Decision Support at the Point of Care

1. Decision Support at the Point of Care Representing & Managing Knowledge & Integrating it into the Care Process Robert A. Greenes, M.D., Ph.D. Harvard Medical School Brigham & Women’s Hospital Boston, MA, USA

2. We are at a turning point in clinical information systems • Old focus: EMR, retrieval, reporting, communication • New focus: Knowledge access & decision support Greenes

3. Greenes

4. Medline reports gene analyses volume months Seeds of change • New technologies for Dx & Rx • Medical literature doubling every 19 yr • Doubles every 22 months for AIDS care • 2 million facts needed to practice • Gene expression analyses doubling every 8 months Greenes

5. Safety and quality concerns • To Err is Human(IOM 1999) • Adverse events in up to 3.7% of hospitalizations in US • Up to 13.6% lead to death • Half preventable • 22,000 – 49,000 people • Medical errors kill more people than MVAs (43,458), or breast cancer (42,297) • Costs to society of $17-29B • 50% is health care Greenes

6. The treatment gap • Approximately 25% of U.S. population has an abnormal LDL requiring intervention • 10% qualify for drug intervention • Of those, only ¼ are presently being treated • Treatment gap for hyperlipidemia presently = 7.5% of US population) Greenes

7. Disparities: Variability in CABG where HRR = Hospital Referral Region

8. Demand for change Crossing the Quality Chasm: A New Health System for the 21st Century • Safe • Effective • Patient-centered • Timely • Efficient • Equitable Richardson, William C. Crossing the Quality Chasm, Institute of Medicine, 2001 Greenes

9. Consumer empowerment • More involved in care process • More knowledgeable • More activist • More technically savvy Greenes

11. Disclosure

12. Demand for CPOE

13. Amendment to California SB 1875 Introduced On February 15, 2002, California state Sen. Jackie Speier (D-San Francisco/San Mateo) introduced Senate Bill (SB) 801, which amends Section 1339.63 of the California Health and Safety Code, bolstering the requirements specified by SB 1875, “Facility Plan to Eliminate or Substantially Reduce Medication Errors.” SB 1875 required as a condition of licensure that all general acute care hospitals, surgical clinics, and special hospitals adopt a formal plan to eliminate or substantially reduce medication-related errors. Plans must be implemented on or before January 1, 2005.

14. Error reduction, safety, quality • Safety • Appropriate drug dose & form • Adjustments • allergies, renal status, age, contraindications • interactions • Quality • Best Rx for indication • Appropriate referrals • Cost-effectiveness, efficiency • Reduced redundant or inappropriate tests • Generic or lower-cost medications • Order sets & care pathways • Optimal workflow • Correct dispensation, administration • Monitoring for adverse events • Providing feedback, education Greenes

15. Experience exists • Demonstrated success of CPOE • Error checks, ADE reduction • Decreased cost • Alerts & reminders • Appropriateness criteria • Guidelines Greenes

16. BWH Order entry

17. Drug-drug interaction alert

18. Lab alerts

19. Order sets

20. Other functionality • Check for redundant tests • Interpretive reporting • Identify non-indicated imaging procedures • Adverse event monitoring rules • Charge display • Signout • Reference/handbook Greenes

21. 55% decrease in serious medication errors Bates, JAMA 1998 Decreased redundant labs Bates, Am J Med, 1997 More appropriate renal dosing No reduction in inappropriate x-rays Harpole, JAMIA, 1997 Minimal effect of charge display Bates, Archives of Internal Medicine, 1995 More appropriate dosing, substitutions accepted Teich, Archives of Internal Medicine, 2000 Decreased vancomycin use Sojania, JAMIA, 1998 Cost-effective Greenes

22. Guidelines • Much development of guidelines since 1970s • Recent efforts aimed at computer-based interpretation • Goal of delivering patient-specific recommendations at point of care • Guidelines as core technology for many decision support applications Greenes

23. Guidelines as a core technology • Protocol-based care • Chronic disease management • Consultations • Critical pathways, UR/monitoring • Referral management • Workflow/process optimization • “Infobuttons” • Education/training • … Greenes

24. All told, there is much to cheer about … • Public interest, demand • Growing number of activities • Successes • in error reduction • in cost-effectiveness Momentum is building! Greenes

25. So what’s broken? • Limited availability • Most successes are one-of-a-kind, often academic • Slow diffusion Greenes

26. Original research 18% variable Negative results Dickersin, 1987 Submission 46% 0.5 year Kumar, 1992 Koren, 1989 Acceptance Negative results 0.6 year Kumar, 1992 Publication 17:14 Expert opinion 35% 0.3 year Poyer, 1982 Balas, 1995 Lack of numbers Bibliographic databases 50% 6. 0 - 13.0 years Antman, 1992 Poynard, 1985 Reviews, guidelines, textbook 9.3 years Inconsistent indexing Patient Care Balas EA, Boren SA. Managing clinical knowledge for health care improvement. Yrbk of Med Informatics 2000; 65-70 Converting research to care 17 years to apply 14% of research knowledge to patient care!

