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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 Managing Evidence at the Speed of Change Change

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Page 1: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Tonya Hongsermeier, MD, MBACorporate Manager,

Clinical Knowledge Management for Decision Support

Clinical Informatics Research and Development,

Partners Healthcare System

Managing Evidence at the Speed of ChangeManaging Evidence at the Speed of Change

Page 2: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

OutlineOutline

• 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

Page 3: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Current State of Translating Current State of Translating Evidence into PracticeEvidence 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. AHRQGandhi et al, NEJM 2003;348(16):1556-1564 Gurwitz et al, JAMA 2003;289:1107-16McGlynn et al, NEJM 2003;348(26):2635-45.

Page 4: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

•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

Page 5: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Computer-Based Clinical Computer-Based Clinical Decision SupportDecision 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 1998And Unpublished

Kaushal R, et al. Arch Intern Med. 2003

Page 6: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

The Volume and Velocity The Volume and Velocity of Knowledge Processing Required of Knowledge Processing Required for Care Delivery Growsfor 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

Page 7: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

When do you order this test?When do you order this test?How do you use the test result?How do you use the test result?

June 25, 2003Roche Holding AG is launching the first gene test able to predict how a personwill react to a large range of commonly prescribed medicines, one of the biggestforays yet into tailoring drugs to a patient's genetic makeup.The test is part of an emerging approach to treatment that health expertsexpect could lead to big changes in the way drugs are developed, marketed andprescribed. For all of the advances in medicine, doctors today determine thebest medicine and dose for an ailing patient largely by trial and error. Thefast-growing field of "personalized" medicine hopes to remove such risks andalter the pharmaceutical industry's more one-size-fits-all approach in makingand selling drugs.

Leading the News: Roche Test Promises to Tailor Drugs to Patients --- Precise Genetic Approach Could Mean Major Changes In Development, Treatment

Page 8: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

When Knowledge Changes…When Knowledge Changes…

How quickly can you change the content of your rules, order sets, templates, and reports?

Page 9: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Clinical Decision Support ChallengesClinical 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?

Page 10: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

ImprovisationPatient Preferences

User Quality of LifeEnd-user role, workflow

preferences

Quality PerformanceEvidence, Safety

Process RequirementsRegulatory Requirements

Three Facets of Three Facets of Clinical Decision SupportClinical Decision Support

Page 11: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Typical Vendor System ChallengesTypical 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

Page 12: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

New OpportunitiesNew 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

Page 13: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Where are we?

Page 14: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Partners has a long track-record in Partners has a long track-record in applied clinical decision supportapplied 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

Page 15: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Heterogeneous InfrastructureHeterogeneous 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

Page 16: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Knowledge ManagementKnowledge ManagementStrategic GoalsStrategic 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

Page 17: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Knowledge Life-Cycle Challenges:

Committee, Department, Researcher, or Other

Proposes to Implement Content

Guideline is Defined and Validated

Functional Knowledge SpecificationFor 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 orimpact on clinical outcomes impact to direct updating•No content management tools to support process and ensure timeliness

Specification isEngineered into Production Generating

a Technical Specification

Page 18: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Tactics we have deployed: 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

Page 19: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

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

PCHIP&T

Pharmacotherapy

Quality Disease Management Trend Management

SMEGroups

MedicationKnowledgeCommittee

BWHPrecipio

Imaging Studies

MGHROE

Production Knowledge Repositories

Knowledge Analysts facilitate

Knowledge Editors update

Page 20: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

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

Page 21: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Compare Content Across OrganizationsCompare Content Across Organizations

Page 22: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Geriatric Dosing: Geriatric Dosing: Case Example of Collaborative Content Case Example of Collaborative Content Development using Documentum E-RoomDevelopment 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

Page 23: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

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 moveon to new jobs and folders get lost…..

Must maintain the “Metaknowledge”:the who, what, when, where, and why about decision support content,

Page 24: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

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

Page 25: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners
Page 26: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners
Page 27: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners
Page 28: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Votes

Page 29: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners
Page 30: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners
Page 31: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Other poll approaches

Page 32: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners
Page 33: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

E-room report illustrating aggregation of expert input,dramatically improves efficiency for subject matter expertsand medication services design teams

Vioxx alert shared, removed from database

Page 34: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

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

Page 35: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Diabetes:Diabetes:Case example of the Case example of the knowledge editing challenge 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

Page 36: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

MethodologyMethodology

• 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

Page 37: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Editing Evidence into Editing Evidence into Clinical Decision Support --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

Page 38: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Composite Decision Support Application: Diabetes Management

Guided Data Interpretation Guided Observation Capture Guided Ordering

Page 39: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Managing change across Managing change across content types, across siloscontent 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

Page 40: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

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

CollaborationServices

Knowledge Management Staging Area

3rd PartyContentNDDFZynx

MicromedexClineguide

Etc.

Validation &

Integration

Production Knowledge Bases

Transaction Knowledge Repositories

WebServiceLookup

Partners ServicesPartners ServicesAnd ApplicationsAnd Applications

Documentum Deployment Agent

Quality Data ManagementKnowledge Repositories

Conceptual Architecture for Knowledge Management Conceptual Architecture for Knowledge Management

Page 41: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Managing Evidence at the Speed of ChangeManaging 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

Page 42: Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management for Decision Support Clinical Informatics Research and Development, Partners

Questions?Questions?

Never, ever think outside of the box!!!