DecreasingVariability in Health Care

HST950

Decision Systems Group Brigham

amp Womenrsquos Hospital

Harvard Medical School

Harvard-MIT Division of Health Sciences and Technology Peter Szoiovits PhD

HST950J Medical Computing Isaac Kohane MD PhD

Lucila Ohno-MachadoMD PhD

Variability in Health Care

Decision support systems

1048708Integration of guidelines into practice 1048708Decrease variability homogenize

1048708Knowledge discovery in biomedical data 1048708Increase variability customize

1048708Support for clinical trials

Guidelines and clinical protocols

What are they

Why computerize

Knowledge representation

Application in breast cancer protocol

eligibility with uncertain information

Decreasing practice variation

Studies demonstrate huge variability in practices

What are clinical guidelines Institute of Medicine definition

systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances

A recommended strategy for managementof a medical problem in order to 1048708

Reduce inappropriate use of resources $$$$$$ 1048708 Reduce practice variation 1048708 Improve outcomes

Conventional publicationGuidelines can be developed and published by 1048708

A medical institution to be used locally National and international organizations used by many medical institutions

Conventional publication 1048708 In journals and textbooks 1048708 Booklets or guideline summaries 1048708 Compilations of guidelines for reference

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
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• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Variability in Health Care

Decision support systems

1048708Integration of guidelines into practice 1048708Decrease variability homogenize

1048708Knowledge discovery in biomedical data 1048708Increase variability customize

1048708Support for clinical trials

Guidelines and clinical protocols

What are they

Why computerize

Knowledge representation

Application in breast cancer protocol

eligibility with uncertain information

Decreasing practice variation

Studies demonstrate huge variability in practices

What are clinical guidelines Institute of Medicine definition

systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances

A recommended strategy for managementof a medical problem in order to 1048708

Reduce inappropriate use of resources $$$$$$ 1048708 Reduce practice variation 1048708 Improve outcomes

Conventional publicationGuidelines can be developed and published by 1048708

A medical institution to be used locally National and international organizations used by many medical institutions

Conventional publication 1048708 In journals and textbooks 1048708 Booklets or guideline summaries 1048708 Compilations of guidelines for reference

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
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• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Guidelines and clinical protocols

What are they

Why computerize

Knowledge representation

Application in breast cancer protocol

eligibility with uncertain information

Decreasing practice variation

Studies demonstrate huge variability in practices

What are clinical guidelines Institute of Medicine definition

systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances

A recommended strategy for managementof a medical problem in order to 1048708

Reduce inappropriate use of resources $$$$$$ 1048708 Reduce practice variation 1048708 Improve outcomes

Conventional publicationGuidelines can be developed and published by 1048708

A medical institution to be used locally National and international organizations used by many medical institutions

Conventional publication 1048708 In journals and textbooks 1048708 Booklets or guideline summaries 1048708 Compilations of guidelines for reference

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
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• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Decreasing practice variation

Studies demonstrate huge variability in practices

What are clinical guidelines Institute of Medicine definition

systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances

A recommended strategy for managementof a medical problem in order to 1048708

Reduce inappropriate use of resources $$$$$$ 1048708 Reduce practice variation 1048708 Improve outcomes

Conventional publicationGuidelines can be developed and published by 1048708

A medical institution to be used locally National and international organizations used by many medical institutions

Conventional publication 1048708 In journals and textbooks 1048708 Booklets or guideline summaries 1048708 Compilations of guidelines for reference

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

What are clinical guidelines Institute of Medicine definition

systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances

A recommended strategy for managementof a medical problem in order to 1048708

Reduce inappropriate use of resources $$$$$$ 1048708 Reduce practice variation 1048708 Improve outcomes

Conventional publicationGuidelines can be developed and published by 1048708

A medical institution to be used locally National and international organizations used by many medical institutions

Conventional publication 1048708 In journals and textbooks 1048708 Booklets or guideline summaries 1048708 Compilations of guidelines for reference

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Conventional publicationGuidelines can be developed and published by 1048708

A medical institution to be used locally National and international organizations used by many medical institutions

Conventional publication 1048708 In journals and textbooks 1048708 Booklets or guideline summaries 1048708 Compilations of guidelines for reference

