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EMERGENCY SERVICE:A
GENERALIZED FLEXIBLE
SIMULATION MODEL
Paola FACCHIN Department of Paediatrics, University of Padova, Italy
Giorgio ROMANIN JACUR Department of Management and Engineering, University of Padova, Italy
AIRO 2003
EMERGENCY SERVICE 1
Any emergency service:
• is devoted to supply first aid to outpatients
• may alternatively serve:
– a hospital or a group of hospitals,
– a department or a group of departments,
according either to pathologies (e.g.,
obstetrics, surgery) or to types of patients
(e.g., neonatology, paediatrics)
EMERGENCY SERVICE 2
Any emergency service is characterized by:
• high variability of patient arrivals, depending on:
– time (different intervals of the day, week, year)
– randomness (e.g., accidents, weather,
epidemics)
• hard requirements for:
– quick (sometimes immediate) response, also in
case of congestion
EMERGENCY SERVICE 3
Any emergency service shall be correctly designed
and managed for what concerns:
• structures (major treatment rooms, minor treatment
rooms, beds)
• technological resources (specifical instruments)
• human resources (doctors,nurses, engineers and
related working rules, turns of duty, etc.)
in order to supply a high quality service at minimum
cost
EMERGENCY SERVICE 4
Discrete simulation may be a useful tool:
• in the design phase, to find the right dimension of
employed structures and resources
• in the working phase, to analyze, check and
possibly adapt the system behaviour
Discrete simulation requires to:
• build up a model with the right level of detail
• implement it in a friendly language
PAPER CONTRIBUTION
• We build up a generalized flexible model, able to
correctly describe many existing emergency
services, by adjusting fundamental parameters
• We implement it by specialized software Micro
Saint, which presents a good compromise
between abstraction level and user friendliness,
and therefore may be easily employed both by
those who adapt the general model to the
particular application and those who utilize the
application for design or management
ARRIVALS
ARRIVALS
TRIAGE
QUEUE
QUEUE
QUEUE
QUEUE
SERVICE
SERVICE
SERVICE
SERVICE
EXTERNAL
SERVICE EXTERNAL
ARRIVALS QUEUE
RESOURCES:
DOCTORS
NURSES
INSTRUMENTS
OUT
OUT
EXTERNALS
EMERGENCY SERVICE GENERAL MODEL (LOW DETAIL)
ARRIVALS 1ARRIVALS 1
ARRIVALS 2ARRIVALS 2
TRIAGE
QUEUE
QUEUE
QUEUE
QUEUE
SERVICE
SERVICE
SERVICE
SERVICE
EXTERNAL
SERVICE EXTERNAL
ARRIVALS QUEUE
RESOURCES:
DOCTORS
NURSES
INSTRUMENTS
OUT
OUT
EXTERNALS
EMERGENCY SERVICE MODEL ARRIVALS
EMERGENCY SERVICE MODEL ARRIVALS
“Average arrivals”:• random independent• time dependent mean• groupable in classes (to be defined now)
“Special arrivals” (e.g., epidemics, extraordinary weather):• randomness to be defined according to the particular case• time dependency to be defined according to the particular case “Pseudo arrivals”:• change of orders (deterministically at every duty change)• other
ARRIVALS
ARRIVALS
TRIAGETRIAGE
QUEUE
QUEUE
QUEUE
QUEUE
SERVICE
SERVICE
SERVICE
SERVICE
EXTERNAL
SERVICE EXTERNAL
ARRIVALS QUEUE
RESOURCES:
DOCTORS
NURSES
INSTRUMENTS
OUT
OUT
EXTERNALS
EMERGENCY SERVICE ARRIVAL SELECTION (TRIAGE)
EMERGENCY SERVICE ARRIVAL SELECTION (TRIAGE)
All arrivals are selected by the same unique filter (triage) which is ruled by specialized nurses
The selection is based on the presented life parameters (predefined and universal) which determine the immediate life danger
