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

  1. 1. Clinical Decision Support Systems (CDSS) Sunil Nair Dalhousie Health Informatics November 1, 2007
  2. 2. Artificial Intelligence in Medicine <ul><li>Quest for “electronic brain” </li></ul><ul><li>Early research – “”doctors in a box” </li></ul><ul><li>More emphasis on Diagnosis </li></ul><ul><li>“ Medical Artificial Intelligence is primarily concerned with the construction of AI programs that perform diagnosis and make therapy recommendations” </li></ul>
  3. 3. What are CDSS’s <ul><li>“ active knowledge systems which use two or more items of patient data to generate case-specific advise” </li></ul><ul><li>[Wyatt J, Spiegelhalter D, 1991]. </li></ul>
  4. 4. Clinical Decision
  5. 5. CDSS - Definition <ul><li>“ the provision of Clinical Knowledge and Patient related Information, intelligently filtered or presented at appropriate times, to enhance patient care” </li></ul><ul><li>Osheroff JA, Pifer EA, Sittig DF, Jenders RA, Teich JM. Clinical decision support implementers' workbook . Chicago: HIMSS, 2004. . </li></ul>
  6. 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. 7. Why CDSS’s? <ul><li>Knowledge at the point of care </li></ul><ul><li>Apply the best evidence </li></ul><ul><li>Serve as a peripheral brain – assist </li></ul><ul><li>Decision making – enhance communication. </li></ul><ul><li>Improve Healthcare processes and Outcomes. </li></ul>
  8. 8. The Information Overload
  9. 9. Clinical decision making Paul Gorman, Medical Decision Making 1995
  10. 10. Clinical Workflow: How does CDSS fit?
  11. 11. CDSS application areas
  12. 12. CDSS - Applications <ul><li>Alerts and reminders </li></ul><ul><li>Diagnostics Assistance </li></ul><ul><li>Therapy critiquing and planning </li></ul><ul><li>Prescribing decision support systems </li></ul><ul><li>Information Retrieval </li></ul><ul><li>Image recognition and interpretation </li></ul><ul><li>Diagnostic and educational systems </li></ul>
  13. 13. CDSS Functions - trend <ul><li>Administration </li></ul><ul><li>Managing clinical complexity details </li></ul><ul><li>Cost control </li></ul><ul><li>Decision support </li></ul>
  14. 14. An Effective CDSS should: <ul><li>Speed </li></ul><ul><li>Anticipate/Suggest </li></ul><ul><li>Fit in to user’s Workflow </li></ul><ul><li>User friendly-interface-rules </li></ul><ul><li>Alerts should be descriptive </li></ul><ul><li>Changing direction </li></ul>
  15. 15. Effective CDSS features contd. <ul><li>Simple guidelines </li></ul><ul><li>Prompt Additional Information only when required </li></ul><ul><li>Monitor impact, feedback and respond </li></ul><ul><li>Manage and maintain Knowledge Based system </li></ul><ul><li>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 </li></ul>
  16. 16. CDSS Goals <ul><li>Patient Safety – Error Reduction/prevention </li></ul><ul><li>Cost Reduction – without compromising care </li></ul><ul><li>Promoting best practice – Enforcing compliance (Practice Guidelines) </li></ul>
  17. 17. What makes CDSS possible? <ul><li>Machine Learning Systems/Expert Systems </li></ul><ul><ul><li>Create new knowledge </li></ul></ul><ul><ul><li>Expressed as RULES or decision aids. </li></ul></ul><ul><ul><li>KARDIO – for interpreting ECG </li></ul></ul><ul><ul><li>A Study in Deep and Qualitative Knowledge for Expert Systems Ivan Bratko , et al., Nov 1989 </li></ul></ul><ul><ul><li> </li></ul></ul><ul><ul><li>Data Mining and Knowledge Management systems </li></ul></ul><ul><li>KNOWLEDGE MANAGEMENT, DATA MINING, AND TEXT MINING IN MEDICAL INFORMATICS., Hsinchun chen et al., </li></ul><ul><li> </li></ul>
