muditgarg

Yeah, I hope it doesn't come to it but this is the right first step. Adapted a flu surge model with folks at my company to estimate bed capacity shortage and it's not pretty. https://qventus.com/blog/predicting-the-effects-of-the-covid...

We adapted the CDC Flu Surge model to estimate the effects of COVID-19 on US hospital resources. Many assumptions detailed here but combined disease and population with hospital bed and occupancy data to help prepare for where the largest shortages may occur if things were to get bad

Unfortunately, there aren't any great APIs in the health IT world but we integrate with various hospital systems. We do not ask staff to enter any additional data than what is already in these systems

Good question. ER doctors hate when software gets in the way of their clinical decision making. We deliver recommendations to the front line managers but they decide what to act upon. One of the most frustrating things for the doctors often is when they are waiting to treat the patients but can't because there are no beds, or not enough staff or labs are not coming back. Our software anticipates those problems and recommends taking out those bottlenecks in advance.

Our hope is that we will make the day of the staff in the ER much less stressful and allow them to focus on spending more time with the patients.

Thanks @mendelc

Yes. Our data feeds include the outcome variables we are optimizing for which helps the algorithms retrain as new patterns emerge.

Great question. Generally our system performs better in higher volume areas given the higher "n" in the data but we don't have a live deployment in a high traffic community ER yet. Hopefully we will have a more conclusive answer for you soon!

Just launched our product on TechCrunch. Helping hospitals run smoothly a challenging problem but one we care a lot about.

If any of you want to talk about this or have stories from waiting in the ER or a doctors office please share :)