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Types of guidelines

Risk assessment

Chronic disease management 1048708 Diabetes asthma hypertension

Screening

Diagnosis and workup

Protocol-based care (clinical trials)

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Clinical Trial ProtocolsGoal is to intervene in a random part of the eligiblepatient and leave the other part with current standard ofcareCarefully selected population with few comorbidities (other diseases) 1048708Homogeneous care in each arm to investigate statistical significance of differences

Select patientsRandomize into

-intervention arm -control arm

Compare outcomes

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Where do the recommendations come fromPanel of experts (most common)

Hard to get experts to agree on anything 1048708Decision analysis models (least common)1048708Difficult to obtain probabilities and utilities 1048708 Observational studies1048708Small numbers may lead to wrong recommendations Clinical trials1048708Controlled populations strict eligibility criteria

A major problem is to match the patient in front of you with carefully selected patient population used in the trials

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Ways of helping implement guidelinesclinical trials

Help authors to create guidelines that

make sense (verify the ldquologicrdquo)

Eligibility determination for a variety

of competing guidelinesprotocols

Assistance in implementing the

prescribed actions

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Eligibility determinationThere are hundreds of guidelines and clinical trials out there

Automated eligibility could warn providers of guidelinesprotocols that match the patient

MAJOR problem uncertainty in patient status (tests to be done info not available)

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Increase versus decrease variability

Recommendations are based on

ldquoaveragerdquo or ldquomoderdquo patient

ldquoModerdquo patient may not exist

If more info is available why not

use it

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Example

Consent forms for interventional

cardiology procedures

Acknowledgement that risk of death in

hospital is about 2

Who is at 2 risk

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Why people want to computerize guidelines

Provide automatic decision support 1048708 Applied to individual patients 1048708 During the clinical encounter

Ambiguities in guidelines may be reduced Software tools and guideline models can promote spe

cifying logic precisely

Can integrate guidelines into workflow 1048708 Patient-specific guideline knowledge available at point of care

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Computer-interpretable guidelineInteractive guidelines 1048708

Enter patient parameters to traverse

guideline

Guidelines embedded in EPR Systems

Automated remindersalerts 1048708

Decision support and task management

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellip Why people want to computerize guidelinesCan be used for quality assurance

Guideline defines gold-standard of care Perform retrospective analysis to test if patients were treated appropriately

Allows for interactive visualization ofguideline logic 1048708eg allows one to focus on relevant sections of flowchart

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Why share guidelines

Provide consistency in guideline

interpretation

Reduce cost of guideline development

Minimize misinterpretations and errors

through the process of public review

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Challenges in sharing guidelines

Local adaptation of guidelines 1048708

Must allow care sites flexibility in

modifying guidelines for 1048708 Availability of resources and expertise

Local workflow issues

Practice preferences

Differences in patient population

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Patient and Provider Preferences

Who cares

Who elicits preferences for a particular

patient

How does this get taken into account

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Patient and Clinician Vocabulary How Different Are They

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipChallenges in sharing guidelines

Integration with information systems

Match patient data in EPR to terms in

guideline 1048708

Match recommendations in guideline to

actions in order entry system

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Guideline modelsGuideline models make explicit

Knowledge concepts contained in a guideline

1048708Structure of the concepts and relationships among them

1048708Scope of the model 1048708Types of guidelines eg alerts vs multi-

encounter guidelines 1048708Level of detail eg structured or text

specification

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Models for guidelines and rulesIndividual decision rules (single

step) 1048708Arden Syntax

Multi-step guidelines modeled as

sets of guideline tasks that are connected in a graph 1048708

nested

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Arden Medical Logic ModulesFormat for representation and sharing

of single medical decision

Each medical decision (rule) is called

a medical logic module (MLM)

Suitable for alerts and reminders

A guideline may be represented by a

chained set of MLMs

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipArden MLM

Simplified exampledata 1048708

potassium_storage = event lsquo1730rsquo 1048708potassium= read last lsquo32471rsquo

1048708evoke potassium_storage (to EPR)1048708logic potassium gt 5 mmolL1048708action write ldquoPotassium is significantly elevatedrdquo

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipArden Syntax

Standard published by ANSI

Part of HL7 activity

Supported by many commercially- available hospital informationsystems

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipModels for multi-step guidelinesMulti-step guidelines modeled as hierarchical sets of nested guidelinetasks 1048708