The selection assignes a colour code, according to immediate life danger, and related urgency:red code, aid shall be immediate, any wait may cause deathyellow code, aid shall not be delayed more than some minutes, wait may increase severitygreen code, aid may be delayed, a limited wait (tenth of minutes) is permitted without dangerwhite code, no life danger, any wait cannot cause damage
PATIENT ROUTING AND SUPPLIED SERVICES
According to the assigned colour code the patient is characterized by:• different routing• different treatments• different resources utilized• different service time• different priority and possible preemption in the queues, in particular for external services, if required
ARRIVALS
ARRIVALS
TRIAGETRIAGE
QUEUEQUEUE
QUEUE
QUEUE
QUEUE
SERVICESERVICE
SERVICE
SERVICE
SERVICE
EXTERNAL EXTERNAL SERVICESERVICE
EXTERNAL
ARRIVALS QUEUEQUEUE
RESOURCES:RESOURCES:
DOCTORS
NURSES
INSTRUMENTS
OUT
OUT
EXTERNALS
PATIENT ROUTING AND SUPPLIED SERVICES
RESOURCES AT DISPOSITION
DOCTORS• duty chief = responsible of the service• (possible) assistant(s) on duty• available within minutes (e.g., ten, twenty)• working in external services
NURSES• triage nurses• nurses on duty
STRUCTURES AND INSTRUMENTATION• Major treatment room(s)• Minor treatment room(s)• Special instruments
MODEL IMPLEMENTATION BY SW MICRO SAINTMicro Saint is based on task network modelling
MODEL IMPLEMENTATION BY SW MICRO SAINTNetwork is easily built up by a CAD method
MODEL IMPLEMENTATION BY SW MICRO SAINTMain elements of networks are tasks, decisions and queues
MODEL IMPLEMENTATION BY SW MICRO SAINTExample of task description
MODEL IMPLEMENTATION BY SW MICRO SAINTExample of description of a decision
MODEL IMPLEMENTATION BY SW MICRO SAINTExample of queue description
MICRO SAINT MODEL NETWORK
MICRO SAINT MODEL NETWORK: ARRIVALS AND TRIAGE
MICRO SAINT MODEL NETWORK: EXTERNAL SERVICES
MICRO SAINT MODEL NETWORK: RED CODE
MICRO SAINT MODEL NETWORK: YELLOW CODE
MICRO SAINT MODEL NETWORK: GREEN CODE
MICRO SAINT MODEL NETWORK: WHITE CODE
MICRO SAINT MODEL NETWORK: DATA DEFINITION
ARRIVALS are ruled by all time dependency parametersTRIAGE chooses different routing for every patient groupPATIENT ROUTING defines access to resources and to external services and related priorities (and preemption)RESOURCES WHICH MAY BE SEIZED, PRIORITY AND PREEMPTION are different for the various patient groupsEXTERNAL SERVICE UTILIZATION are ruled by time dependency and different priority for the patientsHUMAN RESOURCE PRESENCE is ruled by turns of duty
ALL ABOVE PARAMETERS ARE ADJUSTED IN ORDER TO CORRECTLY DESCRIBE THE ACTUAL STUDIED SERVICE
MICRO SAINT MODEL NETWORK: SIMULATION RESULTS ABOUT A QUEUE
MICRO SAINT MODEL NETWORK: SIMULATION RESULTS
Results report:flow times queues parametersresource utilization
They may be supplied referred to:single groups whole performance
CONCLUSIONS
The presented model has been tested on an actual
service
It is sufficiently detailedsufficiently detailed and extremely flexibleflexible,
therefore it may be easily employed to simulate
different emergency services
It is a useful managing instrumentmanaging instrument to improve the
service performance, as it permits to detect all
possible critical points and consequently to suggest
suitable correcting actions
The presented model has been tested on an actual
service
It is sufficiently detailedsufficiently detailed and extremely flexibleflexible,
therefore it may be easily employed to simulate
different emergency services
It is a useful managing instrumentmanaging instrument to improve the
service performance, as it permits to detect all
possible critical points and consequently to suggest
suitable correcting actions