1. 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

2. 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)

3. 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

4. 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

5. 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

6. 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

7. ARRIVALS TRIAGE QUEUE SERVICE EXTERNAL SERVICE EXTERNAL ARRIVALS QUEUE RESOURCES: DOCTORS NURSES INSTRUMENTS OUT EXTERNALS EMERGENCY SERVICE GENERAL MODEL (LOW DETAIL)

8. ARRIVALS 1 ARRIVALS 2 TRIAGE QUEUE SERVICE EXTERNAL SERVICE EXTERNAL ARRIVALS QUEUE RESOURCES: DOCTORS NURSES INSTRUMENTS OUT EXTERNALS EMERGENCY SERVICE MODEL ARRIVALS

9. “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

10. ARRIVALS TRIAGE QUEUE SERVICE EXTERNAL SERVICE EXTERNAL ARRIVALS QUEUE RESOURCES: DOCTORS NURSES INSTRUMENTS OUT EXTERNALS EMERGENCY SERVICE ARRIVAL SELECTION (TRIAGE)

11. 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 death yellow code, aid shall not be delayed more than some minutes, wait may increase severity green code, aid may be delayed, a limited wait (tenth of minutes) is permitted without danger white code, no life danger, any wait cannot cause damage

12. 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

13. ARRIVALS TRIAGE QUEUE QUEUE SERVICE EXTERNAL SERVICE EXTERNAL ARRIVALS QUEUE RESOURCES: DOCTORS NURSES INSTRUMENTS OUT EXTERNALS PATIENT ROUTING AND SUPPLIED SERVICES

14. 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

15. MODEL IMPLEMENTATION BY SW MICRO SAINT Micro Saint is based on task network modelling

16. MODEL IMPLEMENTATION BY SW MICRO SAINT Network is easily built up by a CAD method

17. MODEL IMPLEMENTATION BY SW MICRO SAINT Main elements of networks are tasks, decisions and queues

18. MODEL IMPLEMENTATION BY SW MICRO SAINT Example of task description

19. MODEL IMPLEMENTATION BY SW MICRO SAINT Example of description of a decision

20. MODEL IMPLEMENTATION BY SW MICRO SAINT Example of queue description

21. MICRO SAINT MODEL NETWORK

22. MICRO SAINT MODEL NETWORK: ARRIVALS AND TRIAGE

23. MICRO SAINT MODEL NETWORK: EXTERNAL SERVICES

24. MICRO SAINT MODEL NETWORK: RED CODE

25. MICRO SAINT MODEL NETWORK: YELLOW CODE

26. MICRO SAINT MODEL NETWORK: GREEN CODE

27. MICRO SAINT MODEL NETWORK: WHITE CODE

28. MICRO SAINT MODEL NETWORK: DATA DEFINITION ARRIVALS are ruled by all time dependency parameters TRIAGE chooses different routing for every patient group PATIENT 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 groups EXTERNAL SERVICE UTILIZATION are ruled by time dependency and different priority for the patients HUMAN RESOURCE PRESENCE is ruled by turns of duty ALL ABOVE PARAMETERS ARE ADJUSTED IN ORDER TO CORRECTLY DESCRIBE THE ACTUAL STUDIED SERVICE

29. MICRO SAINT MODEL NETWORK: SIMULATION RESULTS ABOUT A QUEUE

30. MICRO SAINT MODEL NETWORK: SIMULATION RESULTS Results report: flow times queues parameters resource utilization They may be supplied referred to: single groups whole performance

31. CONCLUSIONS The presented model has been tested on an actual service sufficiently detailedflexible It is sufficiently detailed and extremely flexible, therefore it may be easily employed to simulate different emergency services managing instrument It is a useful managing 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 sufficiently detailedflexible It is sufficiently detailed and extremely flexible, therefore it may be easily employed to simulate different emergency services managing instrument It is a useful managing instrument to improve the service performance, as it permits to detect all possible critical points and consequently to suggest suitable correcting actions