PROcesses &

Editable byUSers Hemant Shah M.D., M. Surg.

Scientist, Information Sciences

City of Hope National Medical Center

Duarte, CA

hemant@proteme.org

Transactions

A Guidelines Model

In This Presentation …

A very brief introduction of Proteus

Demonstration of software tool Protean and other associated tools

Implications for healthcare

Potential uses of Proteus technology in healthcare tools

Proteus – A Brief Introduction

What Is Proteus?

A model for constructing clinical decision-support Guidelines with entities called Knowledge Components which are:ExecutableEditableReusable

Proteus is a Model for…

Creating clinical practice guideline based decision-support systems

EMR systems

Kernel of integrated healthcare information systems

Proteus Contains

A specification of an architecture forExecutable GuidelinesSystems to handle them

A notation system for Guidelines – human & machine readable

The Vision

The Vision

Organization B

Knowledge Component Server

The Vision

Knowledge Component

Server

Organization A

What is a knowledge component (KC)?

A software component with a discrete bit of knowledge Complete in itself Can manage its own internal affairs Can be “connected” with other KCs to work

cooperatively with them

Contains knowledge about a clinical activity: Actions to be performed Events to look for Data to be collected from the actions and events Interpretation and implications of that data Supplementary information about the activities

(e.g. links to websites)

Knowledge Component

KC Represents Clinical Process

(e.g. diagnosis of acute abdomen pain)

Clinical Transaction

Knowledge Component (KC)

Transaction may be Clinical Event

(e.g. vomiting) Clinical Action

(e.g. Palpation of liver)

KC may contain data-fields describing the underlying

clinical entity

Lump

Tenderness

Vomiting

Temperature

Abstraction

Value of KC

Knowledge Component

KCs can be NestedTo represent composite processesTo reduce complexity

KC to Guidelines

KCs can be linked by Activity-links To represent process To define Guidelines

Guidelines to EMR

Lump presentTenderness severeVomiting yesTemperature 102 F

Instantiated (executed) KCs become medical record

Knowledge Component

Lump

Tenderness

Vomiting

Temperature

Abstraction

Inference toolPart of KC, yet separate

Just an interface Technology neutral Pluggable

Decides Abstraction – The value of

the component Activity within the

component

Pluggable Inference Tool

Test ATest A

Test BTest B

Test CTest C

Action AAction A

Action BAction B

User’s System

Knowledge Component

Inference ToolInference Tool

NetworkInference Tool

Inference Tool

Internet

Inference Tools•Algorithm•Decision Tables•Decision Theory•Rule Based System•Neural Network•Fuzzy System•Patient assisted decisions•Human expert (even user)•User Defined•User Specified •Combination of these

Inference Tools•Algorithm•Decision Tables•Decision Theory•Rule Based System•Neural Network•Fuzzy System•Patient assisted decisions•Human expert (even user)•User Defined•User Specified •Combination of these

Inference tool reference

Two Types of Knowledge Components

Transaction KC

Process KC

Transaction KC

Represents: Action or Event or combination

Contains: Data Elements Abstraction

Inference tool

Transaction NameTransaction Value

Transaction NameTransaction Value

Data 1 - Value

Transaction Icon

Data 2 - Value Data n - Value

Transaction KC Icon

Process KC

Represents Clinical process

Contains Nested KCs Activity Links Abstraction

inference tool Action inference

tool

Process NameProcess Value

Process NameProcess Value

Process Icon

ProcessProcess

TransactionTransaction

TransactionTransaction

Nested KCs

Links

Process KC Icon

Activity Links

Represent the sequence of Triggering of KCs and how they are triggered

Inferential Link

Sequential Link

Synchronous Link

Inferential Stop Link

Sequential Stop Link

Activity Links

Proteus Model – UML Class Diagram

Proteus Model – UML Class Diagram – Proteus

Guideline Component Class

11

2

Execution and Inference

2

AA BB

33

DD EE

CC

A B

The Cycle is repeated

Process KC 2’s inference tool decides next action.

Guideline’s abstraction is changed

Process KC 1’s abstraction is changed

Process KC 2’s abstraction is changed

Transaction KC A is executed

D E

Process KC 1 is executed

Process KC 2 is executed

Protean – A Software Environment for Proteus Guidelines

And Other Ancillary Tools

Tutorial

To test some of the Proteus concepts in action, see the tutorial

http://www.proteme.org/tutintro.html

Features of Protean

Loading and Display of Guideline

Execution Inferencing and Decision Support

What actions to performWhat events to look for Interpretation based on the dataSupplementary information

Data Entry SupportEMR

Features of Protean

EditingCreating New ElementsDeleting Modifying existing elementsReuseChanging the Inference tool Changing the inference tool behaviorUMLS Knowledge Source Server access to

associate an entity with a UMLS term

Extensibility – JIT feature

A patient has been selected as shown by the title of the Protean window.Here the user in the process of selection of a guideline for the patient.

