Errors in laboratory medicine: practical lessons to improve patient safety

Peter J Howanitz1

  • 1Department of Pathology, State University of New York Downstate, Brooklyn, NY 11203, USA. Peter.Howanitz@downstate.edu

Abstract

Insights

Critical performance measures in laboratory medicine were identified to improve patient safety. Eight key measures, including patient identification and critical value reporting, were recommended for error reduction in clinical pathology laboratories.

Area of Science:

  • Laboratory Medicine
  • Healthcare Quality Improvement
  • Patient Safety

Background:

  • Patient safety is significantly impacted by healthcare errors.
  • Clinical pathology laboratories in the US routinely collect error rate data.
  • A standardized list of critical performance measures for laboratories was previously lacking.

Purpose of the Study:

  • To define critical performance measures in laboratory medicine.
  • To report error rates associated with these measures.
  • To provide actionable strategies for error reduction to enhance patient safety.

Main Methods:

  • A comprehensive literature review was conducted, focusing on College of American Pathologists (CAP) Q-Probes and Q-Tracks studies.
  • Data from over 130 interlaboratory studies were analyzed.
  • Experiences from ongoing (Q-Tracks) and time-limited (Q-Probes) studies were synthesized.

Main Results:

  • Preanalytic and postanalytic performance measures exhibited higher error rates than analytic measures.
  • Eight critical performance measures were identified: customer satisfaction, test turnaround times, patient identification, specimen acceptability, proficiency testing, critical value reporting, blood product wastage, and blood culture contamination.
  • Benchmarks for error rates were established, with recommendations for patient safety improvement.

Conclusions:

  • The eight identified performance measures are practical, valuable, and essential for patient care.
  • Implementation of these measures aids in meeting regulatory requirements.
  • Laboratories are encouraged to adopt these measures and standardize their data analysis and error reduction strategies based on published findings.

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