cap today session: new directions in pathology informatics … · 2014-10-30 · informatics...
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BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 1
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APIII
CAP Today Session: New Directions in Pathology InformaticsCAP Today Session: New Directions in Pathology Informatics::Oncology Informatics as a Tool for Oncology Informatics as a Tool for
Improving Surgical PathologyImproving Surgical PathologyLab Infotech Summit Lab Infotech Summit –– The Venetian, Las Vegas, NV The Venetian, Las Vegas, NV
Wednesday, March 1Wednesday, March 1stst, 2006, 2006
Michael J. Becich, MD PhD ([email protected])Vice Chairman and Professor of Pathology,
Professor of Information Sciences & TelecommunicationsUniversity of Pittsburgh School MedicineDirector, Center for Pathology Informatics
http://path.upmc.edu/cpiDirector, Benedum Oncology Informatics Center (Hillman Cancer Center)
http://www.upci.upmc.edu/internet/benedum/index.htmlCourse Co-Director, APIII or Advancing Practice, Instruction and
Innovation through Informatics (http://apiii.upmc.edu)
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 2
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APIIIDisclosures by MJBDisclosures by MJB•• Corporate Support for API and APIIICorporate Support for API and APIII
–– 650K projected for 2006 650K projected for 2006 [Cerner, [Cerner, ElecktaEleckta/IMPAC/Tamtron, Misys, IBM, /IMPAC/Tamtron, Misys, IBM, GE/Triple G, Apollo, Ardais, Cisco, CAP Today, GE/Triple G, Apollo, Ardais, Cisco, CAP Today, DefiniensDefiniens, De, De--ID Corp, ID Corp, ExcellerisExcelleris, , Amersham, Applied Imaging, Chromavision, Nikon, Olympus, DakoCytAmersham, Applied Imaging, Chromavision, Nikon, Olympus, DakoCytomation, omation, Ikon, General Data, Trestle, SCC Soft, Sysmex, Neural Ware, SNOMIkon, General Data, Trestle, SCC Soft, Sysmex, Neural Ware, SNOMED, Pathology ED, Pathology Outlines.comOutlines.com, PSA, Thermo Shandon and others], PSA, Thermo Shandon and others]
•• Corporate Sponsored Research AgreementsCorporate Sponsored Research Agreements–– 1.5M in 2006 1.5M in 2006 [[AffymentrixAffymentrix, Amgen, Cerner, De, Amgen, Cerner, De--ID Corp, IBM, Intel, Nikon, ID Corp, IBM, Intel, Nikon,
Clinical Data (MJB founder), Clinical Data (MJB founder), PathWorksPathWorks, , StoneboundStonebound, Trestle (MJB founder), , Trestle (MJB founder), VeridexVeridex]]
•• Startup/Public Companies (Startup/Public Companies (Founder Equity Founder Equity -- MJBMJB):):–– Trestle Holdings, Inc. Trestle Holdings, Inc. (NASDAQ: TLHO; (NASDAQ: TLHO; http://www.trestlecorp.comhttp://www.trestlecorp.com))
»» Provider of high speed/volume microscopic imaging/telepathology Provider of high speed/volume microscopic imaging/telepathology systemssystems»» VentureVenture--MAVF, Birchmere & Cape Andover.MAVF, Birchmere & Cape Andover.»» Ultrarapid digitization: Gb data transfers, terabyte storage andUltrarapid digitization: Gb data transfers, terabyte storage and roboticsrobotics
–– Clinical Data Clinical Data (NASDAQ:CLDA, formerly Icoria, Paradigm Genetics, (NASDAQ:CLDA, formerly Icoria, Paradigm Genetics, TissueInformatics, merged 12/31/05, TissueInformatics, merged 12/31/05, http://www.clda.comhttp://www.clda.com))
»» Becoming a leader in molecular testing and pharmacogenomicsBecoming a leader in molecular testing and pharmacogenomics»» Provides clinical chemistry and hematology equipment and reagentProvides clinical chemistry and hematology equipment and reagentss»» Recent acquisitions include Genaissance Pharma (pharmacogenomicsRecent acquisitions include Genaissance Pharma (pharmacogenomics) and ) and
Lark Technologies (CRO) and Icoria (systems biology, Lark Technologies (CRO) and Icoria (systems biology, metabolomicsmetabolomics))
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 3
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APIIIOutlineOutline
•• Introduction to Oncology InformaticsIntroduction to Oncology Informatics–– Organizational and Strategic GoalsOrganizational and Strategic Goals
•• How Oncology Informatics can be leveraged in Surgical How Oncology Informatics can be leveraged in Surgical Pathology?Pathology?
