Reaching New Levels of Patient Safety Through Improved Specimen Labeling

View Presentation

Session
Clinical Performance Improvement

Authors
Leslie Fedraw
Systems Analyst
Mayo Clinic

Doreen Ryan
Quality Coordinator
Mayo Clinic

Gene Dankbar
Quality Improvment Analyst
Mayo Clinic

Description
Incorrect specimen labeling can adversely affect patient safety. In order to reduce the risk to patients, Mayo Clinic Rochester completed a project to improve and standardize the labeling process across clinical settings. Highlights of the project and lessons learned will be shared.

Abstract
Introduction: Incorrect specimen labeling has a high potential for patient harm. Misidentified specimens could cause results to be reported on the wrong patient and patients could be misdiagnosed or go undiagnosed. In order to reduce the risk to patients, Mayo Clinic Rochester completed a project to improve and standardize the labeling process across clinical settings. Methods: A multidisciplinary team visited various specimen collections sites throughout the institution. Based on these observations and review of labeling error data, key principles were developed to create a standardized labeling process. Analysis included Pareto charts, FMEA, user surveys, direct observation, prototyping, and run charts. Results: Direct observation and user surveys were used to assess the implementation of the standardized process in five diverse practice areas. Direct observation of personnel using the new process showed a reliability rate of 81-100%. User surveys indicated a large majority felt the new process improved patient safety with little or no added time. Campus-wide implementation involving 120+ inpatient and outpatient areas is currently in progress. Labeling error data is monitored to determine the impact of the new process. Conclusion: An institution-wide standardized specimen labeling process, based on key labeling principles, was successfully developed and implemented across diverse clinical settings.




© 2014 Society for Health Systems. All rights reserved.