MAS course - Lect12 - URV health care applications

LECTURE 12: Applications of MAS at URV (II)

Artificial Intelligence II – Multi-Agent Systems

Introduction to Multi-Agent Systems

URV, Winter-Spring 2010

Outline of the talk

Rationale for applying agents in health careSome specific projects developed by the members of ITAKA

Management of data of palliative patientsWeb-based platform for providing home care services

Research and development challengesFinal thoughts

http://deim.urv.cat/~itaka

Information and Communication Technologies

End of 20th century: enormous development of information technologies

Mobile phonesPersonal and portable computersPersonal Digital Assistants (PDAs)Internet

Information SocietyEasy, flexible and cheap access to information

ICT and MASRecent trend: join the intelligent performance of multi-agent systems with the flexible access to information through new technologiesFuture scenario: ambient intelligence, inwhich ubiquitous agents communicate wirelessly to provide intelligent services to users

In particular, AmI@Medicine

Health Care problemsDistributed knowledge

E.g. different units of a hospitalCoordinated effort

E.g. receptionist, general and specialised doctors, nurses, tests personnel, ...

Complex problemsE.g. organ transplant management

Great amount of informationE.g. medical information in Internet

MAS applied in Health Care

Summary of main motivationsMAS are inherently distributedAgents can coordinate their activities, while keeping their autonomy and local dataDynamic and flexible distributed problem solvingmechanismsUse of personalisation techniques

Example: national organ transplant coordination

Fields of application

Patient schedulingPatient monitoringAgent-based decision support systemsInformation agents in InternetCommunity care, home care, care of old/disabled peopleAccess to medical informationManagement of distributed processes

Outline of the talk




PalliaSys Project

Integration of Information Technologies and Multi-Agent Systems to improve the care given to palliative patientsSpanish research project, 2004-05Work conducted between the Research Group on Artificial Intelligence at URV and the Palliative Care Unit of the Hospital de la Santa Creu i Sant Pau of Barcelona

Palliative care

Palliative patients are in a very advanced stage of a fatal disease. The aim of their care is to ease their painThese patients may be located in hospitals(Palliative Care Units-PCU, or other units of the hospital), specialised hospice centres or at their own homes

Aims of the PalliaSys project

To improve the process of collecting information from the palliative patientsTo improve the access to this information bypatients and doctorsTo monitor the state of the patientsTo apply intelligent data analysis techniques on the data of the PCU

WAPServer Simul.

WebServer

DB Wrapper

Doctor

Doctor

Patient

Patient

PCU Database

DataAnal.

PCU Head

PALLIASYSArchitecture

Multi-AgentSystem

InformationTechnologies

Web interface

Web interface

Alarm management

Information collectionPatients have to send periodically non-technical information relative to their health stateFill in a form with 10 items to be valued in the [0-10] intervalIn the developed prototype forms could be sent

through a Web page, orwith a mobile phone via WAP (simulated)

Information accessAll the data of the palliative patients arestored in a central Data Base at the PCU of the hospital

Personal information, family data, auto-evaluations, health record

Patients and doctors may make queries on the stored information

Patient queries are made directly on the DB (via Web or WAP-simulated interface)Doctor queries are made through agent communication (the Doctor Agent requesting the information from the DB Wrapper)

Data Base at the PCU / Security

There is an agent that controls the access to the Data Base (the DataBase Wrapper)The whole system includes security mechanisms to protect the privacy of themedical data

User authentication (private-public keys)Encrypted messages (SSL)Access through login/passwordPermissions associated to user types

WAPServer Simul.

WebServer

DB Wrapper

Doctor

Doctor

Patient

Patient

PCU Database

DataAnal.

PCU Head

PALLIASYSArchitecture

Multi-AgentSystem


Web interface

Web interface

Alarm management

Patient agentsThere is a patient agent associated to each palliative patientIt has to continuously monitor the status of the patient, and send alarms to the doctorassociated to the patient if something goes wrong

Doctor agents

A doctor agent is an agent associated to eachdoctor of the PCU, which would be running inthe doctor’s desktop computerIt provides a graphical interface to help:

Request information about his patientsDefine alarm situationsReceive alarm signals from patient agents

Classes of alarmsGeneral alarms

They are defined by the PCU head (through his Doctor Agent), and they have to be applied to all the patients of the unit

