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Clinical Decision Support Systems - Sunil Nair Health Informatics Dalhousie University
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Clinical Decision Support Systems - Sunil Nair Health Informatics Dalhousie University

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  • Thanks for the presentation! It is super helpful. Simply the idea of an electronic brain sends my brain into hyper-drive, as do 'doctors in a box.' The medical world today is so advanced, it is absolutely incredible. http://www.my911help.com
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  • Fioricet is often prescribed for tension headaches caused by contractions of the muscles in the neck and shoulder area. Buy now from http://www.fioricetsupply.com and make a deal for you.
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  • nice presentation.
    would you please send me a copy at soton73@yahoo.com
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  • 1. Clinical Decision Support Systems (CDSS) Sunil Nair Dalhousie Health Informatics November 1, 2007
  • 2. Artificial Intelligence in Medicine
    • Quest for “electronic brain”
    • Early research – “”doctors in a box”
    • More emphasis on Diagnosis
    • “ Medical Artificial Intelligence is primarily concerned with the construction of AI programs that perform diagnosis and make therapy recommendations”
  • 3. What are CDSS’s
    • “ active knowledge systems which use two or more items of patient data to generate case-specific advise”
    • [Wyatt J, Spiegelhalter D, 1991].
  • 4. Clinical Decision
  • 5. CDSS - Definition
    • “ the provision of Clinical Knowledge and Patient related Information, intelligently filtered or presented at appropriate times, to enhance patient care”
    • Osheroff JA, Pifer EA, Sittig DF, Jenders RA, Teich JM. Clinical decision support implementers' workbook . Chicago: HIMSS, 2004. www.himss.org/cdsworkbook .
  • 6. Evolution: Early Systems. DX plain – CDSS – Diagnosis aid 1989 HELP – HIS integrated with CDSS 1980 Current Systems MYCIN – Infection management -Rule based, IF and THEN rules. PUFF – LIS for interpretation of Pulmonary function test. 1976 INTERNIST 1 – diagnosis 1974 AAPHELP –Leeds Abdominal Pain System 1972
  • 7. Why CDSS’s?
    • Knowledge at the point of care
    • Apply the best evidence
    • Serve as a peripheral brain – assist
    • Decision making – enhance communication.
    • Improve Healthcare processes and Outcomes.
  • 8. The Information Overload
  • 9. Clinical decision making Paul Gorman, Medical Decision Making 1995
  • 10. Clinical Workflow: How does CDSS fit?
  • 11. CDSS application areas
  • 12. CDSS - Applications
    • Alerts and reminders
    • Diagnostics Assistance
    • Therapy critiquing and planning
    • Prescribing decision support systems
    • Information Retrieval
    • Image recognition and interpretation
    • Diagnostic and educational systems
  • 13. CDSS Functions - trend
    • Administration
    • Managing clinical complexity details
    • Cost control
    • Decision support
  • 14. An Effective CDSS should:
    • Speed
    • Anticipate/Suggest
    • Fit in to user’s Workflow
    • User friendly-interface-rules
    • Alerts should be descriptive
    • Changing direction
  • 15. Effective CDSS features contd.
    • Simple guidelines
    • Prompt Additional Information only when required
    • Monitor impact, feedback and respond
    • Manage and maintain Knowledge Based system
    • Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality. David W. Bates, MD, MSc, Division of General Medicine and Primary Care, Brigham and Women's Hospital, May 27, 2003
  • 16. CDSS Goals
    • Patient Safety – Error Reduction/prevention
    • Cost Reduction – without compromising care
    • Promoting best practice – Enforcing compliance (Practice Guidelines)
  • 17. What makes CDSS possible?
    • Machine Learning Systems/Expert Systems
      • Create new knowledge
      • Expressed as RULES or decision aids.
      • KARDIO – for interpreting ECG
      • A Study in Deep and Qualitative Knowledge for Expert Systems Ivan Bratko , et al., Nov 1989
      • http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=5059
      • Data Mining and Knowledge Management systems
    • KNOWLEDGE MANAGEMENT, DATA MINING, AND TEXT MINING IN MEDICAL INFORMATICS., Hsinchun chen et al.,
    • http://ai.arizona.edu/hchen/chencourse/MedBook/Chapter_01.pdf
  • 18. CDSS - Benefits
    • Improve patient safety
      • Reduce medical errors
      • Improved medication and test ordering
    • Improve quality of care
      • Application of Clinical Pathways and Guidelines
      • Evidence based Medicine
      • Improved Clinical documentation
      • Increase quality time for direct patient care
    • Improve efficiency in Healthcare delivery
      • Reduce costs, reduce test duplication, decrease adverse events
  • 19. CDSS: Computerized Physician Order Entry
    • Growing evidence that CPOE reduce medical errors and adverse drug events.
    • Effects of Computerized Physician Order Entry and Clinical Decision Support Systems on Medication Safety Rainu Kaushal,MD,MPH et al Arch Intern Med. 2003
    • http://archinte.ama-assn.org/cgi/content/full/163/12/1409
    • Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes
    • Garg et al JAMA. 2005
    • http://jama.ama-assn.org/cgi/content/full/293/10/1223
  • 20. Opposing views…
    • CPOE facilitate medication error ‘risks’, create new errors.
    • Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors. Ross Koppel,PhD et al. JAMA. 2005 http://jama.ama-assn.org/cgi/content/full/293/10/1197
    • Computer Technology and Clinical Work
    • Robert L. Wears et. al. JAMA.  2005;293:1261-1263 .
    • http://jama.ama-assn.org/cgi/content/full/293/10/1261
  • 21. CDSS: Drawbacks
  • 22. CDSS Issues: Success or Failure
    • Careful evaluation of user needs
    • Leadership
    • Integration Issues
    • Human-Computer interface
  • 23. Why does CDSS fail?
    • Belief that Diagnosis is the dominant decision making issue
      • “what does this patient have?” vs. “how can I help this patient”
    • Cognitive factors – different people understand differently. Human-Computer interaction.
    • http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=130077
  • 24. CDSS reasons for failure.
    • Dependence on electronic patient record.
    • Challenging task of interaction between technologies and organizations.
    • Only as effective as the underlying Knowledge base, needs constant updating.
    • Additional effort (already busy, overworked)
    • Resist to Change
    • Computer Literacy
  • 25. CDSS Integration Objectives:
    • Critical Evaluation
    • Identifying main factors involved
    • Understand that Healthcare is Complex and Patient focused
    • Efficient Data Management
    • Tracking the “Alerts”
    • Standardization/Interoperability
  • 26. Evaluation Problem Definition Potential for Errors Change Issues Measure Outcomes Implementation
  • 27. CDSS: Summary
    • Possible in a complex healthcare environment
    • Has to fit in to the workflow
    • Enhance patient safety features
  • 28. Conclusion
    • The future of CDSS depends on removal of barriers to implementation.
    • Continue to have profound effect on medical education
    • Trained clinicians will always be required, the key is cooperative relationship between physician and computer based decision making tool
  • 29.
    • Discussions
      • CDSS recommendation to clinician results in patient harm, who is responsible?
    • Questions
  • 30.
    • Thank you!