NEW YORK, Nov. 1, 2017 /PRNewswire/ -- AllazoHealth, the industry leader in optimizing adherence programs through predictive analytics and artificial intelligence, today announced positive results from a randomized controlled study co-published with one of the largest regional health plans in North Carolina.
The study titled, "Improving Medication Adherence by Better Targeting Interventions Using Artificial Intelligence – a Randomized Controlled Trial", was conducted for the health plan's Medicare Advantage Part D (MAPD) population of 104,392 patients. The main objective was to improve adherence rates across the three groupings of medication classes that are directly tied to end-of-year Star Ratings and bonus payments: renin angiotensin system antagonists (RASAs), oral anti-diabetics (OADs), and statins.
The results of the study validate the effectiveness of AllazoHealth's AI engine (The AllazoEngine) in better targeting live phone call interventions to the right patients with the optimal message at the best time. Interventions targeted based on the recommendations of the AllazoEngine generated 5.45x greater uplift in medication adherence compared to the calls targeted through traditional methods (e.g., based on historical fill behavior, late-to-fill triggers). In fact, these results were achieved while delivering 33% fewer calls on average per patient, demonstrating the ability to achieve significant adherence uplift at a fraction of the cost of conventional adherence programs.
The study, co-authored by AllazoHealth team members (Clifford Jones, Brittanie B. Gracie, and Davin S. Cho) and the payer's executives (Suzanne Conner and Estay Greene), validates the value of predictive analytics and artificial intelligence in combatting one of the most pervasive yet manageable healthcare issues today -- medication non-adherence. Despite the tremendous amount of investment healthcare companies make each year on combating non-adherence, the issue continues to persist.
"Medication non-adherence remains one of the largest unsolved issues in our society today. One of the biggest drivers for this is that the reasons for non-adherence are unique to each patient. At AllazoHealth our engine first predicts which patients will become non-adherent, and then identifies the intervention that will be most effective in overcoming the poor adherence behavior," says Clifford Jones, AllazoHealth's CEO.
As healthcare stakeholders face greater pressures to demonstrate value-based care in an increasingly cost-constrained environment, improving medication adherence is the first step towards unlocking value for both patients and healthcare organizations. AllazoHealth collaborates with both regional and national payers to improve Star Ratings and HEDIS scores by lifting adherence rates for all metric-eligible patients. AllazoHealth also provides services to healthcare organizations with a stake in their patient population's adherence rates, including providers, pharmacies, and pharmaceutical manufacturers.
The study was first shared at the 2017 Connected Health Conference in Boston on October 26-27 and has since been made publicly available on AllazoHealth's website at: https://allazohealth.com/category/news/, in the Featured section.
AllazoHealth is a healthcare technology company focused on improving medication adherence through predictive analytics and artificial intelligence (AI). Our award-winning AI engine better targets medication adherence interventions, helping our healthcare customers optimize the impact of their adherence programs at a substantially lower cost.
This is accomplished through our engine's proprietary algorithms and machine learning capabilities, which target the best adherence interventions to each patient at the optimal time, while simultaneously eliminating unproductive outreach.
Our healthcare clients, who collectively serve over 30 million patients in the U.S., include some of the largest players in the payer, pharmacy, and pharmaceutical industry.
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