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.
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!