1. Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners Healthcare System Managing Evidence at the Speed of Change

2. Outline New Market Demands for Evidence-based Practice Challenges and Opportunities of Integrating Evidence-based Decision Support with the Electronic Health Record The Partners Healthcare Model for Managing Evidence at the Speed of Change

3. Current State of Translating Evidence into Practice 17 year innovation adoption curve from discovery into accepted standards of practice Even if a standard is accepted, patients have a 50:50 chance of receiving appropriate care, a 5-10% probability of incurring a preventable, anticipatable adverse event The market is balking at healthcare inflation, past utilization management measures have not succeeded Carolyn Clancy, MD, Dir. AHRQ Gandhi et al, NEJM 2003;348(16):1556-1564 Gurwitz et al, JAMA 2003;289:1107-16 McGlynn et al, NEJM 2003;348(26):2635-45.

4. Employers and consumers are now paying for performance They will not wait for the data to be right or fair because they believe if they wait, it never will be Instead, they are using the process of rewarding performance to force the healthcare providers to “make the data right” Defined Contribution lays even greater purchasing responsibility at the door of the consumer

5. Computer-Based Clinical Decision Support Not a panacea, doesn’t substitute for organizational alignment required for bringing evidence to practice, but when done well…. 55-83% decrease in hospital non-intercepted serious ADEs using CPOE 22-78% increased adherence to preventive health reminders At Partners, proprietary Drug-Drug Interaction checking intercepts 5% of physician orders, physicians change their decision about 33% of time Bates, JAMA 1998 And Unpublished Kaushal R, et al. Arch Intern Med. 2003

6. The Volume and Velocity of Knowledge Processing Required for Care Delivery Grows Medical literature doubling every 19 years 2 Million facts needed to practice A typical drug order today, decision support accounts for, at best, Age, Weight, Height, Labs, Other Active Meds, Allergies, Diagnoses Already, there are 3000+ molecular diagnostic tests on the market, genomics and personalized medicine will increase the speed of change of evidence exponentially Covell DG, Uman GC, Manning PR. Ann Intern Med. 1985 Oct;103(4):596-9

7. When do you order this test? How do you use the test result? June 25, 2003 Roche Holding AG is launching the first gene test able to predict how a person will react to a large range of commonly prescribed medicines, one of the biggest forays yet into tailoring drugs to a patient's genetic makeup. The test is part of an emerging approach to treatment that health experts expect could lead to big changes in the way drugs are developed, marketed and prescribed. For all of the advances in medicine, doctors today determine the best medicine and dose for an ailing patient largely by trial and error. The fast-growing field of "personalized" medicine hopes to remove such risks and alter the pharmaceutical industry's more one-size-fits-all approach in making and selling drugs. Leading the News: Roche Test Promises to Tailor Drugs to Patients --- Precise Genetic Approach Could Mean Major Changes In Development, Treatment

8. When Knowledge Changes… How quickly can you change the content of your rules, order sets, templates, and reports?

9. Clinical Decision Support Challenges How do we supply meaningful decision support that both improves quality of care for patients and quality of life for clinicians (and self-managing patients)? How do we affordably develop, acquire and maintain the knowledge bases required to deliver meaningful decision support?

10. Improvisation Patient Preferences User Quality of Life End-user role, workflow preferences Quality Performance Evidence, Safety Process Requirements Regulatory Requirements Three Facets of Clinical Decision Support

11. Typical Vendor System Challenges Task-interfering approach to decision support - Siskel and Ebert Model Editors don’t support “content vetting” process or the development of disease management approaches Labor of developing and maintaining decision support knowledge is vastly underestimated Consequently, clinical systems implementations are under-resourced with adequate knowledge to meet workflow and quality needs

12. New Opportunities Content suppliers are emerging for decision support content: Primarily order sets and some rules Zynx, Wolters-Kluwer, Micromedex New systems are available to support the vetting process without required attendance at committee meetings New systems are available that make it possible to manage knowledge at the “goal level” Manage Diabetes or Coronary Artery Disease related knowledge rather than managing just rules or order sets or documentation templates

13. Where are we?

14. Partners has a long track-record in applied clinical decision support Physician-oriented Drug-Drug Interaction Checking Inpatient interactive order rules and notification alerts Inpatient templated orders (hundreds) Proactive Dosing support for Geriatric, Pediatric, Neonatal, Renally-Impaired, and Heme-Onc populations Radiology Ordering decision support Preventive health reminders Documentation templates Disease management reports/dashboards (Diabetes, others to follow) Outpatient drug-lab, drug-disease interactive reminders

15. Heterogeneous Infrastructure 5 internally developed POE applications (inpatient and outpatient) 3 versions of Meditech and Siemens POE Despite this heterogeneity: Many sites share common expert dosing services Many sites share a common allergy repository Moving toward common problem list and medication list over the next 2 years Partners is very committed to maintaining high- quality common logic to support Evidence-based Practices

16. Knowledge Management Strategic Goals Reduce the cost and increase the speed of translation of clinical innovation and evidence into clinical practice Proactive, anticipatory decision support -- avoid “interruptive” decision support Improve Partners’ organizational effectiveness as a learning organization through data-driven performance improvement Align knowledge assets with business, regulatory, safety and quality requirements, Only build what we cannot buy Partners has created some of the best decision support in production in the world, the goal here is to keep the knowledge up to date