The guideline is loaded in Protean.

Guideline has been “started”. The first Process KC within it, “Magsulf Loading” gets triggered first, which leads to the triggering of the first Transaction KC, “Convulsions eval” in it. The Transaction KC is shown as a dialog box for the user to enter the data in it.

The guideline is shown partly executed here. Since the activity link between “Intravenous” and “Intramuscular” is a sequential one, anytime “Intravenous” is executed, after it terminates, the “Intramuscular” Transaction KC is always also triggered. Here a wait of twenty seconds has been specified for the activity link. Which means only after the duration has elapsed will the next KC be triggered.

The yellow box is countdown clock telling the user the time remaining before the next activity is triggered. The edge that connects the box to the link, tells the user where the execution is stalled.

Here an incomplete guideline is loaded in Protean. The user is in the process of completing it. The tree on the left shows all the KCs that are available in the repository . The user drags a Process KC, “Diabetes Diagnosis” from the repository on the guideline.

The user has dragged the Process KC, “Diabetes Diagnosis” and has dropped it on the guideline.

The user creates a link between the pre-existing Process KC, “Management of PROM” and the newly dropped Process KC by dragging from one to the other. A dialog box opens up to allow the user to specify characteristics of the behavior of the new activity link.

The new link has been created

This shows the rule editing application GREEd (Graphical Rule Elements Editor). The Process KC, “Diabetes Diagnosis” is loaded into the application. The list on the top left shows all the rules in the KC. Using simple drag and drop actions the user has created a rule here.

The main panel shows all the KCs contained in the “Diabetes Diagnosis” Process KC, on the left side. The right side of the main panel shows all the values (abstractions) that the “Diabetes Diagnosis” KC can possessThe rule is shown as Java code in the lower panel. Since the interpreter for this rule is BeanShell which interprets Java as a script – the Tab says BSH rule.The User-view tab shows the same rule in user readable format.Tabs for Arden Syntax and Jess are being constructed

This shows the “Magsulf Loading” Process KC being edited. The user can type a broader term in the Term field, and click the [><] button to connect to UMLS Knowledge Source Server over the Internet to select a more specific term. This feature allows every KC to be tagged with a concept in an Ontology/Vocabulary. The advantage is to index and search for KCs in a repository and to allow features like Just in Time information retrieval.

Extensibility for Non-Clinical Functionality

Data

Action

Data DecisionActionDecision

ActionCore (clinical) Process

Action

Associated Process

Clinical Process as a Skeleton

Almost everything in healthcare can be mapped to the elements of the Clinical Process

Proves that clinical process is the core

Gives unlimited extensibility

Layers for Unlimited Extensibility

Physician

Researcher

Administrator

Accountant

Organization (a)

Expert

Knowledge Component

Servers

IndependentClinician

Organization (b)

System Overview

“Publish” KCs

Access KCs

Human Expert as an “inference tool”

Inference tool (b)

Inference tool (a)

EMR

Get KCreferences

Access

Knowledge Managers

InferenceTools

Naming Server

Knowledge Users

Healthcare Delivery Organization

Comparison with Other Approaches

Other models – Modularity Missing

Inaccurate lines of separation

•Workflow entities are part of the clinical activity entities.•Inferencing elements are part of clinical activity elements

PROforma PROforma

Attributes of the generic task

Attribute Description

Name Unique identifier of task

Caption Descriptive title of task

Description Textual description of task

Goal Purpose of task

Pre-conditions Conditions necessary before a task may be started

Trigger conditions Conditions which will initiate a task

Post-conditions Conditions true on task completion

Other models – why we cant have modularity

Inaccurate lines of separation

•Programmatic (inferencing) entities are represented as steps just like clinical activity entities.

GLIFGLIF

Other models – why we cant have modularity

Inaccurate lines of

separation•next_step is an attribute in each step which is directive for the next action.

GLIFGLIF

Other models – why we cant have modularity

Inaccurate lines of separation

•Sequential Step has attribute followed_by within the Guideline entities.

EonEon

Object oriented design principles

Encapsulation and information hiding

Abstraction

Design - implications

Proteus Others

Independent development of entities Different inference technologies

Pluggable inference tools Ease of editability

How systems based on Proteus can change the way healthcare is conducted?

