25 years of promises lessons learned from modeling professional practices
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25 Years of PROMISES: Lessons Learned from Modeling Professional Practices. Extending Medical Enterprise Ontologies: Levels; Limits; and Tensions. 7 th International Protégé Conference July 6, 2004. Bob Smith, Ph.D. Tall Tree Labs [email protected] Bill Elliott, Internal Medical Labs

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25 years of promises lessons learned from modeling professional practices

25 Years of PROMISES: Lessons Learned from Modeling Professional Practices

Extending Medical Enterprise Ontologies: Levels; Limits; and Tensions

Draft 3

7 th international prot g conference july 6 2004
7th International Protégé ConferenceJuly 6, 2004

Draft 3

comprehensive computer supported medical decision support systems
Comprehensive Computer Supported Medical Decision Support Systems?
  • Comprehensive: Intelligent, Robust, Adaptive?
  • Computer Supported: Knowledge, Model Driven, and Data (Factual) Informed?
  • Medical: Ecology: Public and Private Health Care and “caring systems”
  • Decision Support: NOT Professional Automation but Professional Reasoning Enhancements
  • Systems: Social components, technical components, cultural components with explicit guidance “rules for rule making in informed communities”

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swim lanes level 7 to level 1
Swim lanes Level 7 to Level 1(?)
  • De Facto Standards (Current Practice Tensions between competing evolving-emergent standards: Knowledge Management, Process Management, Standards Management; Business Strategist’s Strategy (HBR))
  • Standard Abstractions (MS, IBM, SUN: WS-I)
  • Regulatory Guidance Clusters (NIST, NIH, W3C, etc.)
  • CEO-Supply Chain Integration (Health Care Infrastructure and Payment Systems)
  • Medical Practitioners (Internal Medicine Associates, Inc.)
  • Technical Staff (IT-Lab Techs)
  • Patients with medical problem(s) and paper Med Records (Brave Dave with High PSA Radical Surgery)

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this prot g conference demonstrates top down strategies
This Protégé Conference demonstrates top down strategies
  • Vast changes in the supply of technical capability with ontologies, semantic web services standards, tools, vendors: with obvious economic and social ripple effects;
  • Vast changes in the demographics of demand for effective and efficient integrated and orchestrated medical practice

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bottom up strategy
Bottom Up Strategy
  • Size distribution of medical practice and associated IT and Process maturity
    • How and where do most patients receive medical care?
      • Garfield model: Distributed health delivery areas
    • Scenario: You are the technology “gatekeeper” for an 8 physician practice with a Stat Lab (Statistics go here…)

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dialectics from hbr
Dialectics from HBR?
  • Harvard Business Review June 2004 article by Michael Porter challenging current assumptions of US Health Care Competitive Strategies
  • Can the Porter-Teisberg policy changes be modeled? With Ontology and Process Management-Knowledge Management simulators?

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coherent architectural plans
Coherent Architectural Plans?
  • What kind of a roadmap would you sketch for yourself, today, in thinking about the real needs of these physicians in your organization?
  • How might you arrange to brainstorm the options using available process modeling and simulation tools to position Protégé and SAGE Projects in context?

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application development options architect needed
Application Development Options (Architect Needed)
  • Protégé?
  • SemTalk2 ?
  • MS_DotNET?
  • Hybrid?
  • See link: ..\Sacramento_Wk\101MSDCF\LabPicsJune04a.htm

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protege sage project architecture
Protege – Sage Project Architecture
  • Sharable Active Guidance Environment

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process model as is
Process Model: AS IS
  • Describe current workflow

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references
References

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alan rector where are we going
Alan Rector: Where are we going?
  • Citation: Rector, AL (2001) AIM: A personal view of where I have been and where we might be going. Artificial Intelligence in Medicine 23:111-127
  • “My own career in Medical Informatics and AI in Medicine has oscillated between
    • concerns with medical records and
    • concerns with knowledge representation with decision support as a pivotal integrating issue.
  • It has focused on using AI to organize information and reduce ‘muddle’ and
  • improve the user interfaces to produce ‘useful and usable systems’ to help doctors with a ‘humanly impossible task’. “

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reference domains
Reference Domains
  • Protégé/Sage Project/CoP linkages
  • Ontology Management of OE
  • Health Care Technology Trends (Cladistics)
  • Strategy and Policy (Direction and Guidance)
  • Business Semantic Primes
  • Knowledge Flow Metrics
  • Process Knowledge Management

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