Doctor-specific alarmsA doctor can define personal alarms, and he can assign them

to a single patient, orto all his patients

Patient auto-evaluation

There are 10 differents aspects in patient’s auto-evaluation forms (weakness, pain, anxiety, hunger, etc)Each of the aspects has to be evaluated by the patient with an integer number from 0 to 10.Each patient has to send an auto-evaluation form every 2-3 weeks

Alarm types (I)

Alarms defined on a single auto-evaluation(Weakness >7) and (Pain > 8) : extreme_weakness(Hunger < 3) and extreme_weakness: dangerous_weaknessExtreme_weakness => patients 1, 3 and 4Dangerous_weakness => patients 2, 3 and 7

Basic alarms can be combined with and/or/not operators to define more complex alarms

Alarm types (II)Alarms defined on a sequence of auto-evaluations

(Last 2 evaluations a,b) Weaknessb-Weaknessa > 2 : fast_weakness_increase(Last 4 autoevaluations a,b,c,d) Paind-Paina > 3: extreme_pain_increase(Evaluations received in the last 3 weeks) Increase of pain degree > 4

These types of alarms may be defined on the last n evaluations or on the evaluations received in a certain amount of time

The use of Boolean operators and the definition of complex alarm situations are also allowed

Alarm management

Alarms are defined by doctors through their Doctor AgentsWhen an alarm is defined, it is automatically sent to the corresponding Patient Agent (or set of agents)When a new auto-evaluation is stored on the DB, the associated Patient Agent gets a signal, and then it checks all the alarms associated to that patientIf any alarm situation is detected, a message is sent to the Doctor Agent that defined it with an explanation of why the alarm has been activated

WAPServer Simul.

WebServer

DB Wrapper

Doctor

Doctor

Patient

Patient

PCU Database

DataAnal.

PCU Head

PALLIASYSPresent State

Multi-AgentSystem


Web interface

Web interface

Alarm management

Data Analyser: main tasks

To apply Data Mining and Machine Learning techniques to analyse the information of the DBTo provide general statistics on the data, which are useful to the PCU head to fill in the annual report

Available medical data

Input data: sequence of treatment episodesPatient location (home, PCU, socio-sanitary centre)Length of stay (days)Medication received by the patientMedical tests and procedures made on the patientGeneral patient health status

Intelligent Data Analysis

Generation of patient circuits (circuit graph)Automatic detection of patient states

Clustering techniques, unsupervised learningGeneration of models of patient evolution (state graph)Generation of decision structures (decision trees, set of rules)

Possibility of making predictions on future states and anticipate and prevent undesired situations

Circuit graph

State graph

Conclusion – PalliaSys main ideasInformation technologies and Intelligent agents may be used to build useful systemsin the Health Care domainMost of the ideas underlying this project might also be applied in elderly care or home care

Use of Information TechnologiesAutomated patient monitoringIntelligent data analysis

Outline of the talk


Management of data of palliative patientsWeb-based platform for providing home care services: K4Care


© K4Care, 2006

KnowledgeKnowledge--Based Based HomeCareHomeCare eServices eServices

ffor an Ageing Europeor an Ageing Europe

Project Presentation K4CARE Consortium

A Project funded by the European Community under the Sixth Framework Programme for Research and Technological Development

Contract no IST-026968

K4Care basic facts

March 2006 – March 2009 (3 years)Extended until September 2009

EC funding: 3.130.000 €

Coordinator: University Rovira i Virgili

13 Partners from 7 countries

K4Care project

The aim of the K4Care European project is to provide a Home Care model, as well as design and develop a prototype system, based on Web technology and intelligent agents, that provides the services defined in the model

Basic features: a) actors are members of well defined organizations, with

different roles and allowed activitiesb) there is extensive domain knowledge to be considered

(e.g. standard clinical guidelines)c) coordination of tasks in daily care

Clinical Guidelines (CGs)

Indications or principles to assist health care practitioners with patient care decisions Applicable in diagnostic, therapeutic, or other clinical procedures for specific clinical circumstances

CGs: benefits

Consistent clinical practice, avoidance of errorsReutilisation and tailoringRapid dissemination of updates and changesConsideration of appropriate knowledge at appropriate timeUse of formal representation languages

CGs: barriers in daily use

Lack of awarenessLack of familiarityInertia of previous behaviours

No integration with standard practices

Lack of time or resources

Automatic management and enactment of guidelines

Use of CGs in Home Care

Problem: patients in health care usually suffer from several pathologies, and it is not possible to apply the guidelines directlyChallenge: take into account the recommendations of existing guidelines, but adapt their application to the personal circumstances of each individual patient

K4Care Model: Structure1 Nuclear Structure + n Accessory Services

...