Implications

Bridging the Research to Practice GapIn the beginning, there was – The Gap

ResearcResearchh

The Gap

PractisePractise

Bridging the Research to Practice Gap

Bridging the Gap – The Last Mile Problem

ResearcResearchh

The Gap narrowed

Access Access to to

ResultsResultsPractisePractise

Bridging the Research to Practice Gap

Bridging the Gap – The Last Mile Problem

ResearcResearchh

The Gap still exists

Meta-Meta-ResearcResearc

hh

Access Access to to

ResultsResultsPractisePractise

Bridging the Research to Practice Gap

Bridging the Gap – The Last Mile Problem

ResearcResearchh

The Gap

Meta-Meta-ResearcResearc

hh

Access Access to to

ResultsResultsProteusProteus PractisePractise

Implications Clinicians

Decision-support for individual patients at point of careKnowledge representation that clinician understands and can manipulate and that is not passive but executableFacilitating visualizing of the previous data which has a bearing on the current decision to be madeUsage of contexts for the decision on handVisualization of the potential courses for a patientOffering suggestions for next action to be takenDirect application of principles of Evidence Based Medicine (EBM)Link to reference medical literature pertinent to action or decision being takenUse of knowledge created by other experts or institutesAccess to real-time expertise of other experts in a collaborative manner, even if the experts are spread over different locationsAllowing invoking appropriate Artificial Intelligence toolsAllowing multiple inferencing technologies to be used

Decision supportDecision supportDecision supportDecision support

Implications Clinicians

Data-entry supportAbility to manage different conditions, even new onesAbility to use data of colleaguesAllow usage of physician’s data by othersPermit scientific audit for performance review or for medico-legal purposesAbility to create their own protocols – increases participation in guidelines and in sustaining the systemAccess to patient information in several ways, including webSafeguard against litigations by helping make proper decisions automatic logging of things like

Actions Times Persons Deviations from the standard action for the situation

EMR advantagesEMR advantages EMR advantagesEMR advantages

Implications Clinicians

Ability to deal with uncertainty and unexpected situations so common in clinical practice

Protection against usage of outdated concepts by allowing usage of protocol components that are updated by other experts or organisations, without any effort on part of the user

New way of professional remuneration that also takes into consideration intellectual content of their clinical activities rather than just their qualifications, experience or the procedures performed

Ability to use many software concepts and tools of Medical Informatics besides those for decision-support seamlessly, like electronic medical record (EMR), controlled vocabulary sources, telemedicine tools etc.

Other advantagesOther advantages Other advantagesOther advantages

Implications for ManagersStandardized healthcare, QAHealthcare quality evaluationAccurate way of estimating, monitoring and predicting Costs, Requirements, Reimbursements, Revenues, patient satisfaction etc.Executive decision-support systemsDisease management, case management, outcomes management, integrated healthcare delivery frameworkCost containmentContinuity of healthcare

Implications for PatientsPatient-education regarding her condition and specific features of her own case

Informed consent

Allow patient aided management

Patient participation in management of her condition

Implications for Publishers

A new way of publishing medical literature linked directly with medical management

Not passive knowledge but dynamic executable type

Ability to assess “usage” of information as compared to “access” of information

For LibrariansProvide accurate information relevant to the cases being managed

Linking it to the appropriate steps in the management

Anticipate what information will be required by the clinicians and providing it before that step in management is reached

Implications for

Researchers Research utilization directly by clinicians directly plugging in their results or discoveries into clinical protocols

Compliance with research protocols, while allowing clinicians managing the cases to change parts which do not compromise the research

Ability to study diseases and their managements in a different way – as processes

Implications for MI & IT FolksDevelopment of new applications and knowledge components for healthcare

Extensibility in applications and in protocols including non-clinical extensions

Standard components based on CORBA, which will have interoperability with other components

Potential Tools

Proteus Based Tools for Clinical Trials

Eligibility determinationProtocol prioritizationDose Escalation & Maximum Tolerable Dose determinationAdverse Event Determination Grading Monitoring

Post-approval research behavior change monitoring

CommunicationEducation

Proteus Based Tools for Clinical Medicine

Guideline based Clinical Decision Support System with a library of guidelines for set of conditions

Electronic Medical Record

Proteus Based Tools for Clinical Trials

Clinical Trials Workflow Designer and Executor

Proteus Based Tools for Education

Guidelines based teaching of clinical care for specific conditions

Conclusion

Something like Proteus is imperativeSomething like Proteus is imperative