Improving patient safety through quality assurance

Arch Pathol Lab Med. 2006 May;130(5):633-7. doi: 10.1043/1543-2165(2006)130[633:IPSTQA]2.0.CO;2.


Context: Anatomic pathology laboratories use several quality assurance tools to detect errors and to improve patient safety.

Objective: To review some of the anatomic pathology laboratory patient safety quality assurance practices.

Design: Different standards and measures in anatomic pathology quality assurance and patient safety were reviewed.

Main outcome measures: Frequency of anatomic pathology laboratory error, variability in the use of specific quality assurance practices, and use of data for error reduction initiatives.

Results: Anatomic pathology error frequencies vary according to the detection method used. Based on secondary review, a College of American Pathologists Q-Probes study showed that the mean laboratory error frequency was 6.7%. A College of American Pathologists Q-Tracks study measuring frozen section discrepancy found that laboratories improved the longer they monitored and shared data. There is a lack of standardization across laboratories even for governmentally mandated quality assurance practices, such as cytologic-histologic correlation. The National Institutes of Health funded a consortium of laboratories to benchmark laboratory error frequencies, perform root cause analysis, and design error reduction initiatives, using quality assurance data. Based on the cytologic-histologic correlation process, these laboratories found an aggregate nongynecologic error frequency of 10.8%. Based on gynecologic error data, the laboratory at my institution used Toyota production system processes to lower gynecologic error frequencies and to improve Papanicolaou test metrics.

Conclusion: Laboratory quality assurance practices have been used to track error rates, and laboratories are starting to use these data for error reduction initiatives.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Humans
  • Medical Errors / prevention & control*
  • Medical Errors / statistics & numerical data
  • Pathology, Surgical / standards*
  • Patients*
  • Quality Assurance, Health Care*
  • Safety Management / methods*