Hello,
I have a simulation of a clinic (including patients and different staff). The staff service times are drawn from different distributions (one for each staff type) that were built from historical data (of course after the historical data was cleaned).
What possible sources of noise could there be in the simulation?
Thank you for your inputs.
Alex
Please elaborate; is your simulation generating noise and looking for the source or do you want to introduce noice based on realistic scenarios?
Hello Douw Faurie ,
The simulation is not generating noise……or this is what I believe [taking in consideration that all the data was thoroughly cleaned before creating the different distributions from which the simulation drowns from]. I am looking for possible source(s) or, what, if there is noise, what type of noise could that be [from where?].
I do not want to introduce noise in the simulation.
Cheers,
Alex
Alex Popp
The first thing that comes to mind is the cyclic nature of the system. For example on a day by a day, early morning, mid-day and late afternoon would be peak times in regards to the patient walking in. On a week scale, Saturdays will be will experience increased traffic due to people not willing to sacrifice a day of work. Additionally, month-end will have increased traffic in regards to patients due to prescription renewals and medicine collection. Finally, any day that would lead to an increase in alcohol consumption will lead to increased accidents and increased patients. This final one would be especially unstable due to local sports team's performance in leagues and scheduling being an unstable external force. All these on an hour time step and simulation running a full year would cause noise.
Secondly, flu season and outbreaks would increase patient traffic. Finally, this ties into climate if the winter is warmer fewer patients will seek medical help and a colder winter will mean more. These would have a larger effect on the data when the simulation is done over years timeframe.
To summarize the reasons i thought of 1. Schedule of patients 2. Situations that increase alcohol consumption 3. Large scale infections and 4. The year to year change in the climate.
I hope this helps
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