Technology Evolution in Pathology: The University Health Network Experience Across Ontario Sylvia L. Asa, MD, PhD Pathologist-in-Chief Medical Director, Laboratory Medicine Program

Objectives Participants should have an understanding of: • • • • The nature of pathology practice in Ontario The reason for a centralized laboratory program The IT requirements for success of centralized pathology The reason for using digital imaging 2

Assumptions • A single payer, publically funded health care system • A large geographic area with population concentration in 5 large centers • A shortage of Pathologists 3

• • Initial Status Multiple hospitals of variable size scattered throughout the province – Toronto (GTA) has 7 major teaching hospitals and 35 other hospitals – 5 medical schools in various cities with 1-5 affiliated hospitals – – Other large cities with large, full-service hospitals Many small towns with hospitals of varying size Each hospital is operated as an independent entity with funding from the Ontario Ministry of Health and Long-term Care 4

Historical Issues • 1990s Ontario determined that – Health care costs were too high – Pathology was a dying field – There would be no need for Pathologists in the next century – Training programs in Pathology were slashed Outcome: major shortages of Pathologists emerged in late 1990s-2000 5

Healthcare Reform 1990s • • Regional planning for healthcare (LHINs) Consolidation of hospitals 6

The University Health Network • A consolidation of three U f T affiliated teaching hospitals • Programmatic restructuring – TGH cardiac care; transplantation; advanced medicine and surgery – PMH cancer care – TWH neurosciences, musculoskeletal care, community health • Laboratory consolidation 7

The University Health Network 8

The Challenge: Lab Consolidation • • • 3 physical sites 3 cultures 3 missions of the academic institution: – Complex patient care – Education – Research 9

Proposed Solution • • A single core department Electronic support for specimen tracking and handling at 3 sites • Highly subspecialized expertise – Biochemistry - Microbiology – Hematology, Transfusion & Hematopathology – Subspecialty Anatomical Pathology – HLA - Molecular/Genetics 10

Solution: Step 1 LIS implementation goals: • • • • Best-of-breed approach to support high volume complex testing Integration in e-chart with e-orders Specimen tracking and management Integration of lab data from all disciplines into a consolidated report 11

Solution: Step 1 LIS implementations: • • • • • Core Lab automation and middleware CoPath solution for Pathology Transfusion Medicine LIS HLA Histotrack Upgrade existing Shire for molecular lab and interface with CoPath 12

Solution: Step 2 • • Analyze workflow and clinical needs Build core labs and satellites – State-of-the-art space and equipment – Tubes where possible – Rapid response labs where required – On-site accessioning and grossing for surgical pathology with enhanced PA support 13

Informatics: Voice Recognition • Dragon-speech integrated with LIS means instant reporting without the need for dictatyping 14

Solution: Step 3 • • Recruit appropriate medical and technical expertise Create teams of experts who integrate with clinical staff in priority programs: The Pathologist as Medical Consultant “As is your pathology, so goes your clinical care.” Sir William Osler 15

Subspecialty Pathology • • • All cases reported by a pathologist with expertise in the specific subspecialty required Benefits: – – Better quality and faster patient care Fiscal responsibility: 1 pathologist per case – Pathologist satisfaction – enhanced academic excellence Challenges: – Requirement for appropriate staffing in all areas and redundancy 16

Solution: Step 4 • Implement telepathology for intraoperative consultations and frozen sections at non core sites – Phase 1: Robotic microscopy – Phase 2: Digital WSI 17

Historical Data: Telepathology • 1973: Washington DC diagnosis of leukemia via satellite from Brazil • • 1986: Dr. Ronald Weinstein coins name 1990s: Norway implements robotic microscopy to support frozen sections in remote hospitals • 2003 ? Why Not UHN 18

Barriers to Telepathology • • • • • Cost – cheaper than another pathologist!

FDA approval – not applicable in Canada Billing/CPT codes – not applicable Turnaround time - overcome Pathologist issues – learning curve/accuracy – “images are good, but not ready for prime time” 19

Th Philosophical Response In a time of drastic change it is the learners who inherit the future. The learned usually find themselves equipped to live in a world that no longer exists.

Eric Hoffer 20

• • • • Due Diligence Before Going Live Medical Malpractice Insurance Provider – – Canadian Medical Protective Association (CMPA) telepathology will not affect coverage UHN Medical Advisory Committee – SOP presented for approval Health Canada – Therapeutic Products Program – telepathology does not involve “medical devices” (no direct contact between instrument and patient) – no federal approval required Surgeon Education – demonstrating the robotic microscope/slide scanner • essential to get surgeon buy-in!

