High complexity and chronic patient clusters
Exhaustive analysis, through clustering techniques with innovative Artificial Intelligence and Machine Learning algorithms, of chronic and highly complex patients. The management tools available so far for health institutions have not been specifically developed for the sector.
ANIS from Amalfi Analytics allows to detect patterns of complexity of chronic patients and acute pathologies. Analyze patient profiles, comorbidities, associations, processes, associated treatments and other variables with structured data.
The objective is to improve care management and optimize resources from a multidisciplinary point of view with data on mortality, readmissions and average hospital stays.
ANIS analyzes all the variables (RWD), based on structured data, offering a global vision of the status of patients, detecting the groups at greatest risk and facilitating Benchmarking.
ANIS offers a vision of the real complexity of the population to be studied, making it easier to adjust care protocols based on the knowledge of experts and the results it provides them.
Analysis with ANIS allows patterns to be discovered for each group of patients, thus making it easier to allocate resources more efficiently and develop programs based on real and meaningful data.
ANIS offers associations to visualize disease groups quickly and easily.
Analysis with ANIS makes it possible to identify different types of patients with the same diagnosis, in order to adapt clinical practice to the different patterns of comorbidities, explain the difference in results and assess the real needs of patients in each organization or territory.