•• Why Pathology Informatics has lagged and how we can Why Pathology Informatics has lagged and how we can fix it.fix it.–– Lack of focus on Specialty Labs, critical to Personalized MediciLack of focus on Specialty Labs, critical to Personalized Medicinene–– Funding issuesFunding issues–– Training Program issuesTraining Program issues
•• Cancer Biomedical Informatics Grid Initiative (caBIG Cancer Biomedical Informatics Grid Initiative (caBIG ––http://cabig.nci.nih.govhttp://cabig.nci.nih.gov–– Example of how to transform Oncology Informatics Example of how to transform Oncology Informatics –– NIH RoadmapNIH Roadmap
•• Conclusions Conclusions
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 4
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APIIICancer Informatics Cancer Informatics Services at U PittServices at U Pitt
• Software Solutions Supported and Deployed:– Clinical Trials Software – Developed at U Pitt = Clinical Trials Mgmt App
» Deployed at Hillman Cancer Center, UPMC Presbyterian/Shadyside» Deployments underway at regional cancer centers and physician offices» Deployments planned at Magee Women’s, Children’s Hospital
– Cancer Registry Software – MRS system of IMPAC (formerly ImPath)» Deployed in 12/18 hospitals (homogeneous consolidation); Outpatient rollout
– Tissue Banking Info System (URL behind firewall) at 8 cancer centers– Organ Specific Databases (URL behind firewall) – identify tissue samples– Gene Expression Databases (public, see below) – at U Pitt only– Support of Clinical Systems:
» LIMS (Cerner, Affy and Amersham), Cerner CoPath (Anatomic Path), Misys (Clinical Path), Cerner (Electronic Medical Record)
– Web Tools (including extensive web casting): » UPMC Cancer Centers Website (see http://www.upmccancercenters.com)» UPCI Website (see http://www.upci.upmc.edu)» Bioinformatics (see http://bioinformatics.upmc.edu/index.html)
• Honest Broker for Tissue, Data and Outcomes Research (handout)– Certified Honest Brokers include:
» 7 Tissue Bankers (Pathology Assistants and Support Staff), 5 Cancer Registrars & 3 Outcomes Researchers–Coordinator/Data Mgrs
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 5
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APIIIComponent Technology Component Technology ––
Pathology & Oncology InformaticsPathology & Oncology Informatics
•• Pathology InformaticsPathology Informatics•• Anatomic PathologyAnatomic Pathology•• Clinical PathologyClinical Pathology•• Hematopathology & Hematopathology &
Molecular DiagnosticsMolecular Diagnostics•• LIMS for Genomics and LIMS for Genomics and
ProteomicsProteomics•• Tissue BankingTissue Banking•• TelepathologyTelepathology•• Web Site SupportWeb Site Support
•• Oncology InformaticsOncology Informatics•• Cancer RegistryCancer Registry•• Clinical TrialsClinical Trials•• Organ Specific Organ Specific
Program SupportProgram Support••Prostate, Prostate,
Melanoma, etc.. Melanoma, etc.. •• Telemedicine (for Telemedicine (for
oncology)oncology)•• Web Site SupportWeb Site Support•• EE--Health InitiativesHealth Initiatives
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 6
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APIIIStrategic Approach Strategic Approach ––
Why Oncology Informatics?Why Oncology Informatics?• Why Oncology Informatics as the next step
forward?– Higher profile in the clinical arena (70/70/70 rule)– No developed systems/people to support Onc Info– Unlike Path, Onc Informatics has significant $ support:
» Onc svc lines at most major med ctrs – very profitable, growing» NCI has launched several strategic IT initiatives:
• NCICB – NCI Center for Bioinfo (5 FTEs 5 years ago now >80)• caBIG – Cancer Biomed Info Grid Initiative – $100M (with NCICB)• NBN – Ntnl Biospecimen Network (NCI backed) – $100M
» Cancer Centers Program is highly supported by new director• Cancer Center Support Grants represent 20% of NCI funding base
» Part of the NIH Roadmap – Informatics keykey to research/clinical success
» Pathology needs to embrace this and move to “personalized” testing to support Oncology
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 7
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APIIISupport for Cancer Support for Cancer
Informatics ServicesInformatics ServicesOverall Annual Budget
Dollars PercentCCSG Request $224,421 7%Grants $2,375,000 65%Foundations $350,000 11%Institution $578,000 17%Total Facility Budget $3,527,421 100%
For CY 2005:148 PIs used Clinical Trials Tools,
89 used Tissue Bank Info Svcs, 371 used Research Registry Info Svcs, 371 used the Honest Broker Services
161 Cancer Informatics server support.Heaviest Users:
Molecular Therapeutics/Drug DiscoveryProstate Urologic Cancer Program
Biologic Therapeutics ProgramLung/Head & Neck SPORE Program
Proposed Budget for Cancer Informatics Service
CCSG7%
Dept Pathol.7%
UPCI11%
NCI Grants40%
Other Grants24%
Foundations11%
Cancer Informatics Service UtilizationBy UPCI Program
PUCP15%
BMOP3%
MVPl2%
MCOP6%
LTMP6%
IP5%
HNCP9%
BTP4%
CEPCP8%
MT/DD18% BThP
15%
Non-UPCI9%
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 8
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APIIIOutlineOutline
•• Introduction to Oncology InformaticsIntroduction to Oncology Informatics–– Organizational and Strategic GoalsOrganizational and Strategic Goals
•• How Oncology Informatics can be leveraged in Surgical How Oncology Informatics can be leveraged in Surgical Pathology?Pathology?