27. So what’s broken? • Limited availability • Most successes are one-of-a-kind, often academic • Slow diffusion • Incompatibility among approaches • Little sharing of experience or capabilities • Little ability to share • Knowledge embedded in systems • Difficulty to extract, generalize, and replicate • Vendor incompatibilities, lack of standards Greenes

28. Non-technical factors • Isolated implementations • Getting the message out • Failures as well as successes • Regulatory issues • e.g., HIPAA • Financial constraints or disincentives • Cultural issues • “Culture eats strategy for lunch” • Leadership and commitment level • Human factors • Ease of use • Time requirements Greenes

29. Cedars-Sinai Experience

30. Technical factors • Infrastructure limitations • Vendor capabilities, platform • Foundational systems: EMR, KBs • Design approach • Lack of local expertise • Inability to capitalize on external expertise Greenes

31. Standards & sharing • Major area of activity in past two years • Gaining momentum • National Health Information Infrastructure (NHII) • National Electronic Disease Surveillance System (NEDSS) • Legislative initiatives • For quality and safety, support of NHII • Advocacy • Connecting for Health (Markle Foundation) • Leapfrog Group Greenes

32. Decision support has special requirements • Knowledge bases • Evidence-based, authoritative • e.g., drugs, interactions, contraindications, alternative forms • Decision rules • Calculations, constraints • e.g., limits, ranges, dose adjustments • Alerts and reminders • Guidelines • Regularly updated • Expressed in executable form Greenes

33. Executable KBs are expensive to develop & update • This argues for: • Standard representations for KBs • Shared content repositories • Tools • For authoring and updating • For adaptation, integration into host systems Greenes

34. Arden syntax was first approach to knowledge standardization • For Medical Logic Modules (MLMs) • single step rules/reminders • data section defining all variables • logic section defining conditions • action if the condition is true • Intended as a standard • First proposed early 1990’s • adopted by ASTM and then HL7 in mid-late ’90’s Greenes

35. Guideline standardization: the GLIF* experience • Goal of creating a common representation for sharing executable clinical guidelines • InterMed project of Harvard, Columbia, Stanford • Supported by NLM, AHRQ, Army * GuideLine Interchange Format Greenes

36. Flu vaccine guideline Asympto- matic Get age and occupation Health-care worker or Age>65? Yes No Give Flu shot Do Nothing

37. Decision step, in GLIF { name = “High risk determination”; condition = Boolean_criterion 1 { type = Boolean; spec = “HCW OR age>65”;}; destination = (Action_Step 3); otherwise = (Conditional_Step 2);} Greenes

38. Guideline authoring

39. Standardization effort • Clinical Guidelines Special Interest Group formed in HL7 • Part of Clinical Decision Support Technical Committee • Arden Syntax SIG also under this TC • First meeting in Jan ’01 Greenes

40. Standards approach • Work in HL7 CDS TC focusing on common infrastructure components: • vMR: an object-oriented virtual medical record subset for decision support • GELLO: object-oriented query & expression language – for all decision rules • Vocabulary management tools • Taxonomy of services invoked by rules • Work in HL7 CG SIG • Process/workflow model • Specific to guidelines Greenes

42. Knowledge content resources • Meds, interactions • Indications, allergies, contraindication, interactions • Templates for orders • Order sets • Rules • for order entry safety, quality, efficacy checking • for dose modification for age, renal disease, … • for monitoring for ADEs • Clinical guidelines & care pathways • Clinical trial protocols Greenes

43. Content dissemination • Government repositories • GenBank, Nat. Guideline Clearninghouse: guidelines.gov, ClinicalTrials.gov • Consortia, open source libraries • IMKI, OpenClinical, … • Professional specialty organizations • ADA, ACP, CAP, Medbiquitous, … • Commercial • First DataBank, Micromedex, … Greenes

46. Tools & infrastructure • For authoring, validation, dissemination, adaptation, execution • Most difficult problem • Must be done in conjunction with standards & content development • Should follow a lifecycle process Greenes

47. Conclusions - 1 • Health care safety & quality now a priority • Examples of successful approaches demonstrate potential benefits • Yet impediments to widespread experimentation, dissemination, and adoption Greenes

48. Conclusions – 2 • Concerted effort needed for integrating knowledge • Standards-based approaches • Sharing of knowledge, tools, and experiences • A joint activity of academic, vendor, health provider, payer, and public sectors Greenes