Transcript Agent-based technology as a tool for integrated assistance

Multi-agent systems in health care.
An example in palliative care.
Antonio Moreno
Multi-Agent Systems Group (GruSMA)
Research Group on Artificial Intelligence
Computer Science and Maths Dep.
University Rovira i Virgili (URV)
Tarragona, Spain
Czech Technical University,
Prague
May 31st 2005
Outline of the talk
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Introduction
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Information and Communication Technologies
Intelligent agents and Multi-Agent Systems
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PalliaSys project
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MAS applied in Health Care
Use of ICT and MAS to help to manage the care of palliative
patients
Research and development challenges on the use of
agents in HC
Some final thoughts
Outline of the talk

Introduction
–
–
Information and Communication Technologies
Intelligent agents and Multi-Agent Systems


PalliaSys project
–


MAS applied in Health Care
Use of ICT and MAS to help to manage the care of palliative
patients
Research and development challenges on the use of
agents in HC
Some final thoughts
Information and Communication
Technologies
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End of 20th century: enormous development of
information technologies
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Mobile phones
Personal and portable computers
Personal Digital Assistants (PDAs)
Internet
Information Society
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Easy, flexible and cheap access to information
Computer Science: Intelligent Agents
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Definition by Dr Michael Wooldridge:
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An intelligent agent is a computational process
that is able to perform tasks autonomously and
that communicates with other agents in order to
solve problems through cooperation,
coordination and negotiation.
These agents work in a complex and dynamic
environment and interact with it in real time to
achieve their goals.
ICT and MAS
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Recent trend: join the intelligent performance
of multi-agent systems with the flexible
access to information through new
technologies.
Future scenario: ambient intelligence, in
which ubiquitous agents communicate
wirelessly to provide intelligent services to
users.
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In particular, AmI@Medicine
Basic agent properties (I)
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Reactivity: awareness of the environment
Autonomy: control over its own actions
Proactivity: anticipation to user’s requests
Reasoning/planning (AI): basis of intelligent
behaviour
Basic agent properties (II)
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Learning: improvement of its performance
Communication: exchange of information
with other agents; implies standardization
of languages and protocols; allows
cooperation, negotiation, ...
Agent classification
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Collaborative: group of agents that cooperate
in the joint solution of a problem
Interface: collaboration with a user to solve a
task
Internet: manage the search and manipulation
of information through Internet
Mobile: physical movement through different
machines
Hybrid: combination of the previous types
Collaborative Agents - Motivation
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To solve problems that are too complex for a
single agent
To be able to solve inherently distributed
problems
To be able to interconnect already existing
systems (agentification)
Multi-Agent Systems
Multi-agent systems
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A multi-agent system is a set of autonomous
agents that can communicate (exchange
information) and thus negotiate and
cooperate in the joint solution of a distributed
problem.
Domains of application of MAS
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Distributed knowledge
Joint effort of a set of autonomous entities
Problem decomposable in subproblems
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Possibly inter-dependent
Health Care problems
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Distributed knowledge
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Coordinated effort
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E.g. receptionist, general and specialised
doctors, nurses, tests personnel, ...
Complex problems
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E.g. different units of a hospital
E.g. organ transplant management
Great amount of information
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E.g. medical information in Internet
MAS applied in Health Care
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Summary of main motivations
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Use of spatially distributed knowledge
Coordination of tasks among several autonomous
entities
Complex problems decomposable in subproblems
Personalised information to doctors and patients
Example: national organ transplant coordination
(Cortés – CARREL, Moreno et al. - URV, Calisti –Switzerland)
Growing interest
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AI in Medicine special issue (2003)
Specialised workshops at AA00, ECAI02, ECAI04.
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Int. Workshop on Health Care Applications of Intelligent
Agents – February 2003
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AI-Communications special issues (2003, 2005)
Book on Whitestein Series on Agent Technology (2003)
Forthcoming workshop at IJCAI05, Edinburgh.
AgentCities WG on HC applications =>
AgentLink III TFG on HC applications
Fields of application
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Patient scheduling
Patient monitoring
Agent-based decision support systems
Information agents in Internet
Community care, care of old/disabled people
Access to medical information
Management of distributed processes
Outline of the talk