•• Why Pathology Informatics has lagged and how we can Why Pathology Informatics has lagged and how we can fix it.fix it.–– Lack of focus on Specialty Labs, critical to Personalized MediciLack of focus on Specialty Labs, critical to Personalized Medicinene–– Funding issuesFunding issues–– Training Program issuesTraining Program issues
•• Cancer Biomedical Informatics Grid Initiative (caBIG Cancer Biomedical Informatics Grid Initiative (caBIG ––http://cabig.nci.nih.govhttp://cabig.nci.nih.gov–– Example of how to transform Oncology Informatics Example of how to transform Oncology Informatics –– NIH RoadmapNIH Roadmap
•• Conclusions Conclusions
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 9
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APIIIMarket Validation of Market Validation of
Oncology & Pathology ValueOncology & Pathology Value• Merger and Acquisition activity in 2000’s – Validation?
– AP-, CP-Lab Information Systems (LIS) and Oncology Systems» Elekta’s purchase of IMPAC’s after their purchase of Tamtron (AP-LIS)
& MRS Registry (CR)» LabCorp’s purchase of Dianon/Urocor (AP and Clinical Trials)» Misys’s (CIS) purchase of Sunquest (CP-LIS)» Cerner’s (CIS) purchase of Dynamic Healthcare Tech. (APLIS-CoPath)» Clinical Data’s purchase of Icoria, Genaissance Pharma and Lark (CRO)» Varian’s purchase of Clinical Trials Software Company» GE’s purchase of Triple G» Siemens purchase of Stentor
• Biotech Startups – More Validation through VC & Mergers– Icoria merger with TissueInformatics – Systems Biology approach
combining Genomics with Tissue Based Image Analysis– LifeSpan Biosciences – Strategic Partnership with NEC (Japan) = CRO for
tissue based discovery with high end imaging strategy– Ardais – >$20M VC – Tissue Banking for Pharma and Biotech– Aureon – >$20M VC – ‘Gold Standard’ Molecular AP Testing & Database– Pathogenomics – >$20M VC – Genomic Discovery on Tissue Bank– PathWorks - $10M – Genomic Discovery based on Cancer Signatures
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 10
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APIII
Oncology Informatics (3 faculty; JLW, VM & AT; and 20 staff)
17 of 20 hospital on one Cancer Registry (MRS, Eleckta) Number of new index cancer patients per year: 10,000+
Clinical Trials Information System (developed by Oncology Informatics); being rolled out to enterpriseGenomics/Proteomics LIMS–GLP developmental labs
Genologics – making significant progress with ProteomicsNow funded by Onc Info due to funding pressure in Path Info
Specialized Cellular Therapies & Personalized TherapiesStem CellCellular Products (Immunotherapy)Immune Monitoring of Cellular TherapiesAll implemented now using Cerner’s PathNet as a LIMSSupported by Oncology Funding but managed by Pathology
Coagulation & Transfusion Medicine is an Opportunity!!!
Oncology Informatics and Relevance Oncology Informatics and Relevance to Personalized Testing in Pathologyto Personalized Testing in Pathology
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 11
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APIIIOutlineOutline•• Introduction to Oncology InformaticsIntroduction to Oncology Informatics
–– Organizational and Strategic GoalsOrganizational and Strategic Goals
•• How Oncology Informatics can be leveraged in Surgical How Oncology Informatics can be leveraged in Surgical Pathology?Pathology?
•• Why Pathology Informatics has lagged and how we can Why Pathology Informatics has lagged and how we can fix it.fix it.–– Lack of focus on Specialty Labs, critical to Personalized MediciLack of focus on Specialty Labs, critical to Personalized Medicinene–– Funding issuesFunding issues–– Training Program issuesTraining Program issues
•• Cancer Biomedical Informatics Grid Initiative (caBIG Cancer Biomedical Informatics Grid Initiative (caBIG ––http://cabig.nci.nih.govhttp://cabig.nci.nih.gov–– Example of how to transform Oncology Informatics Example of how to transform Oncology Informatics –– NIH RoadmapNIH Roadmap
•• Conclusions Conclusions
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 12
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APIIIFrom John Gilbertson, MDFrom John Gilbertson, MD
Now at Case Western UniversityNow at Case Western University
•• ““Information relationships “ in Information relationships “ in medicine are in silent upheaval. medicine are in silent upheaval. Ubiquitous access to information is Ubiquitous access to information is changing the fundamental changing the fundamental relationship between the physician relationship between the physician and patient.and patient.
•• This will impact pathology This will impact pathology informatics.informatics.
•• The way pathology, and its academic The way pathology, and its academic departments, position themselves departments, position themselves now in this emerging infrastructure now in this emerging infrastructure will determine the strength of our will determine the strength of our field twenty years from today.field twenty years from today.
•• This can be one of the ways we This can be one of the ways we reposition ourselves in pathology reposition ourselves in pathology informatics.informatics.
