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06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
06 Am09 Presentations   Gutman
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06 Am09 Presentations Gutman

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  • 1. Take Home Messages
    • Increasing Pressure to Assure Attention to Guidelines
    • Clinical Judgment Counts as long as the Guidelines are Recalled
    • Payers Will be Looking for Practice Metrics
    • There Has to be a Way to Support this.
  • 2.  
  • 3.  
  • 4. ADHERENCE TO QUALITY INDICATORS McGlynn et al NEJM 2003
  • 5. QUALITY IMPROVEMENT ORGANIZATIONS ARE TOOLING UP DEMAND FOR METRICS
    • .
  • 6. COMING EVENTS: ARE YOU GOING TO BE READY IN FOUR YEARS?
    • Federal Pay for Performance
    • Private Payer P4P Contracts and Web Based Display of Adherence
    • Expectations of the public
    • Your own Web Based highlights
    • Patient Satisfaction
    • Practice Satisfaction
  • 7. “ HEALTH CARE INFORMATION TECHNOLOGY CHANGES THE ECOSYSTEM OF PRACTICE” William W. Stead
  • 8. Clinical Decision Support
    • Clinical decision support systems
    • “an automated process for comparing patient-specific characteristics against a computerized knowledge base [a set of guidelines ] with resulting recommendations or reminders presented to the provider at the time of clinical decision-making ”
    • Hunt, Haynes, Hanna, & Smith, JAMA. 208 (15) 1998.
  • 9. STEPS TOWARD DESIGNING AN OFFICE BASED CLINICAL PRACTICE GUIDELINE DECISION SUPPORT AND METRICS SYSTEM
    • Must have an EMR
    • Must have Practice buy-in
    • Must have a decision support system that:
      • Reliably search, obtain, and organize clinical data
      • Reliably translate the data into applicable information
    • Must have agreement (or near agreement) on clinical guidelines used for corrective action
    • Must deliver content at the point of patient contact
    • Must create a culture where metrics are acceptable without anger or fear
  • 10.  
  • 11. CDSS Protocol Content: Nephrology
    • Chronic Kidney Disease Management
    • National Kidney Foundation KDOQI Guidelines
    • ACEI / ARB Therapy, with and without Proteinuria
    • Anemia Screening / Management
    • Vitamin D / Calcium Deficiency Management
    • Elevated Phosphorous Management
    • Medication Avoidance or Cautionary Use
    • Vein Mapping / Cardiology Consult/Surgical Referrals (CKD 4 or CKD 5)
    • Education Options
    • Measure of:
      • Renal Function (eGFR)
      • Parathyroid hormone
      • Vitamin D
      • Calcium
      • Phosphorous
      • Hemoglobin
      • Iron saturation and Ferritin (ESA Therapy)
  • 12. CDSS Protocol Content: Nephrology
    • Cardiovascular Disease Management
    • American College of Cardiology, National Cholesterol Education Program (NCEP) / ATP III
    • CAD or CAD Equivalent Dx: Anti-platelet Therapy
    • CAD, CHF, or CVD: Beta Blocker Therapy
    • CAD, DM or CHF: ACEI / ARB Therapy
    •  
    • Diabetes Screening & Management
    • American Diabetes Association
    • HgbA1c Monitoring
    • Hypertension Screening & Management
    • JNC 7
    • Management with and without Diabetes or Renal Disease
    • Preventive Screening
    • US Preventive Services Task Force , Centers for Disease Control
    • Tobacco Use Screening and Management
    • Advanced Directives Screening
    • Influenza Vaccination
    • Hepatitis B Vaccination
  • 13. Overview of CINA Technology
  • 14. Overview of CINA Technology
  • 15. Point of Care Decision Support Patient Specific Automated Produced for every patient , at every visit , regardless of the Reason for Visit Utilized by all providers (MD, NP, PA, nurses)
  • 16.
