Transcript PalliaSys - Research Group on Artificial Intelligence

PalliaSys: agent-based proactive
monitoring of palliative patients
A.Moreno, A.Valls, D.Riaño
Multi-Agent Systems Group (GruSMA)
Research Group on Artificial Intelligence
Computer Science and Maths Dep.
University Rovira i Virgili (URV)
Tarragona, Spain
4th Intern. Workshop on Practical Applications of
Agents and Multi-Agent Systems
León, 2005
Outline of the talk
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Introduction to the Palliasys project
The PalliaSys prototype
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Architecture
Information Collection and Access
Monitoring using Alarms
Conclusions and future work
Introduction: PalliaSys Project
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Integration of Information Technologies and MultiAgent 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 Cruz y San Pablo of
Barcelona.
Introduction: PalliaSys Project
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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.
The PalliaSys prototype: Architecture
Information
Technologies
Multi-Agent
System
WAP
Server
Simul.
Data
Analyser
Web
Server
Web
interface
PCU Database
DB Wrapper
Patient
PCU Head
Patient
Doctor
PALLIASYS
Architecture
Doctor
Web
interface
Information collection
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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) are being developed.
Information access (I)
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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 can access it.
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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).
Information access (II)
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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
The PalliaSys prototype: Architecture
Information
Technologies
Multi-Agent
System
WAP
Server
Simul.
Data
Analyser
Web
Server
Web
interface
PCU Database
DB Wrapper
Patient
PCU Head
Patient
Doctor
PALLIASYS
Architecture
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 is running in the
doctor’s desktop computer.
It provides a graphical interface to help:
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Add new patients.
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 different 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: Basic alarms
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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.
Simple alarms can be used to define more complex alarms.
Alarm types: Evolution alarms
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Alarms defined on a sequence of auto-evaluations
2e: D Weakness > 2 : fast_weakness_increase
4e: D Pain > 3 : fast_pain_increase
60d: D Pain > 5 : extreme_pain_increase
These types of alarms may be defined on the last n
evaluations or on the evaluations received in a certain
period of time.
The use of Boolean operators and the definition of
complex alarm situations is also allowed.
Alarm management (I)
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Definition:
Alarms are defined by doctors through their
Doctor Agents.
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Storage:
When an alarm is defined, it is automatically sent to the
corresponding Patient Agent (or set of agents).
It is also stored in the DB for proper recovery if
necessary.
Alarm management (II)
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Check:
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.
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Raise:
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.
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
Future work
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Explore the use of mobile phones to
receive/send information from/to home
patients.
Improve the data analysis algorithms.
Deploy and test the prototype.
PalliaSys: agent-based proactive
monitoring of palliative patients
A.Moreno, A.Valls, D.Riaño
Multi-Agent Systems Group (GruSMA)
Research Group on Artificial Intelligence
Computer Science and Maths Dep.
University Rovira i Virgili (URV)
Tarragona, Spain
4th Intern. Workshop on Practical Applications of
Agents and Multi-Agent Systems
León, 2005