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The Development of National Electronic Pathology / Laboratory Networks

The Development of National Electronic Pathology / Laboratory Networks. A Framework for the Diagnostic Collaborative Network Robert Atlas, President & CEO, ATLAS Medical April 16, 2011. Agenda. The Challenge The Opportunity Evolution of the Collaborative Network

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The Development of National Electronic Pathology / Laboratory Networks

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  1. The Development of National Electronic Pathology / Laboratory Networks A Framework for the Diagnostic Collaborative NetworkRobert Atlas, President & CEO, ATLAS Medical April 16, 2011

  2. 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

  3. The Challenge • Increasing complexity of diagnostic disciplines • Multi-modal • Molecular / Imaging / Digital Pathology • Highly personalized • Patient history including genome

  4. The Challenge • Aggregation of disparate data elements from multiple sources • Test results, interpretations • PHR (genomic map) • Knowledge bases • Specialized Consults (genomic counselors, e.g.)

  5. The Opportunity • Traditional “Consultative” relationship between Pathologist/Laboratorian and Clinical Physician must evolve • Are there IT solutions that can enable this evolution?

  6. The “Shiny Object” Problem • Greater collaboration among professionals can be enabled • Technical issues are not the barrier • If we build it, will they come? • Adoption 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?

  7. 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

  8. 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

  9. 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

  10. 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

  11. Evolution of the Collaborative Network • Closed/conditionally closed community • Centralized management/mediation of communication flow • May serve important business need • This model exists today

  12. The Next Generation • The Collaborative Network v 2.0 • Open - Can accommodate multiple modes • Business, academic/research, etc. • 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 • Multiple communities • Open and conditionally closed • Peer to peer

  13. Benefits of Collaborative Network • Leverage • Amplifies capability of any given network participant • Adaptability • Organic (crystalline) structure accommodates multiple use cases • Allows participants to define new use cases within broad parameters of acceptable use/conduct • Disintermediation • Peers deal with peers - nearly “frictionless”

  14. 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

  15. The Diagnostic Collaborative Network • Participants (“Nodes”) can be connected by a communications infrastructure supporting robust interaction and data sharing enabling diagnostics • 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)

  16. Technology Components and Workflow Paradigms • Standards-based connectivity • Value-added network/clinical clearinghouse

  17. Connecting EMRs to Labs Instantly

  18. Technology Components and Workflow Paradigms • Lessons to be drawn from social media • Peer-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.

  19. Technology Components and Workflow Paradigms • Communities • Facebook Friends, Community Pages • Standards based on peer review, as used in current apps • “Like” (Facebook) • “Followers” Twitter • “Recommendation” (LinkedIn) • “Ratings” eBay • Decision support based on network behavior/data received or sought • Amazon (people who bought this also bought . . .)

  20. Technology Components and Workflow Paradigms • Diagnostic Desktop – “Diagnostic EHR” • Distinct from “Clinical EHR” • 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 • Facilitates “super diagnosis”

  21. Creating the Super Diagnosis Reference Material Biomarker Reports Consult SUPER DIAGNOSIS

  22. 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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