  18. 18. CDSS - Benefits <ul><li>Improve patient safety </li></ul><ul><ul><li>Reduce medical errors </li></ul></ul><ul><ul><li>Improved medication and test ordering </li></ul></ul><ul><li>Improve quality of care </li></ul><ul><ul><li>Application of Clinical Pathways and Guidelines </li></ul></ul><ul><ul><li>Evidence based Medicine </li></ul></ul><ul><ul><li>Improved Clinical documentation </li></ul></ul><ul><ul><li>Increase quality time for direct patient care </li></ul></ul><ul><li>Improve efficiency in Healthcare delivery </li></ul><ul><ul><li>Reduce costs, reduce test duplication, decrease adverse events </li></ul></ul>
  19. 19. CDSS: Computerized Physician Order Entry <ul><li>Growing evidence that CPOE reduce medical errors and adverse drug events. </li></ul><ul><li>Effects of Computerized Physician Order Entry and Clinical Decision Support Systems on Medication Safety Rainu Kaushal,MD,MPH et al Arch Intern Med. 2003 </li></ul><ul><li> </li></ul><ul><li>Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes </li></ul><ul><li>Garg et al JAMA. 2005 </li></ul><ul><li> </li></ul>
  20. 20. Opposing views… <ul><li>CPOE facilitate medication error ‘risks’, create new errors. </li></ul><ul><li>Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors. Ross Koppel,PhD et al. JAMA. 2005 </li></ul><ul><li>Computer Technology and Clinical Work </li></ul><ul><li>Robert L. Wears et. al. JAMA.  2005;293:1261-1263 . </li></ul><ul><li> </li></ul>
  21. 21. CDSS: Drawbacks
  22. 22. CDSS Issues: Success or Failure <ul><li>Careful evaluation of user needs </li></ul><ul><li>Leadership </li></ul><ul><li>Integration Issues </li></ul><ul><li>Human-Computer interface </li></ul>
  23. 23. Why does CDSS fail? <ul><li>Belief that Diagnosis is the dominant decision making issue </li></ul><ul><ul><li>“what does this patient have?” vs. “how can I help this patient” </li></ul></ul><ul><li>Cognitive factors – different people understand differently. Human-Computer interaction. </li></ul><ul><li> </li></ul>
  24. 24. CDSS reasons for failure. <ul><li>Dependence on electronic patient record. </li></ul><ul><li>Challenging task of interaction between technologies and organizations. </li></ul><ul><li>Only as effective as the underlying Knowledge base, needs constant updating. </li></ul><ul><li>Additional effort (already busy, overworked) </li></ul><ul><li>Resist to Change </li></ul><ul><li>Computer Literacy </li></ul>
  25. 25. CDSS Integration Objectives: <ul><li>Critical Evaluation </li></ul><ul><li>Identifying main factors involved </li></ul><ul><li>Understand that Healthcare is Complex and Patient focused </li></ul><ul><li>Efficient Data Management </li></ul><ul><li>Tracking the “Alerts” </li></ul><ul><li>Standardization/Interoperability </li></ul>
  26. 26. Evaluation Problem Definition Potential for Errors Change Issues Measure Outcomes Implementation
  27. 27. CDSS: Summary <ul><li>Possible in a complex healthcare environment </li></ul><ul><li>Has to fit in to the workflow </li></ul><ul><li>Enhance patient safety features </li></ul>
  28. 28. Conclusion <ul><li>The future of CDSS depends on removal of barriers to implementation. </li></ul><ul><li>Continue to have profound effect on medical education </li></ul><ul><li>Trained clinicians will always be required, the key is cooperative relationship between physician and computer based decision making tool </li></ul>
  29. 29. <ul><li>Discussions </li></ul><ul><ul><li>CDSS recommendation to clinician results in patient harm, who is responsible? </li></ul></ul><ul><li>Questions </li></ul>
  30. 30. <ul><li>Thank you! </li></ul>