InfoCentric Networks InfoCentric Networks & Personalized Medicine& Personalized Medicine
InformationInformation
PatientPatientClinicianClinician
InformationInformation
PatientPatient
ClinicianClinician
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 13
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APIIIElectronic Medical Repositories:Electronic Medical Repositories:
The Value of Warehoused Lab DataThe Value of Warehoused Lab Data• Pathology is uniquely situated in medicine and provides
objective and quantifiable data via electronic repositories
• Leverage the position we have (70/70 Rule) into leadership role in enterprise clinical datamining and datawarehousing
• As we enter the Post-Genome Era the time spent on actual testing will decrease and the amount spent on data analysis will increase
• This will place tremendous value on warehousing data and being able to efficiently datamine archives of Pathology data.
• Focus on changing system architectures and focus on reporting correlative information not individual values
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 14
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APIII
•• An integrated laboratory view of a An integrated laboratory view of a patient.patient.–– Disease BasedDisease Based–– AP, CP & Imaging information.AP, CP & Imaging information.–– All Path Data & Disease SpecificAll Path Data & Disease Specific
•• Knowledge BasesKnowledge Bases–– Cancer Registry and Outcomes Cancer Registry and Outcomes
Data Warehouse communicated to Data Warehouse communicated to patients and clinicians.patients and clinicians.
•• Integrate pathology data and links to Integrate pathology data and links to appropriate Patient/Physician appropriate Patient/Physician resourcesresources depending on user.depending on user.
•• Report format based on user type Report format based on user type (patient, physician or researcher).(patient, physician or researcher).
•• Provide identified and deProvide identified and de--identified identified access to system.access to system.
Multimedia,Synoptics
LIS (AP/CP)
Cancer Registryand Outcomes
Integration EngineData Customizing Engine
WWW Server
System Wide Access Rules
Network
BrowserResourcesResources
Oncology Informatics and Oncology Informatics and SP Reporting: Future ReportsSP Reporting: Future Reports
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 15
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APIIIThe AP/CP Integration IssueThe AP/CP Integration Issue•• Where does “The New Pathology” lead to:Where does “The New Pathology” lead to:
–– Look at trends over the few four decades:Look at trends over the few four decades:»» Increasingly specialty laboratories reporting needs are not Increasingly specialty laboratories reporting needs are not
being met:being met:•• Tissue TypingTissue Typing•• HematopathologyHematopathology•• CytogeneticsCytogenetics•• MicrobiologyMicrobiology•• ImmunopathologyImmunopathology•• Molecular PathologyMolecular Pathology
»» Harder to distinguish which are CP (quantitative/numeric Harder to distinguish which are CP (quantitative/numeric result driven) and which are APresult driven) and which are AP--like (qualitative/text driven)like (qualitative/text driven)
»» Vendors have largely not engineered this into their solutionsVendors have largely not engineered this into their solutions
•• Problem is that APProblem is that AP-- &CP&CP--LIS are not integrated.LIS are not integrated.•• This is a basic flaw in pathology.This is a basic flaw in pathology.
Fig. 1 - Increase in Specialty Labs in Pathology
0
2
4
6
8
10
12
14
16
18
# o
f La
bs
CP 7 9 10 12
AP 7 8 12 16
AP/CP 2 4 6 9
1960 1970 1980 1990
From Gilbertson and Becich, Adv Lab Mgr, 1998From Gilbertson and Becich, Adv Lab Mgr, 1998
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 16
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APIIIIntegration of Anatomic and Integration of Anatomic and
Clinical Pathology InformaticsClinical Pathology Informatics
Lab InfoTech Summit, Las Vegas Lab InfoTech Summit, Las Vegas Wednesday, March 2Wednesday, March 2ndnd, 2005, 2005
NOTE: Archived on Lab InfoTech Summit Website (http://www.labinfotech.org) at:
https://www.labinfotech.org/LIS2006/Presentations2005/Becich_las_Vegas_2005.htm
Michael J. Becich, MD PhD ([email protected])Vice Chairman of Pathology,
Professor of Pathology, Info Sciences & TelecommunicationsUniversity of Pittsburgh School MedicineDirector, Center for Pathology Informatics
http://path.upmc.edu/cpiCourse Co-Director, Advancing Practice, Instruction and
Innovation through Informatics (http://apiii.upmc.edu)Ad Hoc Councilor, Association for Pathology Informatics
http://www.pathologyinformatics.org
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 17
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APIII
Pathology Informatics (10 faculty; GB, MB, RC, RD, DGx2, DJ, SR,YY & 1 TBN; 85 staff; 3 open positions-CP,AP,R&D)
20 hospitals – one anatomic laboratory information system (LIS = Cerner CoPathPlus and PathNet LIMS)16 of 20 hospitals - one clinical pathology LIS (= Misys)Implementing Molecular Diagnostics LIS in 2006 – Helix from CernerOne tissue banking plan (5 major tissue banks) and now linked to our Organ Specific Database program
Critical Need – Specialty Lab Informatics Support to the vision of Personalize Medicine – happening in Oncology
Molecular DiagnosticsCytogeneticsHematopathologyGenomics and Proteomics
Pathology Informatics Pathology Informatics and Personalized Medicineand Personalized Medicine
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 18
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APIII
Pathology Informatics has many issues to address:Marginalization from Hospital IT investments due to EMR and “one system for all domains” strategyReimbursement pressure continues for PathologySystematic lack of investment by LIS companiesLack of federal funding for Pathology Informatics (at least compared to Oncology Informatics)Lack of significant investment in training (at all levels)
With LIS systems as a strategic IT assetWith prioritizing pathology informatics training (no funding to support)
Critical Need – National Organizations must work together to address this – AACC, AABB, CAP, ASCP and USCAP
Association for Pathology Informatics (API) – see http://www.pathologyinformatics.org is making progress but needs your help. Please support API!!!