    • Active Diagnoses
      • Prioritized in accordance with the Protocol content / chronic disease(s) addressed
    • Active Medications
      • Prioritized in accordance with Protocols / chronic disease(s) addressed
    Point of Care Decision Support
  • 17. Point of Care Decision Support
    • Labs
      • Includes Labs that are pertinent to the Protocol content and referenced by the Action Items
      • Goals can reference as many labs as desired by the practice
  • 18. Point of Care Decision Support
    • Measures / Calculations
      • Referential data from the EMR (vital signs) as well as certain calculated results
    • Diagnostic Testing
      • Referential data from the EMR
      • Indicates date of last procedure
  • 19. Point of Care Decision Support
    • Labs
      • Includes Labs that are pertinent to the Protocol content and referenced by the Action Items
      • Goals can reference as many labs as desired by the practice
  • 20. Point of Care Decision Support
    • Risks
      • Based on Age, Sex, Risk Factors, and Diagnoses
    • Goals
      • Specific metrics of interest to the practice and addressed within the protocols
    • These 2 areas are the basis for the Recommendations / Action Items
  • 21. Point of Care Decision Support
    • Action Items
      • Divided into Action items for the Nurse / MA and for the Provider
      • Action Items relate to Medications, Labs, Procedures, Vaccines, Documentation
    • Visits
      • Derived from the EMR / billing data
  • 22. Point of Care CDSS Workflow
    • Front Desk / Reception
    • Reports are automatically generated prior to the start of the work day and at noon for afternoon add-ons
    • Additionally, the receptionist can generate ad hoc reports for a single patient
    • Nurse / MA
    • Completes missing documentation
    • Administers / queues vaccine / lab orders
    • Medication reconciliation
    • Communication tool for provider
    • Provider
    • Addresses recommendations as appropriate
    • Communication tool for staff
    • Educational tool for patient
  • 23. DNA Baseline Data
  • 24. Improvements In Prevention in Primary Care with Point of Care CDSS
  • 25. Improvements In Diabetes Management in Primary Care with Point of Care CDSS
  • 26. Diabetes Measures: Showing Consistent Improvement from both High Performing & Low Performing Clinics
  • 27. WHAT ARE GUIDELINES?
    • FROM “GHOSTBUSTERS”:
    • Murray to Weaver (she was “hitting” on him):
    • "I make it a rule never to get involved with possessed people." (pause-looking camera):
    • "Actually, it's more like a GUIDELINE than a rule..."
  • 28.  
  • 29. REACHING AGREEMENT WITHIN THE PRACTICE
    • Several of the algorithms are CKD level specific
    • So: what or who decides on the CKD level?
    • Can the practitioner tolerate using the last eGFR found in the computer to “correct” the last diagnosis?
    • If one is too few to correct, can we use two consecutive?
    • How old can the data be?
  • 30. REACHING AGREEMENT WITHIN THE PRACTICE
    • Do we want a reminder to use ACEI and ARB for all CKD patients?
    • Or only those with proteinuria?
    • Can we tolerate being reminded if we have already decided it is not safe?
  • 31. REACHING AGREEMENT
    • Can we agree on a reminder to check vitamin D levels?
    • Which moiety?
    • What are the correct targets for PTH
    • Can we relate them CKD level?
  • 32. “MAPPING” ISSUES
    • How Does the CDR Recognize “proteinuria”?
    • How does it find the primary physician?
    • How can it tell when we refer to a vascular surgeon if all the users don’t have a uniform method of entering the information or leave it out
  • 33. Expected Benefits and ROI
    • Process in place for improving outcomes / guideline compliance
    • Positioned to participate in P4P
    • Ability to incorporate data from outside sources
    • CMS PQRI Reporting (Registry Based)
      • Failed efforts in Claims based reporting 2007
      • Registry reporting requires NO physician effort
      • PQRI bonus funds CINA solution, other quality improvement efforts
    • Per Visit Revenue Increase
      • Primary Care groups report avg $5-15 / visit increased revenue
  • 34. INTRODUCTION OF I.T. SHOULD BE APPROACHED AS AN INTERETIVE PROCESS-- A FAMILY OF APPROACHES, EACH WITH DISTINCT ADVANTAGES AND DISADVANTAGES William W. Stead MD
  • 35. IT HAS BEEN HARD TO SHOW QUALITY IMPROVEMENT. THE FAILURE IS RELATED TO SOLVE A COGNITIVE PROBLEM BY SIMPLY INSERTING AUTOMATION INTO OLD PROCESSES William W. Stead MD
  • 36. WHILE BETTER I.T. DESIGN CAN MINIMIZE MISFIT, DOCS ARE RESPONSIBLE FOR MANAGING THEIR PEOPLE-PROCESS-TECHNOLOGY SYSTEMS TO GET THE PROPER OUTCOME William W. Stead MD
  • 37. Take Home Messages
    • Increasing Pressure to Assure Attention to Guidelines
    • Clinical Judgment Counts as long as the Guidelines are Recalled
    • Payers Will be Looking for Practice Metrics
    • There Has to be a Way to Support this.

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