alexa Errors in laboratory medicine: practical lessons to improve patient safety.
Biochemistry

Biochemistry

Biochemistry & Physiology: Open Access

Author(s): Howanitz PJ

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Abstract CONTEXT: Patient safety is influenced by the frequency and seriousness of errors that occur in the health care system. Error rates in laboratory practices are collected routinely for a variety of performance measures in all clinical pathology laboratories in the United States, but a list of critical performance measures has not yet been recommended. The most extensive databases describing error rates in pathology were developed and are maintained by the College of American Pathologists (CAP). These databases include the CAP's Q-Probes and Q-Tracks programs, which provide information on error rates from more than 130 interlaboratory studies. OBJECTIVES: To define critical performance measures in laboratory medicine, describe error rates of these measures, and provide suggestions to decrease these errors, thereby ultimately improving patient safety. SETTING: A review of experiences from Q-Probes and Q-Tracks studies supplemented with other studies cited in the literature. DESIGN: Q-Probes studies are carried out as time-limited studies lasting 1 to 4 months and have been conducted since 1989. In contrast, Q-Tracks investigations are ongoing studies performed on a yearly basis and have been conducted only since 1998. Participants from institutions throughout the world simultaneously conducted these studies according to specified scientific designs. The CAP has collected and summarized data for participants about these performance measures, including the significance of errors, the magnitude of error rates, tactics for error reduction, and willingness to implement each of these performance measures. MAIN OUTCOME MEASURES: A list of recommended performance measures, the frequency of errors when these performance measures were studied, and suggestions to improve patient safety by reducing these errors. RESULTS: Error rates for preanalytic and postanalytic performance measures were higher than for analytic measures. Eight performance measures were identified, including customer satisfaction, test turnaround times, patient identification, specimen acceptability, proficiency testing, critical value reporting, blood product wastage, and blood culture contamination. Error rate benchmarks for these performance measures were cited and recommendations for improving patient safety presented. CONCLUSIONS: Not only has each of the 8 performance measures proven practical, useful, and important for patient care, taken together, they also fulfill regulatory requirements. All laboratories should consider implementing these performance measures and standardizing their own scientific designs, data analysis, and error reduction strategies according to findings from these published studies. This article was published in Arch Pathol Lab Med and referenced in Biochemistry & Physiology: Open Access

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