Pathology Informatics Pathology Informatics and Funding/Priority Issuesand Funding/Priority Issues
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 19
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APIIIAssociation for Pathology Association for Pathology
Informatics (API)Informatics (API)http://www.pathologyinformatics.orghttp://www.pathologyinformatics.org
…to advance the field of pathology informatics as an academic and a clinical subspecialty of pathology.
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 20
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APIIIAPI Membership Benefits to API Membership Benefits to
IndividualsIndividuals• Recognition as member of Pathology Informatics
professional discipline• Discounts at APIII, Lab InfoTech meetings
–– Attending one meeting alone offsets cost of duesAttending one meeting alone offsets cost of dues• Members-only Listserv
–– Managed at ASIP (Managed at ASIP (advertisementadvertisement--freefree))• Peer networking and education (real time)• Professional development opportunities• Access to open source tools:
–– TMA XML data exchange standardTMA XML data exchange standard–– Comprehensive abbreviations repositoryComprehensive abbreviations repository–– Digital imaging standards efforts for pathologyDigital imaging standards efforts for pathology
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 21
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APIII
• Why Pathology Informatics has a lot to offer Oncology Informatics:– Advancing Practice, Instruction & Innovation through Informatics (APIII)
» National Meeting focused on Biomedical Informatics (emphasis shifted to oncology informatics and bioinformatics from pathology informatics)
» Over 2500 attendees to date over 8 years» Over 375 trainees to date over 8 years via CAP Foundation Program» Includes vendor community critical to long term support and R&D» Relationships with American Medical Informatics Association (AMIA), College of
American Pathologist (CAP), in discussions with American Association for Cancer Institutes (AACI)
– National Member Organizations (Hilliard)» Association for Pathology Informatics (API – see http://apiii.upmc.edu)» American Society for Investigative Pathology (ASIP)» American Telemedicine Society Special Interest Group in Telepathology
– Training program coordinated centrally (Harrison)» APIII Travel Awardees – over 350 and CAP Technology in Training Informatics
Awardees – 6 » MS and PhD Students – 10» NLM Biomedical Informatics Fellows – 8 and Informatics Fellows - 13» Bioinformatics Trainees – 6
– Web Properties – over 3M hits per month from over 350K unique visitors
Leveraging Our Hard Work in Leveraging Our Hard Work in Pathology InformaticsPathology Informatics
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 22
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APIII
API Focus SessionAPI Focus SessionOncology Informatics:Oncology Informatics:
Organizational and Strategic GoalsOrganizational and Strategic GoalsLab Infotech Summit Lab Infotech Summit –– The Venetian, Las Vegas, NV The Venetian, Las Vegas, NV
Friday, March 12Friday, March 12thth, 2004, 2004NOTE: Archived on Lab InfoTech Summit Website
(http://www.labinfotech.org) at:https://www.labinfotech.org/LIS2006/Presentations2004/LIS_2004_becich_lecture.htm
Michael J. Becich, MD PhD ([email protected])Vice Chairman and Professor of Pathology,
Professor of Information Sciences & TelecommunicationsUniversity of Pittsburgh School MedicineDirector, Center for Pathology Informatics
http://path.upmc.edu/cpiDirector, Benedum Oncology Informatics Center (Hillman Cancer Center)
http://www.upci.upmc.edu/internet/benedum/index.htmlCourse Co-Director, APIII or Advancing Practice, Instruction and
Innovation through Informatics (http://apiii.upmc.edu)
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 23
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APIIIOutlineOutline•• Introduction to Oncology InformaticsIntroduction to Oncology Informatics
–– Organizational and Strategic GoalsOrganizational and Strategic Goals
•• How Oncology Informatics can be leveraged in Surgical How Oncology Informatics can be leveraged in Surgical Pathology?Pathology?
