Quality

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Quality, in pathology, has got a lot of attention lately because there have been high profile screw-ups that lead to significant harm.[1][2]

General

The keys to quality are understanding the:

  1. Needs of the stakeholders (surgeons, oncologists, patients, other pathologists, the public at large).
  2. Processes.
  3. Developing measures of quality.
  4. Tracking the measures of quality & assessing their validity.
  5. Understanding the causes of failures/adverse events in the context of the processes.
  6. Continually doing all of the above with the aim of improving outcomes.

Analysis

Overview

Quality issues can be examined in a number of different ways.

Finding a problem:

  • Root cause analysis.

Anticipating problems:

  • Failure mode and effects analysis (FMEA).

General error analysis

Pathology errors happen any time from when the lab gets the specimen until after the report is issued.

When errors happen:

  • Work-up the problem.
    • Where did the error occur? Pathologist error?
  • Talk to the clinician.
    • If it is a critical diagnosis contact the most-responsible physician immediately... if they are unreachable call the physician on-call for the most-responsible physician... if the patient is out-of-town you may have to coordinate with the local emergency department.
  • Talk to the chief of pathology.
  • Incident report.
  • Reconstruct error.
    • Was it a specimen mix-up?
      • Is there another error?
  • Amend the report(s).
  • Remedy the source of error.

The classic structural break down

A classic structal break down for error analysis is:

 
 
 
 
 
 
 
 
Errors in pathology
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Pre-analytical errors
 
 
Analytical errors
 
 
Post-analytical errors

Note:

  • This break down is arbitrary and in of itself most useful for answering exam questions.
  • In a practical context, it is a frame work for classifying errors. It is not useful for understanding the source of an error or addressing it.

Pre-analytic errors

  • Container mix-up - pre-lab & in-lab.
  • Block mix-up.
  • Slide mix-up - labels wrong.
  • Poor quality slides (fixation, processing, staining).
  • Lost specimen - can be potentially anywhere in the process.

Analytic errors

  • Interpretation wrong.
    • Factors:
      • Difficult case.
      • Technical factors (quality of slides).
      • Lack of clinical history.

Post-analytic errors

  • Wrong case signed-out.
  • Filing problem/lost report.
  • Interpretation of report problem (poorly written report, misinterpretation).

Sources of error

  • "Human error".
    • Training.
    • Work flow.
  • Process gaps.
    • Process control.
    • Lack of redundancy.

Types of errors

Can be subdivided into the following groups:[3]

  • False-negative - missed diagnosis.
  • False-positive - diagnosis made that on review considered not to be present.
  • Threshold - difference of opinion regarding a diagnostic threshold.
  • Type and grade.
  • Missed margin.
  • Other.

Grading of errors

May be subdivided by three groups:

  • Grade 1: no consequence.
  • Grade 2: possible consequence.
  • Grade 3: definitely a consequency.

Error reduction

Various strategies can be employed:[4]

  • Training of staff - on error handling.
  • Computer order entry.
    • Avoid duplication fatigue.
    • Quick correlation with several identifying features.
      • Full name, sex, date of birth -- these all appear when one opens a case.
  • Barcode use.
    • Avoid transcription errors.
  • Clinical information entry required.
    • Allow correlation with test.
      • The interpretation may differ if the history says "screening coloscopy" versus "large cecal mass, anemia and weight loss" versus "breast cancer".

Other strategies:

  • Statistical process control.

Biopsy size

Very small tissue fragments are associated with a decreased diagnostic yield and an increased diagnostic uncertainty.

Measures of quality

Any number of parameters can be used to measure quality. The when, where and how-often something is measured depends on the value-added.

General measures of quality

There are really only two:

  1. Timeliness, i.e. turn-around time (TAT).
  2. Error rate.

Note:

  • 1 and 2 can be examined/quantified in any number of ways.
  • Error, in the context of a measurement, has to be defined.

Smaller categories

Smaller categories - errors:[5]

  • Analytic: specimen identification & transport.
  • Preanalytic/analytic: tissue processing, e.g. fixation, blocking, embedding, sectioning, staining.
  • Analytic: interpretation.
  • Postanalytic: reporting/report integrity.
Individual measures

Specific measures:[5]

  • Preanalytic:
    • Identification - numbers match requisition.
    • Appropriate container.
  • Analytic:
    • Mislabeling.
    • Interpretation errors - based on:
      • Internal review.
        • Cytology-histology correlation.
        • Biopsy-resection correlation.
        • Frozen section-permanent section correlation.
        • Internal comparisons, e.g. ASCUS/LSIL between pathologists.
      • External review.
        • External standards/expected rate.
    • Amended reports - captures several of the above.
  • Postanalytic:
    • Completeness of report.
    • Critical diagnosis timely?
    • Report delivered to appropriate person?

