The Development of National Electronic Pathology / Laboratory Networks
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foundation.cap.org v. #
The Development of National Electronic Pathology / Laboratory NetworksA Framework for the Diagnostic Collaborative NetworkRobert Atlas, President & CEO, ATLAS Medical April 16, 2011
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© 2011 Atlas Development Corporation. All rights reserved.
Agenda
• The Challenge• The Opportunity• Evolution of the Collaborative Network• Characteristics and Benefits of an
“Open” Network • Technology Components and Potential
Workflow Paradigms• Questions for Future Consideration
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The Challenge
• Increasing complexity of diagnostic disciplinesoMulti-modal
−Molecular / Imaging / Digital Pathology
oHighly personalized−Patient history including genome
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The Challenge
oAggregation of disparate data elements from multiple sources−Test results, interpretations−PHR (genomic map)−Knowledge bases−Specialized Consults (genomic
counselors, e.g.)
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The Opportunity
• Traditional “Consultative” relationship between Pathologist/Laboratorian and Clinical Physician must evolve
• Are there IT solutions that can enable this evolution?
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The “Shiny Object” Problem
• Greater collaboration among professionals can be enabledoTechnical issues are not the barrier
• If we build it, will they come?oAdoption depends upon utility to
practitioners, patients and other stakeholders
• What are the typical use cases that could benefit from the wider availability of collaboration through technology?
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Use Case 1 – Surgical Pathology Referrals or Send Outs• Pathologist reviews list of all new
cases• Identifies those cases that will not
or cannot be performed in-house• Pathologist needs to identify
resource (other lab or diagnostician) to consult, perform work, pack up specimens / paperwork
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Use Case 2 – Community Hospital• Case / Patient with multiple types of
tests performed (AP, CP, molecular)• Requires expertise from various
diagnosticians• Limited in-house resources available• Often requires patient and family to
travel, sometimes across the country
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Use Case 3 – Centers of Excellence• Centers of Excellence (COE) model
depends on patient encounter to perform sophisticated diagnostics
• Patient travel to COE location is expensive, time consuming and burdensome
• COE may expand through “satellites” in other markets, but this is capital intensive and does not fully leverage expertise of key personnel
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The Collaborative Network Solution* Collaborative networks are work networks
designed to solve issues more efficiently by leveraging the knowledge and experience of the user base.
[The collaborative network] is a web based service, computing platform, and communications vehicle designed to merge enterprise data, forums, and social networking to solve business objectives.
* Adapted from Wikipedia
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Evolution of the Collaborative Network• Closed/conditionally closed
community o Centralized
management/mediation of communication flow
o May serve important business need
o This model exists today
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The Next Generation• The Collaborative Network v 2.0
o Open - Can accommodate multiple modes−Business, academic/research, etc.
o Flexible rules and constructs−Support for governance by consensus−Ad hoc rules based on particular interaction−Strict rules governing conduct of parties over time by agreement
o Multiple communities−Open and conditionally closed
o Peer to peer
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Benefits of Collaborative Network• Leverage
o Amplifies capability of any given network participant
• Adaptabilityo Organic (crystalline) structure
accommodates multiple use cases o Allows participants to define new use cases
within broad parameters of acceptable use/conduct
• Disintermediationo Peers deal with peers - nearly “frictionless”
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The Seven Elements of a Collaborative Network*• Search – data, experts or content• Participant driven – add or share content• Data integration – accessible by all nodes,
subject to security, consent and other rules • Dashboards – manage workflow and data• User follow – allow users (peers) and their
content to be followed and accessed• Dynamic content – instant update availability• Governance – Controlled access to content and
data with defined security levels* Adapted from Wikipedia
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The Diagnostic Collaborative Network• Participants (“Nodes”) can be connected by a
communications infrastructure supporting robust interaction and data sharing enabling diagnosticso Examples of sources of data to be shared
−Diagnostic testing services providers (Clinical, Pathology, Molecular, Imaging, etc.)
−Sources of patient information (HIEs, PHRs, EHRs)−Knowledge bases (best practices, payer driven rules,
preauthorization rules, wellness profiles, disease management and decision support, etc.)
−On-line research resources (Academic, published clinical trials, publicly available information from Centers of Excellence)
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Technology Components and Workflow Paradigms• Standards-based connectivityoValue-added network/clinical clearinghouse
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Connecting EMRs to Labs Instantly
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Technology Components and Workflow Paradigms• Lessons to be drawn from social
media
oPeer-to-peer networks with flexible rules that allow ad hoc formation of communities that are open or conditionally closed to new members based upon relationship, interest, need, etc.
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Technology Components and Workflow Paradigms
o Communities−Facebook Friends, Community Pages
o Standards based on peer review, as used in current apps− “Like” (Facebook)− “Followers” Twitter −“Recommendation” (LinkedIn)− “Ratings” eBay
o Decision support based on network behavior/data received or sought−Amazon (people who bought this also
bought . . .)
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Technology Components and Workflow Paradigms• Diagnostic Desktop – “Diagnostic EHR”
o Distinct from “Clinical EHR”o Uniquely suited to collaboration
−Multi-modal Dashboard−Support for disparate data sources−Smartsearch, predictive search, agents− “Workbench” for merging/synthesizing
aggregated data−Collaborative communication using Chat, push to talk, other tools
o Facilitates “super diagnosis”23
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Creating the Super Diagnosis
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ReportsConsult
Reference Material
SUPER DIAGNOSIS
Biomarker
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© 2011 Atlas Development Corporation. All rights reserved.
Questions for Future Consideration
• How are the rules and constructs developed?
• How is “membership” determined?• What business models will support an
open collaborative network?• What are the obstacles to effective
deployment?
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