GEM & HL7

Richard N. Shiffman, MD, MCIS,

Abha Agrawal, MD, Roland Chen, MD, Bryant Karras, MD,

Luis Marenco, MD, Kristi Polvani, BS, Sujai Nath, MD

Peter Gershkovich, MD, Aniruddha Deshpande, MD

Yale Center for Medical Informatics

NOT!!

http://ycmi.med.yale.edu/GEM

richard.shiffman@yale.edu

Use And Satisfaction 8 physicians—not members of the GEM

development team (UNC, UAB, Hopkins, Yale) marked up a guideline

CONCLUSIONS: Subjects were able to model the content of the guideline using GEM elements.

“satisfactory” Improved editing tools would facilitate

translation Result: GEM Cutter

Karras, Proc AMIA 2001

GEM-Q / GEM-Q OnLine XSL stylesheet extracts info relevant

to quality appraisal from GEMified gl Pass to Shaneyfelt and Cluzeau

instruments Output is a quality report card Valued by AAP in gl devel process Available for ad hoc reports on WWW

Agrawal, Medinfo 2002

GEM to Arden Relevant components for Arden

extracted and used to pre-populate MLMs

Agrawal, Proc AMIA 2002

Implementation GEMified document can

dynamically generate data collection screens and trigger appropriate recommendations based on guideline logic

Proof of concept Applied to NHLBI asthma guideline

and CDC TB screening guidelineGershkovich, Proc AMIA 2002

Knowledge extractor XSL extracts and formats guideline

info relevant to implementation

In use ~100 guidelines have been

GEMified Groups in US, UK, Germany, Italy,

and NZ are using GEM

Funded by NLM: To improve the quality and implementability of an AAP

guideline w/ feedback during development. (Using GEM-Q) To create tools that transform GEM-encoded guidelines

into CDSS. A generic process and software tools will be developed to translate GEM-encoded guidelines into systems that can improve the process of care.

To extend and refine the GEM model to serve as a precise, comprehensive, and consistently applied ontology of guideline-related concepts. (Logic, link, algorithm elements; application of advanced X-technologies)

Logical Analysis with Highlighters

Recommendation 3

If an infant or young child 2 months to 2 years of age with unexplained fever is assessed as being sufficiently ill to warrant immediate antimicrobial therapy, a urine specimen should be obtained by SPA or bladder catheterization; the diagnosis of UTI cannot be established by a culture of urine collected in a bag. (Strength of evidence: good) Urine obtained by SPA or urethral catheterization is unlikely to be contaminated...

UTI Recommendation in XML

<decision.variable id=dv1>age</decision.variable>

<value>2 months to 2 years</value>

<decision.variable id= dv2>unexplained fever </decision.variable>

<decision.variable id=dv3>sufficiently ill to warrant immediate antimicrobial therapy </decision.variable>

<action id=a1>obtain urine specimen by SPA</action>

<action id=a2>obtain urine specimen by catheterization</action>

<reason>the diagnosis of UTI cannot be established by a culture of urine collected in a bag</reason>

<evidence.quality>Good</evidence.quality>

<logic>IF (dv1=2m-2y) AND dv2 AND dv3 THEN a1 OR a2</logic>

<link>after: Recommendation 2</link> <link>Diagnosis section</link>

• Operationalizing abstract constructs

• Determining when to collect data, when to deliver advice (site-specific)

Adding guideline meta-information

Sufficiently ill to warrant immediate antimicrobial therapy

Febrile Interactive Tolerating oral fluids

or

Whither GEM in HL7

• GEM users asking why HL7 is creating a new architecture

TitleCitation

Release DateAvailability

ContactStatus

Companion DocumentAdaptation

Developer NameCommittee Name

Funding

EndorserComparable Guideline

Health PracticesCategory

Target PopulationRationaleObjective

Available OptionsImplementation Strategy

Health OutcomesExceptions

Care SettingClinician Users

Evidence CollectionEvidence Time Period

Evidence GradingCombining Evidence

Specification of Harm/BenefitQuantification of Harm/Benefit

Value JudgmentPatient Preference

Qualifying StatementCost Analysis

RecommendationConditional (decision variable) .

Action .

Logic .

Reason .

Strength of Recommendation .

Evidence Quality . . .Cost .

Certainty .