THE K4CARE MODEL

HCNS

Actor Service

Action Procedure Data/Information

K4Care Model: Actors and Teams

Knowledge layer

K4Care Knowledge structures

EHCR: Electronic Health Care RecordAPO: Actor Profile OntologyCPO: Case Profile OntologyProcedures FIP: Formal Intervention PlanIIP: Individual Intervention Plan

DBs, Electronic Health Care Record

Data Base: with information about the K4Care actors as users of the K4Care Platform (e.g. contact information)EHCR: with the data about the Home-Care processes performed within the K4Care Platform

Medical documents stored in XML

K4Care Ontologies (I)

Actor Profile Ontology (APO)Types of actorsActions that each actor can performPlatform servicesProceduresDocuments...

K4Care Ontologies (II)

Case Profile Ontology (CPO) DiseasesSyndromesSigns and symptomsSocial issuesAssessment testsInterventions...

K4Care FIPsFormal Intervention Plans (FIPs) are formal structures representing the health care procedures to assist patients suffering form particular ailments or diseasesFIPs are represented with the SDA* formalism

StatesDecisionsActions

The SDA* formalism is used to representK4CARE Service ProceduresK4CARE Formal Intervention PlansK4CARE Individual Intervention Plans

FIP for the management

of hypertension

Procedures

Formal specifications, in the SDA* language, of the way in which an administrative service(e.g. admit a new patient to the Home Care service) has to be implemented

Definition of an Individual Intervention Plan

Input: patient data (EHCR), result of comprehensive assessment, general K4Care knowledge structures (APO, CPO, FIPs)Output: Individual Intervention Plan to be applied on a patientProcess:

Select set of applicable FIPs (diseases, syndroms, symptoms)Merge FIPsAdapt the resulting SDA* structure to the individual characteristics of the patient

K4Care platform features Agent-based Web-accessible platform that provides a set of basic Home Care services

Definition of IIPsApply IIP to the patient

The most relevant aspect of this knowledge-drivenarchitecture is the separation of the knowledgedescription from the software realization Key elements of the architecture

declarative and procedural knowledgeinteraction between agents and end-usersagent-oriented execution of patient-centred plans

Interaction between agents and users

Multi-agent system

1 Actor Agent for each user, permanently runningWhen the user logs in, a Gateway Agent is dynamically created

Two-way communication Web-servlet-GA-AAWhen an Actor Agent has to manage the execution of a procedure/IIP, it creates dynamically a SDA-executor Agent

Transparency between knowledge and its use

Agent-based execution of IIPs (I)

Agent-based execution of IIPs (II)

Agent-based execution of IIPs (III)

Agent-based execution of IIPs (IV)

K4Care main conclusions

KnowledgeIndividual Intervention Plans allow practitioners to implement accurate and personalised sequencesof actions for a particular patient’s treatment

UseThe architecture allows implementing agent-based coordination methods between the actors relevant in Home Care, which adapt their behaviour dynamically depending on the knowledge available in the platform

Outline of the talk




Some research topics on the use of MAS in Health Care

Communication standardsMedical ontologiesSecurity mechanismsImplementation of agents in mobile devicesPersonalised access to information

Less social and professional reluctance to adopt agent technology

Legal issues

General research topics on MASService description, discovery, compositionStandard agent communication languages and protocolsNegotiation, coordination, cooperation techniquesAgent-Oriented Software EngineeringTrustHuman-agent interactionIntegration with legacy software...

Outline of the talk




Some general thoughts (I)It is difficult to work with doctors

Very busy, unaware of technical details, change requirements…However, they may end up being happy with a rather simple system (e.g. a well-organised DB, statistics for annual report)

It is difficult to sell “agents” to hospital computer units

Understanding, maintenance, …Information systems are hospital-wide, centralised

Some general thoughts (II)

Security is a matter of degree …Sometimes “real life” technical issues make it unsuitable to use agents

Use of previous prototypes or programming languages

The frontier between “agents” and “non-agents” seems to be difficult to define

Extra material for this week

Many papers on the ITAKA web site on these projects

MAS course - Lect12 - URV health care applications

Technology

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