Immunohistochemistry

Classification of IHC tests

IHC tests are classified in a paper by Torlakovic et al.:[6]

  • Class I:
    • Results used by pathologists.
    • Adjunct to histomorphology.
    • Examples: CD45, S-100.
  • Class II:
    • Used by clinicans for treatment decisions.
    • Considered independent of the other information in the pathology report; thus, cannot be derived from other information in the report.
    • Examples: ER, PR, HER2, Ki-67, CD117, CD20.

The implication of irregularies in the different classes are different. Problems in Class II tests are potentially more severe, as there is no internal control.

Work-up of suspected IHC problems

  • Review controls (internal and external).
    • Isolated to case vs. larger problem?
      • Discuss with lab/make other pathologists aware of the issue.
  • Repeat test - to identify the cause.

IHC process:

  1. Ischemia time - warm ischemia, preparation of specimen.
  2. Fixation - under, over, defective fixative, not enough fixative.
  3. Processing prior to antibody binding, usu. heating (antigen retrieval).
  4. Antibody-antigen binding.
  5. Reporter molecule binding.
  6. Counterstaining.
  7. Interpretation problem.
    • Known/expected epitope cross-reactions, e.g. CMV & HSV.[7]
    • Unknown/unexpected epitope cross-reactions.

Notes:

  • Problems can arise at any step.

Other

Failure-potential analysis

Adapted from Ullman:[8]

  1. Identify potential individual failures.
  2. Identify the consequences of those failures.
  3. Identify how the individual failures can arise.
  4. Identify the corrective action.

See also

References

  1. URL: http://www.attorneygeneral.jus.gov.on.ca/inquiries/goudge/index.html. Accessed on: 1 March 2011.
  2. Judicial inquiry probes faulty breast cancer tests. CBC website. URL: http://www.cbc.ca/news/background/cancer/inquiry.html. Accessed on: 30 January 2012.
  3. Renshaw, AA. (Mar 2001). "Measuring and reporting errors in surgical pathology. Lessons from gynecologic cytology.". Am J Clin Pathol 115 (3): 338-41. doi:10.1309/M2XP-3YJA-V6E2-QD9P. PMID 11242788.
  4. Fabbretti, G. (Jun 2010). "Risk management: correct patient and specimen identification in a surgical pathology laboratory. The experience of Infermi Hospital, Rimini, Italy.". Pathologica 102 (3): 96-101. PMID 21171512.
  5. 5.0 5.1 Nakhleh, RE. (Nov 2009). "Core components of a comprehensive quality assurance program in anatomic pathology.". Adv Anat Pathol 16 (6): 418-23. doi:10.1097/PAP.0b013e3181bb6bf7. PMID 19851132.
  6. Torlakovic, EE.; Riddell, R.; Banerjee, D.; El-Zimaity, H.; Pilavdzic, D.; Dawe, P.; Magliocco, A.; Barnes, P. et al. (Mar 2010). "Canadian Association of Pathologists-Association canadienne des pathologistes National Standards Committee/Immunohistochemistry: best practice recommendations for standardization of immunohistochemistry tests.". Am J Clin Pathol 133 (3): 354-65. doi:10.1309/AJCPDYZ1XMF4HJWK. PMID 20154273.
  7. Balachandran, N.; Oba, DE.; Hutt-Fletcher, LM. (Apr 1987). [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073 URL = http://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073/?tool=pubmed/ "Antigenic cross-reactions among herpes simplex virus types 1 and 2, Epstein-Barr virus, and cytomegalovirus."]. J Virol 61 (4): 1125-35. PMC [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073 URL = http://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073/?tool=pubmed 254073 URL = http://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073/?tool=pubmed]. PMID 3029407. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073 URL = http://www.ncbi.nlm.nih.gov/pmc/articles/PMC254073/?tool=pubmed/.
  8. Ullman, David G. (1997). The mechanical design process. Toronto: McGraw-Hill Companies Inc.. ISBN 0-07-065756-4.