Why Personas Don’t Work to Keep Patients Adherent to Medications

Artificial Intelligence Medication Adherence Patient Engagement Patient Support Programs

Did you know that more than 30 percent of patients fail to fill their prescriptions, which is partly the result of persona-based marketing and patient support programs (PSPs) falling short. This statistic also paints a grim picture against the backdrop of aging populations, escalating chronic illnesses, and the strain on healthcare resources. Medication non-adherence emerges as a formidable foe, threatening to compromise health outcomes.

Patients are asking for a more informed and tailored approach to their healthcare journey- one that goes beyond generalized groups and embraces the uniqueness of individuals. Though once effective, the traditional methods of segmentation and personas are now overshadowed by the need for a more sophisticated solution that can target at the individual level.

The Pitfalls of Personas in Patient Engagement

Patients are unique individuals with unique health histories and personal circumstances; prioritizing personalized healthcare experiences means recognizing them as such. Attempting to categorize diverse patient populations into predefined personas oversimplifies the nuanced reasons behind non-adherence.

People are not one-size-fits-all, nor are the barriers they face in following prescribed medication regimens. Recognizing the unique and evolving nature of each individual’s circumstances is crucial for developing effective strategies to enhance medication initiation and adherence, transcending the limitations of personas in this critical aspect of healthcare.

Let’s explore reasons why personas and rules-based experiences often fall short of fostering meaningful patient connections and sustained engagement.

1.    No One Wants To Feel Like A Number

Consider Ozzy Osborne and King Charles. Arguably, you couldn’t imagine two more polar opposite people. On paper, however, they are both 74-year-old Caucasian males, both suffering from varying degrees of neck pain attributed to past injuries, the royal’s due to his polo-playing days and the rock star’s courtesy of a quad bike accident nearly 20 years ago.

If they were to be enrolled in a PSP or targeted by patient marketing initiatives, most likely, they would be regarded as part of the same segment, with the same persona mapping applied to their experiences. But would this be successful, given their vastly different lived experiences and lifestyles? The answer is unequivocally no.

2.    Failure To Recognize The Individual

No two patients are the same, even if they fit into the same broad persona. The same interventions are not going to resonate with everyone universally. 

Personas are static representations that often fail to account for individual variability in patient backgrounds, preferences, and health journeys. Patients exhibit diverse behaviors and respond differently to interventions, making it challenging for personas to effectively capture and accommodate this variability.

Patients want to feel supported yet empowered to make informed decisions about their own health. They are now consumers first and foremost, navigating through an often-complicated PSP environment.

RELATED: Learn how to leverage AI to build a best-in-class patient support  program >>

3.    Lack of Personalization

In a world where patients are exposed to ads and reminders all across the digital spectrum, pharma companies need to truly stand out. Personas may give marketers and PSPs an idea of how to target certain groups, but lack the true personalization at the individual level needed to make it truly successful. Without true personalization, rather than personas and segmentation, first fill and refill rates will only continue to drag.

Personalization is a much more effective way of connecting with patients, who will be more likely to respond if content is tailored to them individually. This personalization encourages the right engagement, driving them toward their next-best-action for positive medication behaviors, and leads to better health outcomes.

Additionally, personas or segments inform the rules in rules-based programs. These use A/B testing and if/then statements and multivariate testing (deciphering a successful combination of variables) but have limits on how personal and sophisticated interventions can be. By design, these programs lack the kind of consumer behavior data that allows for the creation of truly personalized healthcare experiences at scale. Instead, generic touchpoints funnel patients through, based only on these simple, binary choices.

4.    Overlooking Individuality

Personas often overlook the impact of social determinants of health (SDOH), such as socio-economic status, education, and cultural background, on patient behavior. These factors play a predictive role in shaping health outcomes, and personas may not adequately consider the nuanced influence of SDOH on individual patient engagement and medication behaviors.

Every patient brings a unique set of circumstances, preferences, and challenges to their healthcare journey. Personas, by nature, simplify these complexities and may overlook critical aspects of individual patient contexts. This oversimplification hampers the ability to tailor interventions to each patient’s specific needs, ultimately limiting the engagement strategies’ success. 

Looking Ahead: the Future of Personalized Healthcare Experiences

Personas have had their role in marketing and PSPs, but as patients crave more individualized resources and support, it’s evident that they’re not capable of giving the full picture – which is where AI comes into play.

Unlike technologies that claim to personalize communications but simply target persona groups or segments, AI draws from a bank of patient-level data, detecting risks early and identifying each individual’s unique set of behaviors, preferences, and needs, to go on to recommend optimized interventions for them.

AI allows healthcare and pharmaceutical companies to predict which patients are at risk of non-adherence and likely to respond to interventions. It then personalizes their support down to the individual level, tailoring the content, channel, timing, and cadence of all interventions to them specifically. This personalization maximizes the impact and efficiency of patient support programs and patient marketing initiatives, creating experiences that are truly personal.

AllazoHealth’s AI platform securely and compliantly uses identified patient data to determine risk factors for every individual patient and the optimal interventions for them, meeting them where they are and supporting them in exactly the way they need to be supported.

Want to Learn More?

Discover how AllazoHealth’s AI platform can personalize your patient support programs and omni-channel marketing, driving engagement, transforming health outcomes, and increasing operational efficiency. Request a demo today at AllazoHealth.com

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