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“Adherence Intelligence” is the new AI

“Adherence Intelligence” Is The New AI

How recognizing the unique characteristics of each patient optimizes resources and maximizes impact

Medication non-adherence is an age-old problem that pharmaceutical companies have been grappling with for decades. According to industry research, the global pharmaceutical industry loses more than $600 billion a year in revenue from medication non-adherence – with $250 billion lost in the United States alone.

General solutions can’t solve a specific problem

To address this issue, pharmaceutical companies adopted a suite of offerings that are now standard: co-pay card programs, disease and drug education campaigns, and simple reminders. More recently, digital technologies have enabled pharma to experiment with novel solutions such as smart pill bottles, connected devices, and mobile apps. Despite technological advancements, most of these solutions are not tailored to the needs of individual patients. Even today’s more advanced programs group patients into large buckets, often referred to as personas, based on similarities in demographic profiles and consumer behaviors. However, a deeper look at each patient within a given persona shows stark differences across hundreds, if not thousands, of variables that are unique to each individual patient. So, how do we achieve personalized patient engagement in a way that is cost-effective and impactful?

Adoption of AI by CPG and media

Personalized engagement driven by artificial intelligence is not a new concept. Our digital footprints provide advertisers and their machine learning algorithms with a deep understanding of who we are, what we like, and what compels us. From “based on your purchasing history, you may be interested in” to “because you watched” recommendations, the way consumer packaged goods and media companies engage consumers is personal and prevalent in our everyday lives.

At AllazoHealth, we thought, “Why couldn’t we harness the power of artificial intelligence to personalize patient engagement, and more importantly, empower patients to make healthier choices?”

Focusing on a specific issue is key

It is easy to be distracted by the possibilities AI offers to positively disrupt healthcare. However, the industry must take slow, meticulous efforts to develop, test, and refine use cases before investing heavily in adoption. One way to take a more deliberate approach to the development and adoption of AI within healthcare is to first focus on highly specific and valuable issues. This is precisely why AllazoHealth has addressed the improvement of medication adherence. By focusing on a specific issue, we have been able to cultivate the right type of data, giving our machine learning engine time to ingest, process, and learn from the inputs.

As a result, our AI predictions are accurate and prescriptive: We first identify which patients are both at risk for non-adherence and likely to be receptive to outreach. We then select the best engagement by channel, message and timing for each patient, for the greatest positive impact on their adherence behavior.

Building on our success in adherence, we have expanded our implementation of AI to include closing gaps in care and improving therapy initiation.

About AllazoHealth

AllazoHealth uses artificial intelligence to make a positive impact on individual patient adherence. We help pharmaceutical companies optimize their patient support programs to overcome barriers to adherence and conversion for at-risk patients. The result: better patient outcomes, increased persistence, and stronger brands.

Article originally published in the September 2018 issue of MM&M, written by Davin Cho.