•• Why Pathology Informatics has lagged and how we can Why Pathology Informatics has lagged and how we can fix it.fix it.–– Lack of focus on Specialty Labs, critical to Personalized MediciLack of focus on Specialty Labs, critical to Personalized Medicinene–– Funding issuesFunding issues–– Training Program issuesTraining Program issues
•• Cancer Biomedical Informatics Grid Initiative (caBIG Cancer Biomedical Informatics Grid Initiative (caBIG ––http://cabig.nci.nih.govhttp://cabig.nci.nih.gov–– Example of how to transform Oncology Informatics Example of how to transform Oncology Informatics –– NIH RoadmapNIH Roadmap
•• Conclusions Conclusions
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 24
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APIIICancer Center Needs Cancer Center Needs
Resulted in the caBIG “Grid”Resulted in the caBIG “Grid”
Cross Cutting WORKSPACE
Architecture
Vocabularies & Common Data Elements
Cross Cutting WORKSPACE
Developer
Developer
Adopter
Developer
Developer
Adopter
Developer
Developer
Developer
Developer
Developer
WorkspaceWorking Group
WorkspaceWorking Group
WorkspaceWorking Group
Strategic Level Working Groups
Domain WORKSPACE
Clinical Trial Mgmt Systems Integrative Cancer Research Tissue Banks & Pathology Tools
WorkspaceWorking Group
WorkspaceWorking Group
Adopter
Developer
Developer
Adopter
Developer
Developer
Adopter
Domain WORKSPACE
Domain WORKSPACE
caBIG Coordination and Oversight http://http://caBIG.nci.nih.govcaBIG.nci.nih.gov
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 25
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APIIIThe Big The Big Question(sQuestion(s):):
WHERE IS PATHOLOGY IN ALL OF THIS?WHERE IS PATHOLOGY IN ALL OF THIS?
WHY IS THERE NO SUPPORT FOR THIS KIND OF WHY IS THERE NO SUPPORT FOR THIS KIND OF MAJOR UNDERTAKING FOR PATHOLOGY?MAJOR UNDERTAKING FOR PATHOLOGY?
The bottom line:The bottom line:WE MUST PARTNER WITH THESE BIG SCIENCE WE MUST PARTNER WITH THESE BIG SCIENCE
INITIATIVES OR WE WILL BE FURTHER INITIATIVES OR WE WILL BE FURTHER MARGINALIZED IN THE MARCH TO MARGINALIZED IN THE MARCH TO PERSONALIZED MEDICINE. PERSONALIZED MEDICINE.
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 26
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APIIIOutlineOutline
•• Introduction to Oncology InformaticsIntroduction to Oncology Informatics–– Organizational and Strategic GoalsOrganizational and Strategic Goals
•• How Oncology Informatics can be leveraged in Surgical How Oncology Informatics can be leveraged in Surgical Pathology?Pathology?
•• Why Pathology Informatics has lagged and how we can Why Pathology Informatics has lagged and how we can fix it.fix it.–– Lack of focus on Specialty Labs, critical to Personalized MediciLack of focus on Specialty Labs, critical to Personalized Medicinene–– Funding issuesFunding issues–– Training Program issuesTraining Program issues
•• Cancer Biomedical Informatics Grid Initiative (caBIG Cancer Biomedical Informatics Grid Initiative (caBIG ––http://cabig.nci.nih.govhttp://cabig.nci.nih.gov–– Example of how to transform Oncology Informatics Example of how to transform Oncology Informatics –– NIH RoadmapNIH Roadmap
•• Conclusions Conclusions
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 27
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APIIIThe Value of Oncology to Pathology The Value of Oncology to Pathology Informatics and Pathology PracticeInformatics and Pathology Practice
Digital Pathology& Telepath
LIMS/GLP forGenomics
& Proteomics
Cancer Outcomes &
Clinical Trials Informatics
TissueBanking
Specialty Lab Support for
Personalized Medicine
Anatomic Pathologic
• Pathology in partnership with Oncology has a great future.
• The importance of supporting Specialized Labs as distinct from AP and CP.
• Too many pathologists consider themselves “experts who look at glass slides and test values” not “experts in analysis of tissue/serum in disease and customized theranostics”. Need to change this!!!
• What could we accomplish if we could apply integrated data warehousing methods and standardized data capture to Pathology?