Introduction
–
–
Information and Communication Technologies
Intelligent agents and Multi-Agent Systems


PalliaSys project
–


MAS applied in Health Care
Use of ICT and MAS to help to manage the care of palliative
patients
Research and development challenges on the use of
agents in HC
Some final thoughts
PalliaSys Project
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Integration of Information Technologies and
Multi-Agent Systems to improve the care given
to palliative patients.
Spanish research project, 2004-05.
Work 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
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Palliative patients are in a very advanced stage
of a fatal disease. The aim of their care is to
ease their pain.
These 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
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To improve the process of collecting information
from the palliative patients.
To improve the access to this information by
patients and doctors.
To monitor the state of the patients.
To apply intelligent data analysis techniques on
the data of the PCU.
Information
Technologies
Multi-Agent
System
WAP
Server
Simul.
Data
Anal.
Web
Server
Web interface
PCU Database
PCU Head
Patient
DB Wrapper
Patient
PALLIASYS
Architecture
Alarm
management
Doctor
Doctor
Web interface
Information collection (I)
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Patients have to send periodically non-technical
information relative to their health state.
Fill in a form with 10 items to be valued [0-10]
In the current prototype forms can be sent
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through a web page, or
with a mobile phone via WAP (simulated).
Other communication means (PDAs, e-mails, SMS
messages) have not (yet) been implemented; a study of
their potential usefulness is being carried out with a
questionnaire given to patients.
Information collection
(II – future extensions)
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We could associate an agent to each bed in the PCU,
that would periodically send information about the
patient status.
A doctor might also send information to the system when
he is performing a home visit, through an agent running
on a mobile phone or a PDA via GPRS.
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We have already been available to implement agents in Nokia ngage mobile phones using the JADE-LEAP environment, and
they can communicate succesfully with agents running on a
standard PC via GPRS.
A MSc-Final Year Project on tourism information using this kind
of agents will be presented in June 2005.
Information access
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All the data of the palliative patients is stored in a central
Data Base at the PCU of the hospital.
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Personal information, family data, auto-evaluations, health record
Patients and doctors may make queries on the stored
information.
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Patient queries are made directly on the DB (via web or WAPsimulated interface).
Doctor queries are made through agent communication (the
Doctor Agent requesting the information from the DB Wrapper).
Data Base at the PCU / Security
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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 the
medical data.
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User authentication (private-public keys)
Encrypted messages (SSL)
Access through login/password
Permissions associated to user types
Information
Technologies
Multi-Agent
System
WAP
Server
Simul.
Data
Anal.
Web
Server
Web interface
PCU Database
PCU Head
Patient
DB Wrapper
Patient
PALLIASYS
Present State
Alarm
management
Doctor
Doctor
Web interface
Patient agents
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There is a patient agent associated to each
palliative patient.
It has to continuously monitor the status of the
patient, and send alarms to the doctor
associated to the patient if something goes
wrong.
Doctor agents
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A doctor agent is an agent associated to each
doctor of the PCU, which would be running in the
doctor’s desktop computer.
It provides a graphical interface to help:
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Request information about his patients.
Define alarm situations.
Receive alarm signals from patient agents.
Classes of alarms
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General alarms
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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 alarms
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A doctor can define personal alarms, and he can
assign them
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to a single patient, or
to all his patients.
Patient auto-evaluation
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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)
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Alarms defined on a single auto-evaluation
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(Weakness >7) and (Pain > 8) : extreme_weakness
(Hunger < 3) and extreme_weakness: dangerous_weakness
Extreme_weakness => patients 1, 3 and 4
Dangerous_weakness => patients 2, 3 and 7.
They can be combined with and/or/not operators.
Basic alarms can be used to define more complex alarms.
Alarm types (II)
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Alarms defined on a sequence of auto-evaluations
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(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 is also allowed.
Alarm management
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Alarms are defined by doctors through their Doctor
Agents.
When 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 patient.
If 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.
Information
Technologies
Multi-Agent
System
WAP
Server
Simul.
Data
Anal.
Web
Server
Web interface
PCU Database
PCU Head
Patient
DB Wrapper
Patient
PALLIASYS
Present State
Alarm
management
Doctor
Doctor
Web interface
Data Analyser: main tasks
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To apply Data Mining and Machine
Learning techniques to analyse the
information of the DB.
To provide general statistics on the data,
which are useful to the PCU head to fill
in the annual report.
Available medical data
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Input data: sequence of treatment episodes
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Patient location (home, PCU, socio-sanitary centre)
Length of stay (days)
Medication received by the patient
Medical tests and procedures made on the patient
General patient health status
Intelligent Data Analysis
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Generation of patient circuits (circuit graph)
Automatic detection of patient states
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Clustering techniques, unsupervised learning
Generation of models of patient evolution (state
graph)
Generation of decision structures (decision trees,
set of rules).
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Possibility of making predictions on future states and
anticipate and prevent undesired situations.
Circuit graph
Movement of
each patient
among different
locations
Training sets for each location
State graph
Numerical
analysis of
the flow of
palliative
patients
Palliative patients evolution flowchart
Conclusion - Main ideas
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Information technologies and Intelligent agents
may be used to build useful systems in the
Health Care domain.
The PalliaSys project is an example of the use
of those tools.
Most of the ideas underlying this project might
also be applied in elderly care or home care.
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Use of Information Technologies
Automated patient monitoring
Intelligent data analysis
Work to be carried out in PalliaSys
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Explore the use of new ICTs to be used by
home patients (SMS messages, e-mail).
Implement and test the algorithms of data
analysis.
Test the final prototype at the PCU of the
hospital.
Outline of the talk

