Improving Patient Adherence with the Power of Artificial Intelligence

https://eularis.com/membership/Pharmaceutical companies can no longer ignore the hidden value available by increasing patient adherence. Lack of patient adherence costs the industry approximately $300 billion a year in the US alone. However, that is nothing compared with what it does to patients. It causes roughly 125,000 deaths each year in the US and accounts for around 10% of all hospitalizations.
 
An estimated 70 percent of patients who begin a Pharmaceutical therapy discontinue it within 1 year, even those with chronic conditions that require ongoing treatment or those taking chemotherapy to prevent cancer recurrence. This costs the global Pharmaceutical Industry an estimated $30 Billion a year.
 
Put another way, increased adherence for a product with approximately $1 Billion in sales would translate to an additional $30 to $40 Million in annual revenue. In addition, since it costs six times more to attract new patients than to retain current patients, increasing the focus on, and yields from, adherence means additional money saved and earned.
 
Despite the fact that the lion’s share of sales and marketing budgets are focused on capturing initial market share, companies are doing what they can to improve patient adherence.
 

Many approaches are now being used to improve this, from chip in a pill, better packaging, case management and coordinated care, behavioral support, and cheaper drugs for those who cannot afford it. Nonetheless, barriers to success of these patient adherence programs come from the very nature of adherence.

There is a lack of understanding of the drivers behind non-adherence and the barriers to adherence. The complex nature of non-adherence is baffling to many researchers, and overwhelming to companies. The idea of the typical non-adherent patient is a myth.
 
Attempting to track down the characteristics of non-adherent patients is an extremely difficult endeavor: while a few assertions about age and type of condition (acute or chronic) can be made, little or conflicting evidence exists for consistent relationships between non-adherence and a host of other identifying factors. These include gender, education, intelligence, marital status, occupation and income, ethnic background, personality type, and type of treatment. No consistent relationship has been found between non-adherence and race or socioeconomic status either.
 
Determining the reasons for non-adherence then must move beyond these personal characteristics and look at circumstance, ideology and much more. Dr. David Sackett of McMaster University suggested that there were no less than 250 factors contributing to the problem of non-adherence. The reasons vary and lie on both the physician and patient side. This makes it crucial that clinicians (and Pharmaceutical Companies) not place all the blame on patients but utilize advances in Artificial Intelligence to understand the individual patients and address the causes of each individual’s non adherence.
 
 
Eularis have been applying Artificial Intelligence to understand physicians’ prescribing behaviors to determine what specific messaging will influence individual physicians to change behavior reliably. We realized similar algorithms could be applied to understanding patients’ adherence and lack of adherence behavioral causes, enabling rapid identification of non-adherent patients while using personalized approaches to influence the individual causes for each patient.

 

But, what if you want to do something quickly and do not want to reinvent the wheel?

Well, when finding goodies for our membership, we came across a very interesting company that utilise AI for language analysis and have applied that to patient adherence (and many other areas useful for pharma). They were able to identify some previously unseen insights in a pharma brand engagement on patient adherence. Check out all the details about them in the gameplans section of the membership. And, the best part? Although it took years to perfect, applying it can give you results in 3 days from starting with the tool! 

AI can be automated to consistently add new patients’ data whereby the Artificial Intelligence algorithms will learn from each patients’ data input. This allows personalised approaches to each individual patient but does not require vast time from the Pharma company: the entire approach can be automated.

Conclusion

Adherence to prescribed medication, particularly for long-term therapies, poses a tremendous challenge to the world’s Pharmaceutical Companies and their patients. While the reasons behind non-adherence are complex, and the opportunities to improve adherence many, the causes vary from patient to patient.

The only way to really tackle this effectively is to personalize the solution by identifying individual causes for individual patients using automated Artificial Intelligence and utilize this to ensure that each patient gets the right message or solutions relevant for the reason of their own lack of adherence.

Using AI, Pharmaceutical companies have the power to increase patient adherence on a personalized patient-by-patient level while also increasing brand revenue. With an understanding of adherence issues, careful planning and the use of powerful AI tools, brand managers and team members can eliminate anxiety and uncertainty, and find success through high ROI.
 

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To learn more about how Eularis can help you find the best solutions to the challenges faced by healthcare teams, please drop us a note or email the author at abates@eularis.com.

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