Clinical Pathology
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 28
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APIIIHistory from APIII History from APIII -- 20022002
http://apiii.upmc.edu/archive/2002/Path-in-Onc-Info-APIII2002-MBv3-091802x.htm
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 29
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APIIIAPIII On Line ArchiveAPIII On Line Archive
http://apiii.upmc.edu/live/index.html
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 30
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APIII
Cerner CoPath AP LISCerner CoPath AP LISBill GrossBill GrossAnthony PiccoliAnthony PiccoliFrank LososFrank LososRick NestlerRick NestlerLisa DevineLisa DevineSupport staff of 12 (18 sites)Support staff of 12 (18 sites)
Misys FlexiLab CP LISMisys FlexiLab CP LISGary Blank, PhDGary Blank, PhDJim Harrison, MD PhDJim Harrison, MD PhDSupport Staff of 8 (12 sites)Support Staff of 8 (12 sites)
Cerner PathNet LIMSCerner PathNet LIMSMike SendekMike SendekJeff Jeff SchulloSchulloSupport staff of 3 (5 labs)Support staff of 3 (5 labs)
Specialty Labs Project MgmtSpecialty Labs Project MgmtMary MuellerMary Mueller
Benedum Oncology Informatics CenterBenedum Oncology Informatics Centerand Center for Pathology Informaticsand Center for Pathology Informatics
Programming SupportProgramming SupportBecky BoesBecky BoesTom HarperTom HarperJohn MilnesJohn MilnesKelli RichterKelli Richter
Web ServicesWeb ServicesValerie Monaco, PhD, MS HCIValerie Monaco, PhD, MS HCIAab ArnoldAab ArnoldAdrienne WeissAdrienne Weiss
Network and Server ServicesNetwork and Server ServicesGary Burdelski, Gary Burdelski, Ryan MitchellRyan Mitchell
Help Desk and Application SupportHelp Desk and Application SupportChuck SusaninChuck SusaninJoel Young (Mac Support)Joel Young (Mac Support)Mark Mark MichalskiMichalski (PC support)(PC support)Support staff of 8Support staff of 8
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 31
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Clinical Support
& TrainingPrograms
Health Services/OutcomesResearch
Pathology& Oncology EnterpriseResearch
& TeachingResources
TranslationalResearch
National Teaching
Organizations
Centers for Pathology and Oncology Informatics
Ctrs for Pathology (COE) and Oncology InformaticsMike Becich, MD PhD
Center of Excellence (COE) Director
Clinical Pathology Informatics& Training Programs
Associate Director, To Be NamedGary Blank, PhD
Anatomic Path InformaticsAnil Parwani, MD PhD
Bill Gross, Systems Manager
Oncology InformaticsAssociate Director, To Be Named
Clinical Trials SystemsUPMC Cancer Centers Initiative
Cancer RegistrySharon Winters, MS; Director
12 SYS PUH Registraars10 Community Hospital Registraars
Bioinformatics ResearchDirector R&D, To Be NamedJames Lyons-Weiler, PhD
Uma Chandran, MS
Outcomes Research, COEStephen Raab, MD, COE Director
Dana Gryzbicki, MD PhDDilip Gupta, MD
Imaging ResearchDrazen Jukic, Md PhD; Director
Human Computer Interactions/Web InitiativesValerie Monaco, PhD; Director
http://www.upmccancercenters.comhttp://www.upci.upmc.edu
Intelligent TutorsRebecca Crowley, MD; Lead
National Member OrganizationsWendy Hilliard; Coordinator
APIII-Adv Path Info Imaging & InternetAPI-Association for Path Informatics
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 32
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•• Patel AA, KajdacsyPatel AA, Kajdacsy--Ball A, Berman JJ, Bosland M, Datta MW, Dhir R, Gilbertson J, MeBall A, Berman JJ, Bosland M, Datta MW, Dhir R, Gilbertson J, Melamed J, Orenstein J, Tai KF, lamed J, Orenstein J, Tai KF, Becich MJBecich MJ. The development of common data elements for a multi. The development of common data elements for a multi--institute prostate cancer tissue bank: The institute prostate cancer tissue bank: The Cooperative Prostate Cancer Tissue Resource (CPCTR) experience. Cooperative Prostate Cancer Tissue Resource (CPCTR) experience. BMC Cancer. 2005 Aug 21;5(1):108.BMC Cancer. 2005 Aug 21;5(1):108.
•• Becich MJBecich MJ, Gilbertson JR, Gupta D, Grzybicki DM and Raab, SS. Patient Sa, Gilbertson JR, Gupta D, Grzybicki DM and Raab, SS. Patient Safety and Healthcare Research: The fety and Healthcare Research: The Critical Role of Path Informatics in Error Reduction and QualityCritical Role of Path Informatics in Error Reduction and Quality Initiatives. Clin Lab Med. 2004 Dec;24(4):913Initiatives. Clin Lab Med. 2004 Dec;24(4):913--43.43.
•• Berman JJ, Datta M, KajdacsyBerman JJ, Datta M, Kajdacsy--Balla A, Melamed J, Orenstein J, Dobbin K, Patel A, Dhir R, Balla A, Melamed J, Orenstein J, Dobbin K, Patel A, Dhir R, Becich MJBecich MJ. The tissue . The tissue microarray data exchange specification: implementation by the Comicroarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource. operative Prostate Cancer Tissue Resource. BMC Bioinformatics. 2004 Feb 27;5(1):19. BMC Bioinformatics. 2004 Feb 27;5(1):19.
•• Melamed J, Datta MW, Melamed J, Datta MW, Becich MJBecich MJ, Orenstein JM, Dhir R, Silver S, Fidelia, Orenstein JM, Dhir R, Silver S, Fidelia--Lambert M, KadjacsyLambert M, Kadjacsy--Balla A, Macias V, Balla A, Macias V, Patel A, Walden PD, Bosland MC, Berman JJ. The cooperative prosPatel A, Walden PD, Bosland MC, Berman JJ. The cooperative prostate cancer tissue resource: a specimen and tate cancer tissue resource: a specimen and data resource for cancer researchers. Clin Cancer Res. 2004 Juldata resource for cancer researchers. Clin Cancer Res. 2004 Jul 15;10(14):461415;10(14):4614--21.21.
