As a leader of an emergency department, ambulance service, or out-of-hours medical service, you know that proper staffing is crucial. If you are understaffed, both patients and staff will suffer. If you are overstaffed, it can be costly. Neither scenario is ideal.
By analyzing your historical data along with multiple external data sources, we can accurately predict how many patients you can expect in the next 12 hours. This allows you to plan efficiently.
If someone calls in sick, you’ll know whether you need to cover the shift. And if the department suddenly gets busy, we’ll tell you how long the surge is expected to last—so you’ll know whether to call in extra staff or wait it out.
To get started, we require data on how many patients you’ve seen, broken down by the hour, for at least the past two years. For the system to work optimally, we also need regular updates — at least hourly — on current patient arrivals.
There are other ways to forecast patient attendance, but they are simply not as accurate. Your staff may have a sense of what to expect, but they’ll never consistently get it right. Or you might rely on Excel, but even the best spreadsheet won’t account for all relevant data sources. We’ve already found and integrated those data sources and perfected the algorithms, ensuring the best possible predictions of what’s to come.
Price: Please, contact us.
Contact us at contact@praemostro.com or +45 25 56 30 20. Our pricing is competitive, and you’ll break even if the system helps you avoid unnecessary coverage for just two sick calls/ month.
Our system has been in use since August 2022 in a department with approx. 75 daily arrivals. It consistently provides predictions with a margin of error of ±1 patient per hour (95% of the time over an 8-hour period). When signing up, you commit to a minimum of six months. After that, the contract may be terminated with one month’s notice.
– that much better is our calculation compared to using last week’s data
– that often we predict accurately within +/- one patient per hour, measured over 8 hours
– that often the staff predicts accurately within +/- one patient per hour, measured over 8 hours