EON 1048708PRODIGY 1048708PROforma 1048708Asbru 1048708GLIF

This is an incomplete list

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

EONDeveloped by Tu and Musen (Stanford)Extensible collection of models whereguideline developers select modelingsolutions from a toolkitConcept model patient information model guideline model

eg multiple abstraction methods 1048708Temporal query based on formal temporal modelTemporal abstraction use specifications of abstractions in knowledge base

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
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• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

PRODIGYDeveloped by Ian Purves Peter Johnson and colleagues at the U of Newcastle UK

Simple and understandable model 1048708Few modeling primitives 1048708Complexity management techniques Eases the encoding process

Sufficiently expressive to represent chronic disease management GLs

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
• Slide 19
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• Slide 21
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• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

ProformaDeveloped by John Fox et al (ICRF UK)

Emphasis on soundness safety andverifiability 1048708

PROforma is a formal specification language based on a logic language

Guidelines are constraint satisfaction graphs 1048708

Nodes represent guideline tasks

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
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• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

AsbruDeveloped by Shahar Miksch and colleagues

Emphasis on guideline intentions not only action prescriptions 1048708

eg maintain a certain blood pressure

Expressive language for representing time-oriented actions conditions and intentions in a uniform fashion

Guidelines are modeled as plans that can be hierarchically decomposed into (sub)plans or actions

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
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• Slide 16
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• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

GuideLine Interchange Format Version 3

Emphasis on sharing guidelines acrossdifferent institutions and softwareapplications 1048708

A consensus-based multi-institutional process (InterMed a collaboration of Stanford Harvard Columbia) 1048708An open process ndash the product is not proprietary 1048708

Supports the use of vocabularies and medical knowledge bases

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
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• Slide 14
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• Slide 17
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• Slide 26
• Slide 27
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• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipGLIF3Object-oriented representation model for guidelines

Guidelinenameauthor

Guideline StepHas partsHas specializations

Action StepDecision StepBranch StepSynchronization StepPatient State Stephellip

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
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• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipGLIF3Action steps recommendations for clinical actions to be performed 1048708

eg Prescribe aspirin

Decision steps decision criteria for conditional flowchart traversal 1048708

eg if patient has pain then hellip

Action and decision steps can be nestedBranch and synchronization steps allow concurrency

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
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• Slide 15
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• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipGLIF3Patient-state step 1048708

characterize patientrsquos clinical state 1048708serve as entry points into the guideline

Steps refer to patient data items (age cough)

Expression language derived from Arden Syntax logic grammar

Medical domain ontology

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
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• Slide 13
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• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

hellipGLIF3Medical ontology1048708Concept model 1048708

concepts defined by id from controlled vocabulary 1048708

concept relationships (eg contradindication is-a)

1048708Patient information model 1048708Default model is based on HL7 RIM 1048708User-defined concepts and data model

classes

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
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• Slide 15
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• Slide 27
• Slide 28
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• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Workshop Towards a Sharable Guideline RepresentationHosted by InterMed in March 2000 in Boston80 attendees from 8 countriesRepresentation from 1048708

Government 1048708Professional specialty organizations 1048708Insurers 1048708Health care provider organizations 1048708Academic medical informatics 1048708Industry

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
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• Slide 13
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• Slide 15
• Slide 16
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• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Purpose of the meetingTo recognize the need for a standard

To identify the the functional requirements for sharing guidelines

To establish a process for the development of a robustrepresentation model

To establish a process to foster sharing

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
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• Slide 16
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• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Life cycle of a computer-interpretable guideline

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17
• Slide 18
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• Slide 20
• Slide 21
• Slide 22
• Slide 23
• Slide 24
• Slide 25
• Slide 26
• Slide 27
• Slide 28
• Slide 29
• Slide 30
• Slide 31
• Slide 32
• Slide 33
• Slide 34
• Slide 35
• Slide 36
• Slide 37
• Slide 38
• Slide 39
• Slide 40

Take home messageIt is not all about the technical difficultyhellip

It is about whether people believe in guidelines

It is about whether how a guideline fits a particular case

It is about whether it makes a difference for this particular case

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
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• Slide 40