Introduction
–
–
Information and Communication Technologies
Intelligent agents and Multi-Agent Systems


PalliaSys project
–


MAS applied in Health Care
Use of ICT and MAS to help to manage the care of palliative
patients
Research and development challenges on the use of
agents in HC
Some final thoughts
Some research topics on the use
of MAS in Health Care
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Communication standards
Medical ontologies
Security mechanisms
Implementation of agents in mobile devices
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Personalised access to information
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PDAs, mobile phones
Less social and professional reluctance to adopt
agent technology
Legal issues
General research topics on MAS
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Service description, discovery, composition
Standard agent communication languages and
protocols
Negotiation, coordination, cooperation techniques
Agent-Oriented Software Engineering
Trust
Human-agent interaction
Integration with legacy software
...
Outline of the talk

Introduction
–
–
Information and Communication Technologies
Intelligent agents and Multi-Agent Systems


PalliaSys project
–


MAS applied in Health Care
Use of ICT and MAS to help to manage the care of palliative
patients
Research and development challenges on the use of
agents in HC
Some final thoughts
Some general thoughts (I)
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It is difficult to work with doctors
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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
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Understanding, maintenance, …
Information systems are hospital-wide, centralised
Some general thoughts (II)
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Security is a matter of degree …
Sometimes “real life” technical issues make it
unsuitable to use agents
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Use of previous prototypes or programming
languages
The frontier between “agents” and “nonagents” seems to be difficult to define.
Multi-agent systems in health care.
An example in palliative care.
Antonio Moreno
Multi-Agent Systems Group,
Research Group on Artificial Intelligence
Computer Science and Maths Dep.
University Rovira i Virgili (URV)
Tarragona, Spain
http://grusma.etse.urv.es
[email protected]