•• LyonsLyons--Weiler J, Patel SV, Weiler J, Patel SV, Becich MJBecich MJ, Godfrey T. Tests for finding complex patterns of differential, Godfrey T. Tests for finding complex patterns of differential expression in expression in cancers: towards individualized medicine. BMC Bioinformatics 2cancers: towards individualized medicine. BMC Bioinformatics 2004, 5:110004, 5:110--116.116.
•• Mitchell KJ, Mitchell KJ, Becich MJBecich MJ, Berman JJ, Chapman WW, Gilbertson J, Gupta D, Harrison J, Lego, Berman JJ, Chapman WW, Gilbertson J, Gupta D, Harrison J, Legowski E, and Crowley RS wski E, and Crowley RS Implementation and Evaluation of a Negation Tagger in a PipelineImplementation and Evaluation of a Negation Tagger in a Pipeline--based System for Information Extraction from based System for Information Extraction from Pathology Reports Proc Med Info. 2004:663Pathology Reports Proc Med Info. 2004:663--7.7.
•• Li S, Li S, Becich MJBecich MJ, Gilbertson J. Microarray Data Mining Using Gene Ontology. Pr, Gilbertson J. Microarray Data Mining Using Gene Ontology. Proc Med Info. 2004:778oc Med Info. 2004:778--82.82.•• Gilbertson JR, Gupta R, Nie Y, Patel AA, Gilbertson JR, Gupta R, Nie Y, Patel AA, Becich MJBecich MJ. Automated Clinical Annotation of Tissue Bank Specimens. . Automated Clinical Annotation of Tissue Bank Specimens.
Proc MedInfo, 2004: 607Proc MedInfo, 2004: 607--610.610.•• Yagi Y, Ahmed I, Gross W, Yagi Y, Ahmed I, Gross W, Becich MJ,Becich MJ, Demetris AJ, Wells A, Wiley CA, Michalopoulos GK, Yousem SA, BaDemetris AJ, Wells A, Wiley CA, Michalopoulos GK, Yousem SA, Barnes B, rnes B,
Gilbertson JR. Gilbertson JR. WebcastingWebcasting pathology department conferences in a geographically distributepathology department conferences in a geographically distributed medical center. d medical center. Hum Pathol. 2004 Jul;35(7):790Hum Pathol. 2004 Jul;35(7):790--7. 7.
•• Crowley RS, Gadd CS, Naus G, Crowley RS, Gadd CS, Naus G, Becich MBecich M, Lowe HJ. Defining the role of anatomic pathology images in the, Lowe HJ. Defining the role of anatomic pathology images in themultimedia electronic medical recordmultimedia electronic medical record----a preliminary report. Proc AMIA Symp 2000:161a preliminary report. Proc AMIA Symp 2000:161--5. 5.
•• Landman A, Yagi Y, Gilbertson J, Dawson R, Marchevsky A, Landman A, Yagi Y, Gilbertson J, Dawson R, Marchevsky A, Becich MJ.Becich MJ. Prototype webPrototype web--based continuing medical based continuing medical education using FlashPix images. Proc AMIA Symp. 2000; 462education using FlashPix images. Proc AMIA Symp. 2000; 462--6.6.
•• Becich, M.J..Becich, M.J.. Information management: moving from test results to clinical inInformation management: moving from test results to clinical information. Clin formation. Clin LeadershLeadersh ManagManag Rev. Rev. 2000 Nov2000 Nov--Dec;14(6):296Dec;14(6):296--300.300.
•• Becich, M.JBecich, M.J. The role of the Pathologist as tissue refiner & data . The role of the Pathologist as tissue refiner & data miner:Theminer:The impact of functional genomics on the impact of functional genomics on the modern path laboratory & the critical role of Pathology Informatmodern path laboratory & the critical role of Pathology Informatics & Bioinformatics Molec ics & Bioinformatics Molec DiagDiag. 5(4):287. 5(4):287--299, 2000299, 2000
Recent Publications by Our Team Recent Publications by Our Team ––NOTE: Please eNOTE: Please e--mail me at mail me at [email protected]@pitt.edu
if you want PDFsif you want PDFs
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 33
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APIIIInvitation to APIII 2006 Invitation to APIII 2006
August 16August 16--1818thth, Vancouver, BC, Vancouver, BC
http://apiii.upmc.edu
BenedumBenedum Oncology Informatics Center / Center for Pathology InformaticsOncology Informatics Center / Center for Pathology InformaticsSlide 34
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APIII
End of Talk End of Talk –– ee--mail me at mail me at [email protected]@pitt.edu if you have if you have questions/clarifications not questions/clarifications not covered in the discussion.covered in the discussion.
NOTE: Please eNOTE: Please e--mail me if you want PDFs of mail me if you want PDFs of articles or presentation.articles or presentation.
Thank you for the invitation to participate in the Lab InfoTech Summit.