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- 1. Medicine and web 3.0 - A wishlist Arun Keepanasseril, BDS, MDS (Prosthodontics) Msc e Health candidate McMaster University Hamilton Canada
- 2. Some problems faced by clinicians in the information era • Information overload • Interruptions. • Technology adaptation
- 3. Information overload - Reasons • Rapid production of information • The ease of duplication and transmission . • An increase in the available channels of incoming information.
- 4. Information overload - Reasons • Contradictions and inaccuracies in available information • A lack of a method for comparing and processing different kinds of information • The pieces of information are unrelated or do not have any overall structure to reveal their relationships
- 5. Total Number of Articles per Year, PubMed Database, 1990-2009 900,000 845,175 800,000 700,000 600,000 500,000 400,000 300,000 200,000 100,000 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
- 6. Growth of PubMed citations from 1986 to 2010. Lu Z Database 2011;2011:baq036 © The Author(s) 2011. Published by Oxford University Press.
- 7. Why search? • 0.07 - 1.85 questions per patient visit. Kahane S, Stutz E, Aliarzadeh B.Must we appear to be all-knowing?: patients' and family physicians' perspectives on information seeking during consultations Can Fam Physician. 2011 Jun;57(6):e228-36
- 8. Information seeking behavior HC Coumou-How do primary care physicians seek answers to clinical questions? A literature review. J Med Libr Assoc. 2006 Jan;94(1):55-60
- 9. Information seeking behavior HC Coumou-How do primary care physicians seek answers to clinical questions? A literature review. J Med Libr Assoc. 2006 Jan;94(1):55-60
- 10. Medical Literature Pubmed Proquest Psychinfo CINAHL Cochrane MD Consult Global Health EMBASE AMED Fragmented repositories
- 11. Medical Literature Specialized search strategies
- 12. Fragmented + Specialized =
- 13. Anatomy of Literature search Overview of general user interactions with PubMed (or similar systems) for searching biomedical literature. Lu Z Database 2011;2011:baq036 © The Author(s) 2011. Published by Oxford University Press.
- 15. PUBMED
- 18. Web 2.day • High recall, low precision • Results highly sensitive to vocab. • Results are single web pages.
- 20. ONE
- 22. Super search
- 23. Super search •Contextual. • Comprehensive. • Easy • Fast
- 24. Zhiyong Lu: PubMed and beyond: a survey of web toolsfor searching biomedical literature, Database, Vol. 2011, Article ID baq036, doi:10.1093/database/baq03
- 25. 8 in 10 Internet users have looked online for health information.
- 26. “Year of the Empowered Patient.” - 2011. • Challenge a doctor’s treatment/diagnosis, • Ask a physician to change a treatment, • Discuss information found online with a physician, • Use the Internet instead of seeing a doctor • Made a healthcare decision because of online information.
- 27. Consumer information online • Unreliable. • No contextual information • Likely to confuse the patient and the doctor at times!
- 28. Some times what consumers need are answers
- 31. For the consumer • Authentic Information relevant to their unique condition. • Easy to understand presentation
- 34. TWO
- 36. Improved Health Information
- 37. Traditional clinical trials • Expensive • Time consuming
- 38. ALLHAT Trial • 42,418 patients • 623 offices and clinics • 4 drugs • 5 year follow up • 120 million USD • 8 years from start to finish
- 39. Figure courtesy Scientific American
- 40. Gigantic distributed database with hidden data Figure courtesy Scientific American
- 41. Can semantics find a way to use them for research, could replace the expensive clinical trials whenever possible?
- 43. THREE
- 45. Semantic aided clinical research
- 46. Unintended consequences of EHR • More/New Work for • Changes in Communication Clinicians Patterns and Practices • Workflow Issues • Negative Emotions • Never Ending System • Generation of New Kinds of Demands Errors • Problems Related to Paper • Unexpected and Unintended Persistence Changes in Institutional http://www.ohsu.edu/academic/dmice/research/cpoe/unintended_consequences.php
- 47. Semantic-aware Electronic Health Records • Intelligent patient summary. • Detection of medication conficts • Diagnosis support • Chronic disease monitoring • De Potter P, Debevere P, Mannens E. Next generation assisting clinical applications by using semantic-aware electronic health records. 2009;
- 48. Context aware applications • Entities sense and automatically adapt to their changing contexts. • Personalized, context-aware services in real- time to improve patient safety and quality of care. USING ONTOLOGY TO SUPPORT CONTEXT AWARENESS IN HEALTHCARE :Wen Yao1, Chao-Hsien Chu, Akhil Kumar, Zang Li
- 50. FOUR
- 53. Thank you
Notas do Editor
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- 2010 estimates are more than a million\n
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- Family physicians encounter between 0.07 and 1.85 questions that they need to look up per patient visit.\n
- J Med Libr Assoc. 2006 Jan;94(1):55-60.\nHow do primary care physicians seek answers to clinical questions? A literature review.\n \n Colleagues and paper sources - despite the enormous increase in and better accessibility to electronic information sources. \nCoumou HC, Meijman FJ.\nSource\n\n
- J Med Libr Assoc. 2006 Jan;94(1):55-60.\nHow do primary care physicians seek answers to clinical questions? A literature review.\n \n Colleagues and paper sources - despite the enormous increase in and better accessibility to electronic information sources. \nCoumou HC, Meijman FJ.\nSource\n\n
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- Formulating an appropriate search question \nFinding an optimal search strategy, \nInterpreting the evidence found.\n
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- Anatomy of search\n
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- http://books.google.ca/books?id=cIYAiS1wbRsC&pg=PA7&lpg=PA7&dq=semantic+appointments&source=bl&ots=i9wQwwTbxs&sig=Ud2_aeCfIpUGBnOzL8gJF0bHUMo&hl=en&ei=PJ9iTrPfKdLK0AGqibCTCg&sa=X&oi=book_result&ct=result&resnum=1&ved=0CBoQ6AEwAA#v=onepage&q=semantic%20appointments&f=false\n
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- encouraged better communication between physicians and patients? Or it is leading to a breakdown between the two?.\n\n
- Manhatten research 99 million U.S. adults “Empowered Consumers” –\n
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- the oldest and cheapest of the drugs, known as thiazide-type diuretics, were more effective at reducing hypertension than the newer, more expensive ones.\nBut what should patients do if their blood pressure was not controlled by a diuretic alone, as happened with 60 percent of the ALLHAT patients?\nA follow up study is too expensive to conduct\n
- We have huge ware house of data in our medical institutions.\n
- We have huge ware house of data in our medical institutions. a gigantic distributed database with hidden data held in individual hospitals, research centres, and institutes. Is access to these data useful? Yes. Ground-breaking discoveries can be made if researchers in medicine are exposed to data rich in diversity. Is access to these data easy? Yes and no. The sheer size of the data available is more than any one can handle. Semantic web technologies serve to provide us access to such data and make good use of such data.\n
- The rapid increase of linked data poses new challenges for knowledge engineering.\nData may need to be reengineered before reusing\n
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- \n Context-embedded Intelligent Hospital Ontology (CIHO) to support semantic interoperability and context-aware applications using OWL-DL\n \n For instance, a monitor in a surgery room will be able to display the information of a patient in that room to prevent misidentification and treatment errors.\n \n
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