Rigshospitalet

National pathology reporting system – the Danish experience

Ben Vainer, Professor of digital pathology

Vera Timmermans, Head of department

Department of Pathology

Rigshospitalet, University of Copenhagen

Department of Pathology

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

Content

Rigshospitalet, University of Copenhagen National pathology database Denmark

• Pathology information system

• National pathology database

• The Danish Cancer Biobank

• Digital image analysis

• Business intelligence

Rigshospitalet

Rigshospitalet – Dept. of Pathology

Primary service to the Copenhagen area, the island of

Bornholm, The Faroe Islands and Greenland.

Special consulting services for the rest of Denmark.

Beds, hospital 1,400

Senior consultants, dept. 39

Residents 12

Other employees Appr. 145

Annual requisitions 95,000

Stained glass slides produced 635,000

Publications, peer-reviewed (2015) 100

Rigshospitalet

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

The Danish Pathology Databank –”Patobank”

Rigshospitalet, University of Copenhagen National pathology database Denmark

Includes pathology

analyses performed at each

of the 13 pathology

departments in Denmark

Data

report to

national

database

Rigshospitalet

Patobank

Rigshospitalet, University of Copenhagen National pathology database Denmark

• Established 1999

• Access to previous pathology reports, nationwide

• 7,000 individual SNOMED codes

• Direct access via patient e-journal solutions

• Management of screening programmes for cervical and colorectal

cancer

• Research• Integration with other national registers

• National Cancer Registry

• Organ-specifik cancer research registers

• Search by department, specimen type, disorder, pathoanatomic feature etc.

• Management and workload assessment (BI) (economy, ressource

planning etc.)

Rigshospitalet

Danish Cancer Biobank

Rigshospitalet, University of Copenhagen National pathology database Denmark

• National register of blood and tissue

samples from cancer patients

• Tissue collection

• Selected surgical specimens

• Fresh cancer tissue• Frozen

• Tissue Tek

• RNAlater

• FFPE section for verification

• Normal tissue for comparison

Rigshospitalet

Integration to Patobank

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

LIS – sample handling and managing

Rigshospitalet, University of Copenhagen National pathology database Denmark

• Working list and specimen

overview

• Ordering of stainings

• Specimen flow

Rigshospitalet

Macroscopic imaging – integration in LIS

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

Rigshospitalet, University of Copenhagen National pathology database Denmark

Pathology system

getAllAnswers

Pathology/

Image

DB

Image integration

Import classifications

Analysis instrument

integration

EDI/HL7 integration Cpr integration

Pathology bank

integration

Social security number (cpr)

Clinical systems (EHR)

Classificationsystems

Laboratory answer bank

BioBank

Name, address etc.

EDI/HL7 based messages (order and answer)

All results

for a patient

SHAK,

SNOMED

WebReq

EDI/HL7 based

messages (order)

Pathology bank

XRPT01

formatted

answers

Analysis instruments

Analysis

results

Imagescanners

Image URL

Rigshospitalet

Business Intelligence

Rigshospitalet, University of Copenhagen National pathology database Denmark

Initiatives in the pipeline

COPENHAGEN UNIVERSITY HOSPITAL / RIGSHOSPITALET

Home office / ”digital pathology”

Remote pathology (kidneys,

skin, lungs, heart, prostate,

mesothelioma)

Freeze sections

Agreement prior to initial

diagnose

Faster treatment initiation

Mutual education

Patient-safe lab logistics

Patient identification

Lab management

Online consultations

Faster second opinion

Faster referral

Faster treatment initiation

Realtime consultations

Biomarker image analysis

Correct and safe diagnoses

Intelligent labour distribution

Increase objectivity and

interobserver agreement

Rigshospitalet

TMA, scanning and de-arraying

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

Image analysis and integration in the pathology LIS (HER2)

Rigshospitalet, University of Copenhagen National pathology database Denmark

Rigshospitalet

Sentinel node diagnostics –breast cancer and malignant melanoma

Rigshospitalet, University of Copenhagen National pathology database Denmark

Screening of sentinel nodesDiscard all true negatives

Breast

Stain: Cytokeratin (broad)

All true negatives are found

(neg.pred.value 100%; specificity 100%)

58% reduction in ”pathologist time”

Malignant melanoma

Stain: Melan-A

22% reduction in ”pathologist time”

False positive

Breast cancer SN

Malignant

Melanoma SN

Rigshospitalet

Copenhagen Surgical Pathology Update 2017

Rigshospitalet, University of Copenhagen National pathology database Denmark