Clinical KM 3.0 in a

1.0 EHR World

Tonya Hongsermeier, MD, MBA

CMIO

MU, ACO, PCMH, Safety, Readmission Prevention

Imperative to be Competent at Self-Improvement

Care

Context

Guided Data Review

Guided Decisions

& Orders

Guided Execution

of Decisions & Orders

Guided

Assessments

&Monitoring

of Interventions

Learning

Context

Identify

Gap in

Knowledge

or Care:

CDS Target

Implement

CDS

Knowledge

Measure Effectiveness

Of CDS Knowledge

Research&Discovery

Update/Acquire

Knowledge

Curate Assets Knowledge

Data

2

But: EHRs are not designed

as Collaboration-ware or Learning-Ware

Self-Improving Organizations Know:

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: Who decides what clinical problems to tackle with CDS, How to drive change adoption

Specification is Engineered into Production Generating

a Technical Specification

PARTICIPATION: How to enable Subject Matter Experts engagement in CDS design COMMODITIZATON: Not to build what you can buy STEWARDSHIP: How to allocate resources to steward the CDS knowledge

TRACEABILITY: To invest in technical tools to support build, dependency management, visualization, maintenance

MEASURE EFFECTIVENESS: To focus on measurable targets and invest in continuous program evaluation

3

Lahey Health KM Investments

• Governance and stewardship aligning systems

with business drivers

• Same regulations that force EHR adoption make

them unusable

• Focused on reconciling paradox of

standardization and personalization of care

• 3rd party content (usual suspects)

• Externalization of CDS content from EHR to

support curation

• Collaboration Platform (JIVE)

Portalization Supports Transparency, Curation, De-Silo-ization of CDS Content

Build-trackers and Stove-piped EHR content editors don’t cut it

Jive: Facebook plus Twitter plus Wikipedia plus

Survey monkey plus Expertise Locator plus…

Jive: Mobile apps to further engage…

KM Platforms = Convergence

Content Management Social Interaction Management

Process/Transaction Management

•Email

•IM

•Corporate Twitter

•Portals/Virtual Rooms

•Teleconferencing

•Desktop Sharing

•Idea Capture

•Expertise Locators

•Social Q&A

•CMS

•curation,versioning,auditing

•Wikis, Blogs, RSS

•Database Management

•Document Management

•Clouds

•Semantics

•Tagging

•Taxonomies/Folksonomies

•Search

•User Profiles/Contacts

•Rules Engines

•Workflow Engines

•Task Management

•Scheduling/Tracking

Leaders:

•EMC

•Microsoft

•IBM

•Oracle

•OpenText

Leaders:

•Telligent

•Jive

•Atlassian

•SocialText

•NewsGator

Imagine if EHRs could “Learn”

how to help Users/Health Systems Self-Improve

how to anticipate user workflows and information needs

Amount of data

Pro

ductivity o

f S

earc

h

Databases

Web 1.0 1990 - 2000

The World Wide Web

PC Era 1980 - 1990

The Desktop Keyword search

Directories

2000 - 2010 Web 2.0

The Social Web

Files & Folders

Tagging

Natural

language

search

2010 - 2020

Web 3.0

The Semantic Web

Automated Content

Analysis

2010 - 2020

Web 3.0 User Modeling

User profiling

Health System Profiling

** From: Making Sense of the Semantic Web, BY Nova Spivack

The MetaWeb

Web 4.0

We are about here, can’t find

pt. data or knowledge in the

swamp

Intelligent Agents

Connected Intelligence

EHR vendors today impose enormous costs

of conversion and curation of Data, Knowledge, Behavior