Knowledge Management Challenges in the Healthcare Delivery Market

1. Knowledge Management Challenges in the Healthcare Delivery Market Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Decision Support and Knowledge Management, Clinical Informatics Research & Development Partners HeatlhCare System, Inc.

2. Agenda • About Partners Healthcare • Knowledge Management and Informatics • Knowledge Application • Knowledge Discovery • Knowledge Asset Management • Challenges in Healthcare Delivery • Weak Organizational Alignment • Weak Investment in Asset Management • Implications for Clinical R&D • Implications for Personalized Medicine

3. Partners HealthCare • Massachusetts General Hospital, Brigham and Women’s Hospital and several other hospitals in the network • Licensed Beds 3196 • Births 18,478 • Admissions 134,991 • Patient Days 871,321 • Average LOS 5.31 • Total Outpatient Visits 2,324,073

4. Partners Information Systems • Much published on innovative use of informatics in healthcare (Bates, Teich, Glaser, Kuperman, Barnett, Chueh, and many others) • 800 applications • 520 active projects • 680 employees based in 19 locations • FY02 operating budget of $92.3M • FY02 capital budget of $47M • These are relatively generous numbers as a percentage of operating expenses

5. Some Current Clinical Knowledge Assets Developed at Partners • Medication Data Dictionary and DDIs • Inpatient alerts and interactive order rules • Gerios and Nephros for proactive filtering of drug doses for elderly and/or renal insufficient • Radiology Ordering decision support • Preventive health reminders • Outpatient lab result decision support • Outpatient documentation templates • Piloting outpatient drug-lab, drug-disease interactive reminders

6. Current State Challenges Typical of Many Academic Healthcare Delivery Organizations • 7 homegrown and 2 commercial CPOE systems, plan to evolve to “next generation CPOE” in next 5 years • Limited implementation of structured (encoded) clinical documentation • Proprietary approaches to knowledge encoding • Not re-usable or sharable • Much updating/maintenance is bottlenecked by resource constraints • Research datawarehouse in place, but struggle to expand in face of fragmented clinical systems environment

7. Typical Committee and Project Structures Related to Medication Safety IllustrateOrganizational Alignment Problem Information Technology Projects Committees and Departments • Physician Order Entry Team • Clinical Data Repository Team • Pharmacy System Team • Clinical Documentation Team • Electronic Medication Adminstration Team • Pharmacy and Therapeutics • Patient Safety • Quality or Performance Improvement • Policies and Procedures • Formulary • Infection Control

8. Medication Use Process Organization Medication Safety Steering Committee Chief Medical Officer, Chief Nursing Officer, Chief Information Officer, Chief Quality Officer • Physician Order Entry Team • Clinical Data Repository Team • Pharmacy System Team • Clinical Documentation Team • Electronic Medication Administration Team Interdisciplinary Medication Use Process Advisory Team Physicians, Nurses, Pharmacists, Clinical Systems Architects Information Technology Projects Committees and Departments • Pharmacy and Therapeutics • Patient Safety • Quality or Performance Improvement • Policies and Procedures • Formulary • Infection Control

9. Knowledge Management: The Core Processes Knowledge Application Knowledge Asset Management Knowledge Discovery

10. A Continuum of Clinical Decision Support and Knowledge Discovery* • Proactive • Surveillance • Interactive • Learning Reference Knowledge Linking Event Monitoring Safety Net Anticipation Understanding and Predicting Performance • Making the right decisions the easiest decisions • Monitoring patient data with passive decision support • Interceptingincorrect clinicaldecisions • Predictive Modeling • Case-based Reasoning • Learning Knowledge Repository *modified from the First Consulting Group Model of Clinical Decision Support

11. Medication Decision Support Categories at Partners INTERACTIVE DECISION SUPPORT FOR PHYSICIAN ORDER ENTRY ONLY: • Drug-lab interaction checking • Consequent order recommendations • Relevant lab display • Indication-required orders • Height, weight, allergy update required notification • Dose calculation tools • Intravenous to oral conversion recommendation on renewal of intravenous order when patient receiving other oral medications • Formulary substitution alerts • Antibiotic restriction alerts PROACTIVE DECISION SUPPORT • Gerios for elderly patient medication dosing • Nephros for dosing in renal insufficiency • Preventive health reminders • Problem-linked order sets REFERENCE INFORMATION • Drug-information knowledge linking via info button adjacent to drug name • Partners handbook provides access to numerous drug information databases • Planned drug-information knowledge linking via info button in electronic medication administration record in FY 04 SURVEILLANCE AND MONITORING • Drug-induced abnormal lab result notification of physician • Drug-induced abnormal lab result notification of pharmacist • Renal function decline in patient on renally excreted drug notification of physician and pharmacist INTERACTIVE DECISION SUPPORT FOR PHYSICIAN AND PHARMACIST: • Drug-allergy checking • Drug-drug interaction checking • Drug-food interaction checking • Drug-herb interaction checking • Drug-disease interaction checking

13. Laboratory Notification with consequent order recommendations

14. Alternate Procedures, Redirects, Drug-Allergy, Drug-Drug, Drug-Lab etc.

15. Gerios: Dose-filters for ageNephros: Dose-filters for renal function Inappropriately sedated elderly inpatients on average incur $5600 excess costs over expected for severity of illness

16. Preventive Reminders

17. Problem-level anticipatory decision support • Today, order sets and documentation templates are static which means that clinician must change them to personalize them to patient • We plan to use inferencing to dynamically generate problem-driven order sets and documentation templates that account for multiple co-morbidities • Must be able to incorporate future onslaught of gene diagnostic and prognostic data