21

The Robotic System: November 2004-October 2006 22

The Robotic System: November 2004-October 2006 Toronto Western Surgical Pathology Toronto General Telepathology Work Station 23

Whole-Slide Imaging: October 2006-Present 24

Whole-Slide Imaging: System Parameters 25

• • • • • • • UHN Telepathology Protocol System test each morning Pathologist reviews daily O.R. list and communicates game plan for the day to histotechnologist Surgeon defines tissue of interest Histotechnologist contacts Pathologist - specimen description, processing specimen Histotechnologist at TWH scans the slide and calls the Pathologist Pathologist speaks with the surgeon by telephone QA the next day 26

1003 Frozen Sections from 802 Patients (Nov 2004-Sept 2008)

1200 1000 800 600 400

350

200 0 Robotic

653 1003

Total # Frozen Sections

27

• • • Performance: 1003 Cases/4 Years Accuracy – 98% concordance with final pathology – Not a function of technology Deferral rates – – Identical to on-site rates NOT a function of technology • Sometimes you just don’t know for sure • Sampling issues in the frozen section biopsy Turnaround times – Well within 20 minutes required 28

TAT Single Block Frozen Sections

20 18 16 14 12 10 8 6 4 2 0 Robotic

* *

WSI Frozen Section WSI Frozen + Smear Total TAT

Receipt of tissue to report of diagnosis * p < 0.0001

29

Pathologist Interpretation Time

10 9 8 2 1 0 7 6 5 4 3

* 4-fold *

Time/slide (min)

Receipt of image to Report of diagnosis

Robotic WSI Frozen WSI Frozen + Smear

* p < 0.00001

Pathologists tended to go to TWH site for multi-block cases when using the robotic microscope – not so for whole-slide imaging. 30

WSI Pathologist Interpretation Time 38%

40 35 30 25 20 15 10 5 0

32% 30%

% of Cases < 1 1-2

Minutes/slide

> 2

* 70% of cases reported in < 2 minutes after scan is received 31

Failure Mode Analysis • PRE-CASE: – – Network failure Moving the scanner within the surgical pathology lab • • static vs dynamic IP addresses discovered on morning test run.

• MID-CASE: – Minute/pale pieces of tissue that the scanner would not “recognize” – Excess mounting media causing the cover slip to stick to the scanner objective 32

Subspecialty Support for FS 33

Subspecialty Model • How do we get the two liver pathologists to read transplant biopsies and attend all academic meetings?

 Telepathology solution – USCAP 2008 all rush biopsies read on laptops at the meeting 34

Subspecialty Model • How do we get the subspecialty support for weekend coverage?

 Telepathology solution – Summer 2008 all weekend cases read on laptops at the home/cottage etc. 35

Subspecialty Model • How do we get the pituitary expert to read a tough biopsies when she is in Istanbul?

 Telepathology Blackberry solution 36

Ontario-Wide Implementation • Timmins and District Hospital forms an alliance with 9 other hospitals in North East Ontario • • Seeks Laboratory Medical Directorship UHN provides a suitable proposal – Team of subspecialists to support all clinical needs from core in Toronto • Initiation of a new model 37

Ontario NE Cluster Implementation * * * * * * * * * LHIN # 13

422 miles

LHIN # 7 38 Google Maps 2008

Configurations in NE Ontario • • • Small hospitals going to POCT only Medium hospitals on-site labs with POCT Largest hospital with full lab and surgical pathology accessioning, grossing by PA with webcam support – All smaller hospitals send AP specimens to core in Timmins – Complex testing referred to UHN 39

Subspecialty Model • Requires sign-out of all cases by subspecialist – Slides shipped to Toronto by overnight courier • FS review by subspecialist must be available • Ultimately no pathologist on site  Telepathology solution 40

The Ultimate Solution • • $3M grant from government to implement high resolution digital imaging at all sites – All abnormal blood smears, malaria, microbiology gram stains, CSFs, etc • Plan to expand FS service to hospitals that have not had this available CoPath integration of digital imaging in future will alleviate need for any slide transportation 41

Pros and Cons of LIS Integration • • • • Pros Fast E-filed into right location Integration of gross, micro, EM, molecular Remote access and who has (need) access • Cons Images “trapped” and need for export for other purposes 42

Addition of New Clients * * * * * * * * * LHIN # 13

422 miles

LHIN # 7 43 Google Maps 2008

The Future of Pathology?

+ 44

The Future of Pathology + 45

The Future of Pathology The best way to predict the future is to invent it Alan Kay 46

What About Academia?

• • • • Digital education Digital documentation of the biobank – The “Biobank” is the current phraseology for the “Department of Pathology” Scanning and automated analysis of TMAs Scientific Advances – Laboratories must evaluate, develop, and apply the genotypic and phenotypic analyses of specimens 47

Acknowledgements • •

Pathologists

– – – – – – Andrew Evans Runjan Chetty Blaise Clarke Sidney Croul Bayardo Perez-Ordonez Rasmus Kiehl

Surgeons

– Mark Bernstein – Abhijit Guha – – – – – Fred Gentili Chris Wallace Michael Fehlings Mojgan Hodaie Jaime Escallon • •

Histotechnologists

– Suganthi Ilaalagan – – – – – – – – – – – Sofia Aguierre Alfreda Antonio Carsen Chan Gordon Chin Norman Hew-Shue Pam McCartin Aparna Pant Ann Marie Scott Henry Wu

IT Support

Greg Lewis Karen Jaquardt

Vendor Support

Leica Microsystems Quorum Technology/Aperio 48