The best medicine in the world is no good at all unless patients remember to take it. This is one of the big problems (and expenses) in healthcare today, and one that AllazoHealth, a healthcare analytics firm, is attacking head-on.
Medication adherence programs aren’t one size fits all, since all patients are different. And they’re prescribed medications for different ailments and reasons. AllazoHealth’s analytics platform is addressing that problem with very promising results. By using predictive analytics to identify high risk patients likely to miss a medication fill and predict which interventions will best influence individual patient behavior.
The company was just selected to be part of New York Digital Health Accelerator (NYDHA), which gives up to $100,000 in funding to companies developing digital health solutions for patients and providers. The 5 month accelerator is run by the Partnership Fund for New York City and the New York eHealth Collaborative.
AllazoHealth Founder and CEO Clifford Jones tells us why his platform is making all the difference in the world of medication adherence.
Tell us about the decision to apply for the Digital Health Accelerator.
We applied to the New York Digital Health Accelerator because we want to learn from the mentors’ extensive knowledge of the New York healthcare industry. We also want to better understand their current intervention efforts in areas outside of medication adherence, to guide us in expanding our product line into additional markets. We are also very interested in accessing the Statewide Health Information Network of New York (SHIN-NY) in order to explore a more effective way to deliver our patient-level predictions to distributed prescribers.
Tell us about your product.
AllazoHealth is a predictive analytics company that solves the problem of medication non-adherence. Our AllazoEngine technology incorporates partial or complete population data to forecast individual patients’ adherence to each of their medications, anticipate how medication adherence interventions will influence those patients, and target the right interventions to the right patients at the right time. Our AllazoEngine has demonstrated that it helps to improve the effectiveness of medication adherence intervention programs by over 90%. We provide our services to Pharmacy Benefit Managers (PBMs), health plans, ACOs, and providers both as a stand-alone analytics solution and as a full-service medication adherence solution with interventions executed by our partnering intervention vendors.
How is it different?
We hope that our platform will replace the rules-based or one-size fits all systems current medication adherence programs use. These rules-based systems deliver unnecessary interventions to some patients and needlessly intensive ones with others. Our technology addresses these shortcomings by treating each individual differently and avoiding wasteful spending on interventions for patients who do not need them.
Our predictive analytics platform differs from our competitors in several main ways.
Our engine is built on flexible machine learning technology. This enables us to make more accurate predictions in the less uniform data environments that are common in hospital systems and ACOs.
In addition to predicting patients’ future medication adherence, our AllazoEngine can also predict the amount that each intervention option will influence a specific patient’s behavior.
Our AllazoEngine is dynamic and self-learning. Within several months, it can learn to predict which patients will be more influenced by a novel intervention technology. This enables a more rapid cycle innovation and deployment of new intervention approaches in a rigorous data-driven manner.
What market are you attacking and how big is it?
We sell our solution to payers, PBMs, ACOs, and large provider organizations. These players all have a stake in the reduced costs that result when increased medication adherence improves patient health. Our individualized predictive analytics tools improve the effectiveness and cost-efficiency of existing medication adherence programs and our recommendations are useful for physicians, nurse practitioners, and case managers directly at the point of care.
What is the business model?
We sell our services as both a stand-alone analytics and full service solution. Our stand-alone analytics product improves existing medication adherence programs. It begins with our clients sending us patient data. We then return that data with each patient’s predicted adherence to each of their medications, a patient priority ranking, and a data feed specifying which interventions will best influence each patient. These targeted interventions are input into clients’ call center queues or sent to their existing intervention vendors. Our clients can also incorporate our patient level predictions into their dashboards and clinical software used by care teams and prescribers.
Our full-service medication adherence service not only delivers patient-level predictions and targeted interventions, but also delivers all of the interventions to our client’s patients. These interventions are delivered by our partnering medication adherence intervention vendors Silverlink and TeamHealth.
Is there any data that you can share on the types of New Yorkers unlikely to take their medicine?
We have found that some of the main causes of medication non-adherence are a myriad of interactions between patient characteristics and extrinsic factors. As a result, we have found that patients suffering from chronic co-morbid, cardiovascular diseases are high-risk of becoming non-adherent to their medications. We have also found some patient characteristics, including age, race, income level, and education level, to significantly impact medication adherence. Unfortunately, we are unable to disclose any more specific information
What are the milestones that you plan to achieve within 6 months?
Within the next 6-12 months, we will pilot unique intervention techniques. For one of our clients, Universal American, we will soon be coordinating interventions with caregivers of an intellectually and developmentally disabled population. We are planning to expand these intervention techniques to deliver interventions to other types of patients who are unable to directly manage their own care. In addition, next year we plan to pilot mobile apps and on-bottle devices that remind patients to take medications. We will pilot these two unique technologies with a client population and then analyze the outcomes so that our technologies learn to predict the effectiveness of these interventions.
If you could be put in touch with one investor in the New York community who would it be and why?
We would love to be put in touch with Deerfield Management because of their advanced understating of the healthcare industry.
What is your take on the current healthcare scene in New York today?
Even as the healthcare scene continues to change in New York, medication non-adherence is still a problem that is overlooked. Providers, health plans, and PBMs fail to effectively improve their patients’ medication adherence and continue to use ineffective rules-based systems.
What’s your favorite summer time beach destination close to NYC?
I haven’t had a lot of time for it in the last couple years, but I’m an avid sailor. So preferably, the beach is far off in the distance.
