ER wait time details for @WRHospital and @ESHCare - a thread.

A notebook containing all this data and graphs can be seen here (updates daily):
https://observablehq.com/@johnhaldeman/windsor-essex-emergency-rooms-an-analysis-of-wait-time-data

These numbers were retrieved via script hourly from each hospital's website.
Windsor-Essex Emergency Rooms - An Analysis of Wait Time Data

An Observable notebook by John Haldeman.

https://observablehq.com/@johnhaldeman/windsor-essex-emergency-rooms-an-analysis-of-wait-time-data
First up, the number of patients in treatment for each ER. This can give you an idea of the size of each ER. It's interesting to note the stability of this measure especially in relation to other things we'll be looking at next.
First up, the number of patients in treatment for each ER. This can give you an idea of the size of each ER. It's interesting to note the stability of this measure especially in relation to other things we'll be looking at next.
First up, the number of patients in treatment for each ER. This can give you an idea of the size of each ER. It's interesting to note the stability of this measure especially in relation to other things we'll be looking at next.
First up, the number of patients in treatment for each ER. This can give you an idea of the size of each ER. It's interesting to note the stability of this measure especially in relation to other things we'll be looking at next.
First up, the number of patients in treatment for each ER. This can give you an idea of the size of each ER. It's interesting to note the stability of this measure especially in relation to other things we'll be looking at next.
Next, the number of patients waiting for treatment. Starts increasing around noon on most days and decreases at around 4am.
Next, the number of patients waiting for treatment. Starts increasing around noon on most days and decreases at around 4am.
Next, the number of patients waiting for treatment. Starts increasing around noon on most days and decreases at around 4am.
Next, the number of patients waiting for treatment. Starts increasing around noon on most days and decreases at around 4am.
Next, the number of patients waiting for treatment. Starts increasing around noon on most days and decreases at around 4am.
Now the estimated wait times. Note that these are the estimates on the hospital websites, not the actual times spent waiting. Note that these results are a little different from some earlier graphs I posted. I neglected to adjust the timezone for those ones.
Now the estimated wait times. Note that these are the estimates on the hospital websites, not the actual times spent waiting. Note that these results are a little different from some earlier graphs I posted. I neglected to adjust the timezone for those ones.
Now the estimated wait times. Note that these are the estimates on the hospital websites, not the actual times spent waiting. Note that these results are a little different from some earlier graphs I posted. I neglected to adjust the timezone for those ones.
Now the estimated wait times. Note that these are the estimates on the hospital websites, not the actual times spent waiting. Note that these results are a little different from some earlier graphs I posted. I neglected to adjust the timezone for those ones.
Now the estimated wait times. Note that these are the estimates on the hospital websites, not the actual times spent waiting. Note that these results are a little different from some earlier graphs I posted. I neglected to adjust the timezone for those ones.
Actual average wait times are available from the Health Quality Ontario website. It seems to show lower wait times than the estimates I've been capturing:
https://www.hqontario.ca/System-Performance/Time-Spent-in-Emergency-Departments

Maybe the estimates are a worst case while HQO's numbers are averages.
Actual average wait times are available from the Health Quality Ontario website. It seems to show lower wait times than the estimates I've been capturing: https://www.hqontario.ca/System-Performance/Time-Spent-in-Emergency-DepartmentsMaybe the estimates are a worst case while HQO's numbers are averages.
Actual average wait times are available from the Health Quality Ontario website. It seems to show lower wait times than the estimates I've been capturing: https://www.hqontario.ca/System-Performance/Time-Spent-in-Emergency-DepartmentsMaybe the estimates are a worst case while HQO's numbers are averages.
Actual average wait times are available from the Health Quality Ontario website. It seems to show lower wait times than the estimates I've been capturing: https://www.hqontario.ca/System-Performance/Time-Spent-in-Emergency-DepartmentsMaybe the estimates are a worst case while HQO's numbers are averages.
Unfortunately, HQO's site does not have real time statistics though (2 month delays) and doesn't break things down by day or hour. The finest level of detail is by month.
Next up, we can divide the wait time by # of people waiting, to get a rough idea about throughput (patients/hour). It seems to increase with demand. Interestingly patients in treatment is stable during this time even though throughput goes up. Same beds, more staff I suppose.
Next up, we can divide the wait time by # of people waiting, to get a rough idea about throughput (patients/hour). It seems to increase with demand. Interestingly patients in treatment is stable during this time even though throughput goes up. Same beds, more staff I suppose.
Next up, we can divide the wait time by # of people waiting, to get a rough idea about throughput (patients/hour). It seems to increase with demand. Interestingly patients in treatment is stable during this time even though throughput goes up. Same beds, more staff I suppose.
Next up, we can divide the wait time by # of people waiting, to get a rough idea about throughput (patients/hour). It seems to increase with demand. Interestingly patients in treatment is stable during this time even though throughput goes up. Same beds, more staff I suppose.
Next up, we can divide the wait time by # of people waiting, to get a rough idea about throughput (patients/hour). It seems to increase with demand. Interestingly patients in treatment is stable during this time even though throughput goes up. Same beds, more staff I suppose.
Finally, the proportion of total patients waiting.
Finally, the proportion of total patients waiting.
Finally, the proportion of total patients waiting.
Finally, the proportion of total patients waiting.
Finally, the proportion of total patients waiting.
As I mentioned, all of this information is retrieved from the hospital websites, scheduled to take a snapshot every hour at the half hour. If you'd like an updated view of what's happening, the notebook linked to at the top of this thread should get updated at around 1am daily.
If you'd like to play with the data yourself, I've made it all publicly accessible at the links below. Also updated ~1am daily.

Yesterday's data:
https://d36r51w380amxs.cloudfront.net/yesterday.json 

Data for the last seven days:
https://d36r51w380amxs.cloudfront.net/weekago.json 

All the data I've collected:
https://d36r51w380amxs.cloudfront.net/allresults.json 
I'll write a blog post on what I used to do all of this in a couple of weeks. Hope you find it useful!
You can follow @JLHaldeman.
Tip: mention @twtextapp on a Twitter thread with the keyword “unroll” to get a link to it.

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