Patients evolutionary trajectories
Evolutive trajectories of patients. This tool shows the evolution of people treated for a certain process, beyond the natural evolution of the disease itself. It allows knowing the different states throughout history, from the states prior to diagnosis and complications, to its final resolution.
It can be applied both to acute processes, to assess the real course of patients in episodes in the hospital, and to chronic diseases, with an evolution of years, and care at different levels of care.
TEA generates complex state trajectories with health, social, demographic, and economic data. It works with the entire population served, and has a complete and real view of the cases.
Amalfi Analytics has developed new algorithms to infer multi-state Markov models that are not linear. The same state can have different “next states” that indicate evolutions to clinically different conditions.
The technology developed by Amalfi uses algorithms that provide a description of each state, the average permanence and the probability of transition to other states, so that experts can make recommendations and assess risks.
A second algorithm can place a patient in the current trajectory state and calculate the trajectories that the patient is most likely to follow in the future.
We are currently updating the documentation. You will soon be able to download the study case
Amalfi Analytics is able to develop better products thanks to the support of ACCIÓ, CDTI and ENISA.