AlgorithmEligibilityDefinition

External ReviewPilot Testing

Expiration DateScheduled Review

Developer

Purpose

Method

Knowledge

Audience

Identity

TestingRevision

HS INF

GEM: Distinguishing Characteristics

Conceived and built in XML Multi-platform Open standard Human-readable yet can be processed by

machine DTD/schema allows file validation Markup can be performed by non-programmers …

GEM passed balloting as a standard (ASTM E2210-02)

Goals Comprehensive – capable of

expressing all the knowledge contained in guidelines. Health service models cannot express recommendations in sufficient detail; informatics models inadequate to model constructs that express and support guideline validity

Goal 2 Expressively adequate to

convey the complexities and nuances of clinical medicine while remaining informationally equivalent to the original guideline; tagged elements store actual language

Goal 3 Flexible – must be able to deal

with variety and complexity of guidelines; permit modeling at high and low levels of granularity

Goal 4 Comprehensible – the model

should match the stakeholder’s normal problem-solving language and allow domain experts to describe their knowledge with little effort; markup should not require a background as a programmer

Goal 5 Shareable across institutions

Goal 6 Reusable - across all phases of

the guideline lifecycle

GEM: Major Components

Guideline

IdentityPurpose

Intended Audience

Method ofDevelopment

KnowledgeComponents

Testing RevisionPlan

TargetPopulation

DocumentHeader

DocumentBody

Developer

Unit of implementabilityId

enti

ty

Dev

elop

er

Tar

get P

opul

’n

Pur

pose

Met

hod

of D

ev

Rev

isio

n P

lan

Pil

ot T

esti

ng

Inte

nded

Use

r

Recommendation

Identity

Title CitationRelease

DateAvailability Status

CompanionDocument

Adaptation

Length Electronic Print ContactPatient

Resource

Identity

Developer

DeveloperName

CommitteeName

Funding EndorserComparable

Guideline

DeveloperType

CommitteeMember

MemberExpertise

CommitteeExpertise

Developer

NGC ControlledVocabulary

Purpose

Main Focus Category Rationale ObjectiveAvailable

OptionImplem’nStrategy

HealthOutcome

Exception

Purpose

Intended Audience

UserCare

Setting

ClinicalSpecialty

ProfessionalGroup

IntendedAudience

Method of Development

Descrip’nEvidenceCollection

EvidTime

Period

MethodEvidenceGrading

CostAnal

Spec’nHarm

Benefit

RoleValue

Judgmt

RolePt

Pref

QualifyingStatement

Descrip’nEvidence

Combinat’n

QuantHarm

Benefit

MethodEvid

Collect

NumberSourceDocs

RatingScheme

MethodEvidence

Combinat’n

Methodof

Development

Target Population

Eligibility Age

InclusionCriterion

ExclusionCriterion

Sex

TargetPopulation

Testing

ExternalReview

PilotTesting

ReviewMethod

Testing

Revision Plan

Expiration Scheduled Review

RevisionPlan

Knowledge Components

Recommendation

Conditional

AlgorithmDefinition

Term

TermMeaning

ImperativeSyncStep

ActionStep

Condit’lStep

BranchStep

KnowledgeComponents

Conditional

Value

DecVar

Action FlexbltyReason EvidQuality

RecmdnStrength

Logic Cost Link

Dec VariableDescripn

TestParam

DecVar

Cost

Sensitivity Specificity Predictive Value

ActionBenefit

ActionRiskHarm

ActionDescripn

ActionCost

Ref Certainty

Recommendation

Conditional

KnowledgeComponents

Conditional

Value

DecVar

Action FlexbltyReason EvidQuality

RecmdnStrength

Logic Cost Link

Dec VariableDescripn

TestParam

DecVar

Cost

Sensitivity Specificity Predictive Value

ActionBenefit

ActionRiskHarm

ActionDescripn

ActionCost

Ref Certainty

Recommendation

Conditional

KnowledgeComponents

What HowMuch Where When Who

ActionsWhat How

(much)Where

When Who

Medication

Lab test

Procedure

Consultation

Pt Education

Disposition

GEM Cutter

Knowledge customization

• Add meta-information necessary for implementation, e.g.• Identifier, clinical source, interface, prompt, mechanism

of actions• Local adaptation

• Translation of national recommendations into systems that operate at a local level

• Must account for legitimate variations in clinical settings, populations served, and resources available

• Danger: protection of professional habit or economic self-interest

Strengths of GEM Hierarchy is relatively intuitive Elements are derived from published

models Value-added applications have been

developed Stable >1 year Designation as a standard

GEM Limitations

Has been “frozen” > 1 year Not comprehensive (as demonstrated by

CPGA) Need guidelines for extension

GEM file only as good as guideline document

Requires training to use correctly Need to develop <link>, <logic>, and

<algorithm> elements