Evidence map›Paper›PMID 37659445›Full record

ArticleLaboratory investigation; a journal of technical methods and pathology2023

Quality Management System in Clinical Digital Pathology Operations at a Tertiary Cancer Center.

Orly Ardon, Marc Labasin, Maria Friedlander, Allyne Manzo, Lorraine Corsale, Peter Ntiamoah, Jeninne Wright, Kojo Elenitoba-Johnson, Victor E Reuter, Meera R Hameed and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Laboratory investigation; a journal of technical methods and pathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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  4. Interobserver Variability Across Whole-Slide Imaging Systems.Archives of pathology & laboratory medicine · 2026
    Article
  5. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 1 institution in 1 country.

Orly ArdonDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York. Electronic address: ardono@mskcc.org.
Marc LabasinDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Maria FriedlanderDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Allyne ManzoDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Lorraine CorsaleDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Peter NtiamoahDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Jeninne WrightDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Kojo Elenitoba-JohnsonDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Victor E ReuterDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Meera R HameedDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Matthew G HannaDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Digital pathology workflows can improve pathology operations by allowing reliable and fast retrieval of digital images, digitally reviewing pathology slides, enabling remote work and telepathology, use of computer-aided tools, and sharing of digital images for research and educational purposes. The need for quality systems is a prerequisite for successful clinical-grade digital pathology adoption and patient safety. In this article, we describe the development of a structured digital pathology laboratory quality management system (QMS) for clinical digital pathology operations at Memorial Sloan Kettering Cancer Center (MSK). This digital pathology-specific QMS development stemmed from the gaps that were identified when MSK integrated digital pathology into its clinical practice. The digital scan team in conjunction with the Department of Pathology and Laboratory Medicine quality team developed a QMS tailored to the scanning operation to support departmental and institutional needs. As a first step, systemic mapping of the digital pathology operations identified the prescan, scan, and postscan processes; instrumentation; and staffing involved in the digital pathology operation. Next, gaps identified in quality control and quality assurance measures led to the development of standard operating procedures and training material for the different roles and workflows in the process. All digital pathology-related documents were subject to regulatory review and approval by departmental leadership. The quality essentials were developed into an extensive Digital Pathology Quality Essentials framework to specifically address the needs of the growing clinical use of digital pathology technologies. Using the unique digital experience gained at MSK, we present our recommendations for QMS for large-scale digital pathology operations in clinical settings.

Indexed as

NeoplasmsPathology, ClinicalTelepathologyHumansLaboratoriesTotal Quality Managementclinical implementationdigital pathology operationsquality management

Identifiers

PMID37659445
PMCPMC10841911
OpenAlexW4386318606

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.