Allazo Health is a healthcare analytics company that solves the problem of medication non-adherence for people with diabetes. The AllazoEngine leverages existing member data to both anticipate which patients will not take their medications and to predict the most effective interventions to influence each of those patients to take their medication.
Location: New York, NY

In their own words...

Data Design Diabetes Question: Let’s start at the beginning. How did your story begin? What was the catalyst for your solution?

Allazo Health Answer: The prelude to Allazo Health’s story begins back when our CEO, Clifford Jones, was at CVS Caremark. He was part of a small team that set out to develop a better medication adherence program. That team heavily researched existing intervention types and the impact they had on CVS Caremark’s millions of patients to develop sequences of interventions that were optimized for patients by disease state, for example diabetics. Eventually that program they developed was branded as CVS Caremark’s Pharmacy Advisor Program, and won multiple industry awards for its effectiveness.

Cliff recognized that in order to make significant further improvement in the targeting of interventions for medication adherence programs, we would need a predictive solution that was optimized for each individual patient. Specifically, if we could find a way to predict ahead of time which patients would be adherent to their medication and how to best influence each individual patient we could drastically improve the effectiveness of adherence programs across the industry. Allazo Health was born.

Having a great idea is one thing, but being able to execute on it is another entirely. What has been your biggest challenge in developing your vision into a real solution?

Applying conventional predictive modeling techniques simply doesn’t work very well to predict patients’ medication adherence and how specific patients will be affected by efforts to influence their behavior. Understanding the components of patient behavior that impact medication adherence and the way that different interventions influence those patients has been critical for us to effectively make sense of the data and develop effective predictive models. We had to build custom analytic techniques that were tailored to fundamental components and drivers of medication adherence and patient behavior. Not being able to use an off-the-shelf methodology definitely increased the effort. That extra challenge only made it all the more rewarding when we were able to develop an effective solution.

Who are some of the game-changing people and companies in health tech that you most admire? How have they caught your eye?

We are a big fan of the companies that are developing new types of interventions for medication adherence. Because our Allazo Engine continually learns, we can quickly pilot a novel intervention for clients and then add that intervention to the mix of interventions Allazo Engine pulls from to target the most effective interventions for each patient.

One example of these companies, Adhere Tech, is developing a pill bottle that measures how many pills are in a bottle and can send alerts if a patient forgets to take their medication or takes an incorrect dose. These bottles will be too expensive to distribute to all patients, but by pairing them with Allazo’s targeting algorithms, we can make sure that they are distributed to the patients who will benefit from them the most---those patients whose primary barrier to adherence is a daily forgetfulness to take their medication.

Demo Day is June 3, 2013.
Watch the live stream at
www.healthdatapalooza.org!