Evidence map›Paper›PMID 25250191›Full record

ArticleJournal of pathology informatics2014

Can digital pathology result in cost savings? A financial projection for digital pathology implementation at a large integrated health care organization.

Jonhan Ho, Stefan M Ahlers, Curtis Stratman, Orly Aridor, Liron Pantanowitz, Jeffrey L Fine, John A Kuzmishin, Michael C Montalto, Anil V Parwani

Abstract read
In one paragraph

Article in Journal of pathology informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed
–field-weighted citation impact
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

77 citing papers in PubMed.

  1. Trial
  2. Review
  3. Observational
  4. The patient matters: a roundtable discussion on pathology in the era of digitization and AI.Virchows Archiv : an international journal of pathology · 2026
    Article
  5. Review
  6. Review
  7. Article
  8. Digital transformation of pathology - the European Society of Pathology expert opinion paper.Virchows Archiv : an international journal of pathology · 2025
    Article
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  12. Article
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  18. Article
  19. Article
  20. Review

17 more citing papers are in PubMed but not listed here.

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

9 authors.

Jonhan HoDepartment of Dermatology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Stefan M AhlersInternational and Commercial Services Division, UPMC, Pittsburgh, PA, USA.
Curtis StratmanOmnyx LLC, Pittsburgh, PA, USA.
Orly AridorOffice of Sponsored Programs and Research Support, University of Pittsburgh Medical Center, UPMC, Pittsburgh, PA, USA.
Liron PantanowitzDepartment of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Jeffrey L FineDepartment of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
John A KuzmishinInternational and Commercial Services Division, UPMC, Pittsburgh, PA, USA.
Michael C MontaltoOmnyx LLC, Pittsburgh, PA, USA.
Anil V ParwaniDepartment of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital pathology offers potential improvements in workflow and interpretive accuracy. Although currently digital pathology is commonly used for research and education, its clinical use has been limited to niche applications such as frozen sections and remote second opinion consultations. This is mainly due to regulatory hurdles, but also to a dearth of data supporting a positive economic cost-benefit. Large scale adoption of digital pathology and the integration of digital slides into the routine anatomic/surgical pathology "slide less" clinical workflow will occur only if digital pathology will offer a quantifiable benefit, which could come in the form of more efficient and/or higher quality care.

aimAs a large academic-based health care organization expecting to adopt digital pathology for primary diagnosis upon its regulatory approval, our institution estimated potential operational cost savings offered by the implementation of an enterprise-wide digital pathology system (DPS).

methodsProjected cost savings were calculated for the first 5 years following implementation of a DPS based on operational data collected from the pathology department. Projected savings were based on two factors: (1) Productivity and lab consolidation savings; and (2) avoided treatment costs due to improvements in the accuracy of cancer diagnoses among nonsubspecialty pathologists. Detailed analyses of incremental treatment costs due to interpretive errors, resulting in either a false positive or false negative diagnosis, was performed for melanoma and breast cancer and extrapolated to 10 other common cancers.

resultsWhen phased in over 5-years, total cost savings based on anticipated improvements in pathology productivity and histology lab consolidation were estimated at $12.4 million for an institution with 219,000 annual accessions. The main contributing factors to these savings were gains in pathologist clinical full-time equivalent capacity impacted by improved pathologist productivity and workload distribution. Expanding the current localized specialty sign-out model to an enterprise-wide shared general/subspecialist sign-out model could potentially reduce costs of incorrect treatment by $5.4 million. These calculations were based on annual over and under treatment costs for breast cancer and melanoma estimated to be approximately $26,000 and $11,000/case, respectively, and extrapolated to $21,500/case for other cancer types.

conclusionsThe projected 5-year total cost savings for our large academic-based health care organization upon fully implementing a DPS was approximately $18 million. If the costs of digital pathology acquisition and implementation do not exceed this value, the return on investment becomes attractive to hospital administrators. Furthermore, improved patient outcome enabled by this technology strengthens the argument supporting adoption of an enterprise-wide DPS.

Indexed as

Anatomic pathologycostcost analysisdigital pathologyproductivitywhole slide imaging

Identifiers

PMID25250191
PMCPMC4168664

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Registered trials

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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.