nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

Daily patient volume prediction during covid phase

sweetycha

Hi All

I have daily patient volume data and I am to predict the daily forecast for next 14 days so that they do the appropriate staffing ( doctors, nurse etc.)

So my question is, what is the best method to do the time series in covid variation phase? Before covid I was forecasting with seasonal Arima model .

I have daily data since july 2019 . Is it good idea to include data since July 2019 or since we have about 35% reduction in daily volume, its good idea to just focus on march 2020 data and predict for 14 days? or just past 3 week to predict for 14 days...

Please advise.

Accepted answers

All comments

statman

If the daily patient volume is consistent and stable (as verified using control charts), then you would be able to extend the limits of the control chart as a prediction of future time periods. If, however, the patient volume is inconsistent, any method of prediction will be poor. Since the COVID outbreak, my guess is the data from prior to the event is not representative of the current situation. You could try modeling the "recent" data from that may be representative of the next 14 days (I don't know what specific data that is). But, in any case, if the process is unstable, any prediction will be poor. It might be useful to find leading indicators to help understand the patient volume.

sweetycha

Thank you Statman.

I used the past 4 weeks data to predict for next 3 week. The forecast trend is going way up but in fact the actual is not up high.This ahs caused issue in staffing because we staffed for 165 patients but in fact we are just seeing in 120s.

Ideally it should be in red line in the graph below

is there way we can just give more weights to last week and maintain the weekly pattern ( high on Mondays, low on friday etc) .

which method would that be.. or is there any better suggestion.

Please advise

Thank you jmp sample.PNG

statman

Please attach your JMP file and I'lll take a look.

sweetycha

Hi Statman

I have attached the file with both actual and predicted ( from time series seasonal anima of (110,012)7

I used 7 because we have weekly variation like high on Mondays

I used 3/20 to 5/09 in actual col to predict for 5/10 to 5/23 which is also added in cols c to g

jmp file 516.xlsx