STATE Variables Values Observability Name/identifier <id> Unique per agent I Gender, Medical history (cardiology, pulmonology, neurological,…); Allergies (yes-no); Personal details Treatments that received (classified into therapeutic groups: I bronchodilators, vasodilators, etc.); Origin (national or immigrant) Entrance, Admissions, Waiting Room, Triage, Treatment Location E Zone. Idle, Requesting information from <id>, Giving information Action to <id>, Searching, Moving to <location> , Waiting for E ambulance. Healthy; Hemodynamic-Constant; Barthel Index (degree of Physical condition Variables Values E/I/N Observability dependence). Healthy, Cardiac/respiratory arrest, severe/moderate Symptoms (patients) E/I trauma, headache, vomiting, diarrhea Communication skills Low, Medium, High E Level of experience Resident (1 to 5); Junior (5-10); Senior (10 - 15) and E/ICurrent state Next state / (doctors) Consultant (over 15 years) Input / Output Output …. …. …. Level of experience E/I (triage Low, Medium, High Sx / Ox Ia (p1) Sy / Oy nurses) Level of experience E/I Sx / Ox Ia (p2) Sz / Oz (emergency nurses) Low, Medium, High Level of experience E/I Sx / Ox Ia (p3) Sx / Ox (admissions) Low, Medium, High …. …. ….
1) Active Agents 2) Passive AgentsPatients Information systemCompanions of patientsAdmission personnel Loudspeaker systemSanitarian technicians Pneumatic pipesNurses (Triage, Emergency) Tests servicesDoctors (Emergency,Specialists) 1 to Zone: individuals in Zone1 to 1(One-to-One) 1 to n (Multicast) (Area- Restricted Broadcast)
The Environment Arrival/dismissal by ambulanceArrival/dismissal by own means The model should include the spatial topographical design from the ED
Arrival/dismissalb y ambulance Arrival/dismissal by own means A N D
ED SimulatorInput Patients arrival: Could arrive every 3 min. , but with different probabilities: 20% (4 pat/hr), 40% (9 pat/hr), 60% (13 pat/hr) , 80% (17 pat/hr) Configuration of the ED Staff Staff Number Junior Senior Admission 1-2 2 min. 1 min. 15 sec. Triage Nurse 1-3 8 min. 5 min. Doctor 1-4 20 min. 15 min.Output Patients: How many arrive to the service How many leave the service Times of staying in each area What if?
• Find the best/optimum solution from all the possible solutions. Given any objective (index) function f : f :A max / min f x subject to x A A constraintset; xo A f xo f x f xo f x Maximize minimize xo A
Is it always the "best solution" (theoptimum) the most interesting for us?
Methodology Simulator: 2nd version Parameter configuration: A, N, D = > 3D + P => 4D A N D ~ 400 patients daily
Methodology: Computational complexity Multidimensional Discrete DD D • Search space – # Dimensions = Patients, B staff (D, N, A, …), T, B, P PP … NN N N – Each dimension=> range of possible A A AA T values – # Points = # simulations (indexes)(time) COMBINATORIAL!
ABM SIMULATOR PARAMETERS DSS I N D E + X constraints