AllazoHealth combines behavioral science and machine learning to help pharmaceutical companies, payers and pharmacies improve both clinical outcomes and return on program investment.
How AllazoHealth's AI engine works
Aggregating data for a comprehensive view of patient behavior
AllazoHealth’s AI engine learns from a comprehensive data set of over 14 million lives, including payer, provider and retail claims, social determinants of health, and patient interventions. These diverse data sets complement each other by providing multiple views of patient behavior, and have been proven to be predictive of medication adherence.
Predicting non-adherent behavior
The AI engine accurately correlates thousands of data variables with levels
of adherence for each patient. It then provides a robust prediction for each patient’s risk of being non-adherent. The AI engine also predicts each patient’s likelihood of being influenced by interventions.
Targeting precisely patients who would benefit the most
Based on these predictions, it targets the patients who are both at risk of becoming non-adherent and whose behaviors can be changed through proactive interventions. This enables adherence programs to allocate resources more effectively while improving patient health outcomes.
Personalizing interventions for individual patients
While targeting patients for intervention is important, knowing how and when to intervene is just as critical. The AI engine customizes outreach for each patient by channel, content, and timing for the greatest impact.
Using new data to continually optimize performance
As more interventions are delivered and patient behaviors analyzed, the AI engine learns more about our client’s patient populations and continually improves in accuracy and effectiveness.