17. Knowledge Life-Cycle Challenges: Committee, Department, Researcher, or Other Proposes to Implement Content Guideline is Defined and Validated Functional Knowledge Specification For Encoding is Designed and Validated Ongoing Revisions or Eventual Sunset Of Encoded Guideline Governance and Stewardship Inadequate tools and personnel to support vetting and update of knowledge Lack of transparency of knowledge already in production Bottlenecks the time it takes to agree on content Project and resource competition with other engineering projects, prioritization processes unclear Editors inadequate Lack of access to analytic data available on decision support content or impact on clinical outcomes impact to direct updating No content management tools to support process and ensure timeliness Specification is Engineered into Production Generating a Technical Specification

18. Tactics we have deployed: Transparency and Governance (2004): Build and deploy a document library to provide enterprise wide access to information about of decision support knowledge in production Worked with existing committees to evolve more effective governance models for content Collaboration and Content Life-cycle Tools (2005): Collaboration Portals aligned with clinical goals of Partners Content Management infrastructure to support content management processes using lifecycles and workflows (knowledge maintenance) Content Editing Re-architecture (2006-7): Reduce the editing bottlenecks Once decision is made for knowledge to change, change will be implemented rapidly

19. Clinical Content Committee: Prioritizes and Sponsors Operational Stewardship of Content Safety CAD/CHF, Diabetes, Heme-Onc, Asthma, ID/HIV, Nephrology, Psych Disease Areas Adult, Geriatrics, Pediatrics, Women’s Health Primary Care PCHI P&T Pharmacotherapy QualityDisease ManagementTrend Management SME Groups Medication Knowledge Committee BWH Precipio Imaging Studies MGH ROE Production Knowledge Repositories Knowledge Analysts facilitate Knowledge Editors update

20. The Knowledge Management Portal: Can aggregate all content for Coronary Artery Disease Management

21. Compare Content Across Organizations

22. Geriatric Dosing: Case Example of Collaborative Content Development using Documentum E-Room New pay-for-performance incentive for Geriatric Prescribing at Partners Gerios in production in one inpatient order entry system for several years, must deploy across the enterprise Content review showed gaps (missing drugs) and need for update to accommodate all care settings 160+ Row Decision Table not easily reviewed with Outlook, geriatricians don’t have time for meetings Even if this is commercial content, tools like this are still needed for committee review Outcome: successful review, updated geriatric dosing is now integrated with more order entry applications

23. Example: Setting aside the challenge of “who decides on content”, This screenshot shows a common approach to decision support design: MS office folders, documents related by title and common location only, Difficult to know what changed from one version to next or why, people move on to new jobs and folders get lost….. Must maintain the “Metaknowledge”: the who, what, when, where, and why about decision support content,

24. Partners maintains a geriatric dosing database that supports either default dosing more appropriate for geriatric population or substitution recommendations

28. Votes

31. Other poll approaches

33. E-room report illustrating aggregation of expert input, dramatically improves efficiency for subject matter experts and medication services design teams Vioxx alert shared, removed from database

34. After updating the content in the medication knowledge base, updates are published quarterly to the portal to share across sites, and we are still working with vendors to achieve integration of Gerios dosing with Meditech and Siemens

35. Diabetes: Case example of the knowledge editing challenge Epidemic, associated with obesity Estimated avg $21,000/year per diabetic employee in absenteeism, disability and medical costs (study of 6 employers with 375,000 employees) HEDIS measures drive reimbursement Maintain HbA1c <7 (diet, oral agents and/or insulin) If Renal Disease and no contraindication, should be on ACE inhibitor or ARB If lipid disorder and no contraindication, should be on a statin like lipitor

36. Methodology Identify relevant guidelines to achieve a given measurement goal Decompose guidelines into the draft components for rules, documentation templates, order sets, and reporting Evaluate feasibility of current EHR system to deploy Determine what content can be purchased Establish baseline performance Implement content Re-measure and refine

37. Editing Evidence into Clinical Decision Support -- Imagine a HEDIS measure: Patients with Diabetes and Renal Disease or Hypertension should be on an ACE inhibitor or ARB unless there is a “contraindication” Must define who has Diabetes, Renal Disease and Hypertension (problems, documentation, medications, test results) Define “Contraindication to ACEi or ARB” Allergy, Cough symptom on adverse reaction list Hyperkalemia on problem list or high K test result Pregnancy (Many components) Patient refuses Must be the same in rules, documentation templates, and reporting tools

38. Composite Decision Support Application: Diabetes Management Guided Data InterpretationGuided Observation CaptureGuided Ordering

39. Managing change across content types, across silos The rate of change for contraindication definition today is very slow, it’s a challenge for most EHRs to provide decision support for this With the advent of molecular medicine, this rate of change could become daily Our approach to build a knowledge staging infrastructure that enables our editors to manage propagation and inheritance across related content areas Change in one content area can trigger notifications to edit related content or to validate and automate propagation to relevant content

40. eRoom Content Vetting and Content Editing Portals Knowledge Search, Retrieval, and Reporting Services Documentum Content Management Server Health Language Inc. Terminology Complex Definitions Rules, Templates, Reports Editors Meta- Knowledge Collaboration Services Knowledge Management Staging Area 3 rd Party Content NDDF Zynx Micromedex Clineguide Etc. Validation & Integration Production Knowledge Bases Transaction Knowledge Repositories Web Service Lookup Partners Services And Applications Documentum Deployment Agent Quality Data Management Knowledge Repositories Conceptual Architecture for Knowledge Management

41. Managing Evidence at the Speed of Change Requires strong leadership commitment to invest in knowledge, people and systems to manage knowledge Health systems vendors will need to vastly improve their capabilities to support knowledge acquisition and usable decision support Standards for content representation and interoperability remain a challenge, the current state benefits vendors and consultants Market forces (aging, genomics, pay-for-performance) create decision support imperatives that will drive technology innovation

42. Questions? Never, ever think outside of the box!!!