Emergency Dep. activity predictor
APIS – Emergency Department Activity Predictor. Congestion and long waiting times are a universal problem for emergency departments. Apis trains predictive models on the ED data to anticipate patient inflow, occupation of the different spaces and hospitalization needs, with horizons rangind from hours to weeks.
APIS improves care processes by providing a reliable prediction of the time and resources needed for planned emergency department management and centralised bed management. Healthcare staff can speed up certain processes or analyses by patient type, and reduce unnecessary waiting and analysis.
- Reduction of waiting times, as it warns of potential congestion with time to rearrange resources and cope with it.
- Reduction of complications and costs, as it speeds up the triage process.
- Increased levels of patient satisfaction.
- Optimisation of processes, both in triage and in treatment, limiting analysis and waiting times.
- Learning based on the organisation’s data: the Machine Learning model provides realistic results adjusted to the specific case of the organisation.
- Easy implementation.
- Independent system at centre level.
- Patient-by-patient prediction of admission risk and resource needs.
- Permanently updated thanks to Machine Learning algorithms that continuously adjust predictions based on each centre’s data.
- Guaranteed data protection, in accordance with current legislation (including the EU’s RGPD).
Amalfi Analytics is able to develop better products thanks to the support of ACCIÓ, CDTI and ENISA.