210 likes | 384 Views
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.
E N D
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 • Introduction to the Palliasys project • The PalliaSys prototype • Architecture • Information Collection and Access • Monitoring using Alarms • Conclusions and future work
Introduction: PalliaSys Project • 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 Cruz y San Pablo of Barcelona.
Introduction: PalliaSys Project • 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 • 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 Analyser Web Server Web interface PCU Database DB Wrapper PCU Head Patient Patient PALLIASYS Architecture Doctor Doctor Web interface The PalliaSys prototype: Architecture
Information collection • 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 • 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) • All the data of the palliative patients is stored in a central Data Base at the PCU of the hospital. • Personal information, family data, auto-evaluations, health record • Patients and doctors can access it. • 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) • 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. • 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 Analyser Web Server Web interface PCU Database DB Wrapper PCU Head Patient Patient PALLIASYS Architecture Doctor Doctor Web interface The PalliaSys prototype: Architecture
Patient agents • 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 • 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: • Add new patients. • Request information about his patients. • Define alarm situations. • Receive alarm signals from patient agents.
Classes of alarms • General 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 alarms • A doctor can define personal alarms, and he can assign them • to a single patient, or • to all his patients.
Patient auto-evaluation • 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 • Alarms defined on a single auto-evaluation • (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 • 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) • Definition: Alarms are defined by doctors through their Doctor Agents. • 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) • 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. • 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 • 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. • Use of Information Technologies • Automated patient monitoring • Intelligent data analysis
Future work • 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