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25 Years of PROMISES: Lessons Learned from Modeling Professional Practices PowerPoint Presentation
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25 Years of PROMISES: Lessons Learned from Modeling Professional Practices

25 Years of PROMISES: Lessons Learned from Modeling Professional Practices

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25 Years of PROMISES: Lessons Learned from Modeling Professional Practices

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  1. 25 Years of PROMISES: Lessons Learned from Modeling Professional Practices Extending Medical Enterprise Ontologies: Levels; Limits; and Tensions Draft 3

  2. 7th International Protégé ConferenceJuly 6, 2004 • Bob Smith, Ph.D. Tall Tree Labs • robsmith5@1talltrees.com • Bill Elliott, Internal Medical Labs • BillAppl@AOL.com • Christian Fillies, SemTalk • clillies@semtalk.comwww.sentalk.com • Gay Woods-Albrecht • www.bpmsolutionsgroup.com Draft 3

  3. Outline: 25 Years of PROMISES Draft 3

  4. Problem Oriented Medical Records and Guidance: Draft 3

  5. Draft 3

  6. What happened to our Guidance expectations of 1980? Draft 3

  7. Effective Supply and Demand Draft 3

  8. 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” Draft 3

  9. Draft 3

  10. OMB’s US Statistical Abstract-XML Altova Project and Practices Draft 3

  11. JIT Process Knowledge Integration Draft 3

  12. BPMN.Org Perspectives on Liaison Options – June, 2004 Draft 3

  13. 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) Draft 3

  14. 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 Draft 3

  15. 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…) Draft 3

  16. 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? Draft 3

  17. 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? Draft 3

  18. Application Development Options (Architect Needed) • Protégé? • SemTalk2 ? • MS_DotNET? • Hybrid? • See link: ..\Sacramento_Wk\101MSDCF\LabPicsJune04a.htm Draft 3

  19. Protege – Sage Project Architecture • Sharable Active Guidance Environment Draft 3

  20. Draft 3

  21. Process Model: AS IS • Describe current workflow Draft 3

  22. Draft 3

  23. References Draft 3

  24. 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’. “ Draft 3

  25. 25 Years of PROMISES Draft 3

  26. 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 Draft 3