18. Knowledge Application must anticipate these dimensions of the clinical encounter Clinical Standardization Standards of Practice, Role/Venue Requirements Billing/Regulatory Requirements User Personalization End-user workflow preferences Learning and User-defined Improvisation Patient Preferences

19. Poly-hierarchical inferencing with actionable advice – surveillance, interactive, or proactive mode

20. This is an example from clinical decision support company called Theradoc

21. A Continuum of Clinical Decision Support and Knowledge Discovery • Proactive • Surveillance • Interactive • Learning Reference Knowledge Linking Event Monitoring Safety Net Anticipation Understanding and Predicting Performance • Making the right decisions the easiest decisions • Monitoring patient data with passive decision support • Interceptingincorrect clinicaldecisions • Predictive Modeling • Case-based Reasoning • Learning Knowledge Repository *modified from the First Consulting Group Model of Clinical Decision Support

22. Current Initiatives • Quality data warehouse with Clinician Dashboards • Early identification of patients at risk for case management • Longer term knowledge discovery goals to use performance data to enhance knowledge repository • Need to evolve towards non-human dependent modes of knowledge acquisition

23. Knowledge Asset Management Infrastructure: • Analysis of clinical performance data to understand where knowledge deficits are to support performance goals • Authoring and support of virtual, asynchronous collaborative authoring by knowledge editors and leaders of research, safety and quality improvement initiatives (reference knowledge specs for encoding • Knowledge acquisition from commercial/etc knowledge bases • Validation and audit trail maintenance (meta-knowledge) • Inventory (knowledge librarian) • Publishing and Sharing • Reference information and knowledge model

24. What are the challenges today: • Healthcare delivery organizations purchase systems but don’t invest in knowledge asset management, they install plumbing • Vendors sell knowledge editors, not knowledge management support infrastructure • There is no repository of “best clinical IT practices” at a national level, few among the vendors • No knowledge encoding and representation standards to facilitate knowledge sharing

25. Partners-Wide Knowledge Management Model KNOWLEDGE ASSET MANAGEMENT Signature Initiatives and Sub-Committees set Enterprise-wide Strategy, Clinical Standards and Performance Measures Performance Feedback to Leaders, SMEs, Committees, and End-users Subject Matter Expert (SME) Panels Advise on Entity, Venue, Role, Specialty, Primary Care, Disease Management, and Safety related requirements for application function and knowledge bases Data Warehouse Decision Support Design Teams direct the design of cross-functional knowledge to be encoded Partners Genetics Computing Platform PERFORMANCE and OUTCOMES (KNOWLEDGE DISCOVERY) Applications for Virtual Collaborative Knowledge Authoring and Maintenance Knowledge Repository Clinical Workflow Applications and Services Knowledge Building Blocks Information Model Common Services Knowledge Editors DECISION SUPPORT (APPLIED KNOWLEDGE)

26. Care Applications • (Results, Observations, Orders, Tasks/Proc/Mar,Messaging, CDS, • Measurement) • and Knowledge Bases • Care Applications • (Results, Observations, Orders, Tasks/Proc/Mar,Messaging, CDS, • Measurement) • and Knowledge Bases Knowledge Asset Management: Translating Goals into a Knowledge Repository Taxonomy Goal Framework: Safety, Quality, Efficiency, Research Data/Knowledge Seeking Assessment Dx/Rx Decision Making Order Fulfillment, Communication and Coordination Billing Reporting Transfer/ Handoff CORE CARE PROCESS AUTOMATION TAXONOMY Medical Management, Research, and Reporting Clinical Knowledge for Personalized Medicine Taxonomy Reference Information Model Role and Venue Domain Taxonomy Requirements Care Applications and Knowledge Bases

27. MEDICATION USE PROCESS: Acetaminophen in a 2.5 Kg Premature Infant

28. Sample High-level Example Taxonomy for Knowledge Assets

29. Center for Clinical Knowledge Engineering Welcome to the National Knowledge Engineering Repository Go HEDIS Content search Advanced Search Filters (press Ctrl to select more than one): Clinical Discipline: Surgical Informatics Mode Cardiothoracic Surgery Interactive Rules Search File Hierarchy Interventional Cardiology Orthopedics Etc. Surveillance and Notifications Documentation Templates Etc. Knowledge Asset Management Toolkit Link to references, survey instruments, diagrams, descriptions, process flow diagrams, etc on Partners and VA approaches to asset management Clinical Discipline: Non-Surgical Age Cardiovascular Adult Submit Content to Editor Endocrinology Gastroenterology Etc. Pediatrics Neonate Etc. About Us Clinical Discipline: Safety Role Nosocomial Infection Control Nurse Medication Safety Decubitus Ulcer Prevention Etc. Physician Case Manager Etc. Clinical Discipline: Disease Management Venue Diabetes Mellitus CCU Congestive Heart Failure Multiple Sclerosis Etc. Ambulatory Care Emergency Department Etc.

30. Knowledge Specifications For Encoded Knowledge Vs Meta-knowledge about The knowledge

31. Future State KM Model Portal Collaborative Knowledge Authoring Tools Workflow Applications Meta-Knowledge Repository Knowledge-based Services Knowledge Repositories Information Model

32. Barriers to Success at the Intersectionof Clinical Informatics and KM • Leadership inadequately committed • Products inadequate to support processes • Business case intangible • Fear of exposure (technology increases transparency) • Few roadmaps to success are proven in the healthcare arena

33. Market Drivers will Propel Progress • Aging population: computer literate and population growth will outstrip service capacity, informatics must support self-management • Business community will aid transition from commodity to value based purchasing by employers and consumers, they know that the current inflation rate of the commodity is untenable • Leapfrog and Government are beginning to purchase quality • Genomics: personalized medicine will require technologies for personalization, these same technologies will enable more user-friendly safety solutions

34. Where are we?