, machine learning was used to identify potential WBIT errors which were then compared to manual review by laboratory staff. The machine learning models showed higher accuracy, sensitivity, and specificity compared to manual review.
Seferian EG, Jamal S, Clark K, et al. BMJ Qual Saf. 2014;23:690-7.
This quality improvement initiative used human factors approaches including failure mode and effect analysis, event review, and root cause analysis to successfully reduce the rate of specimen mislabeling in an inpatient setting. This study highlights the importance of re-examining longstanding work processes to augment safety.
Salinas M, López-Garrigós M, Lillo R, et al. Clin Biochem. 2013;46:1767-9.
Although electronic test ordering resulted in fewer patient identification errors in a clinical laboratory, significant variability in error rates between centers remained, emphasizing the continued effect of human behavior on interventions.
This monthly column reports on an error involving products with similar names (quinine and quinidine) and discusses the Anesthesia Patient Safety Foundation's recommendations for safe use of patient-controlled analgesia.
Paterson R. Auckland, NZ; Office of the Health and Disability Commissioner: April 2007.
This report analyzes an incident of medication error that led to a patient's death, discusses the subsequent actions taken by the health board, and calls for a coordinated approach to medication reconciliation in New Zealand.
Bittle MJ, Charache P, Wassilchalk DM. Jt Comm J Qual Patient Saf. 2007;33:25-33.
In response to multiple incidents of registration-associated patient misidentification (eg, assigning a new patient an existing patient's medical record number), an interdisciplinary team used plan-do-study-act methodology to investigate the root cause of such errors and formulate solutions. Several system problems were identified, ranging from inadequate training of registrars to the lack of a true master list of patients' medical record numbers. The authors describe the iterative process used to identify and address sources of error at several points within the patient registration process.
A woman with a fractured right foot receives spinal anesthesia and nearly has surgery for trimalleolar fracture and dislocation of the left ankle. Only immediately prior to surgery did the team realize that the x-ray was not hers.
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