How is the Pharmaceutical Industry Addressing Medication Adherence?

Artificial Intelligence Medication Adherence Patient Adherence Patient Outcomes

Medication non-adherence continues to be one of the most widespread issues faced by the pharmaceutical industry. According to the U.S. Centers for Disease Control, approximately 50 percent of people with chronic illnesses stop taking their medications within one year of being prescribed.

The low adherence trend is consistent across individual conditions such as depression (50 percent); GERD (54 percent); and diabetes treatments (as few as 36 percent are adherent in taking their oral hypoglycemic agents). Even chemotherapy drugs are not immune, as adherence to a chemotherapeutic regimen can be as low as 15 percent.

While medication non-adherence has had a significant negative effect on patient health outcomes, it also has had a profound negative impact on revenue and perceived value of a pharmaceutical company’s branded medications. 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.

Additionally, when a patient does not adhere to a particular medication, physicians are unable to determine if the drug is ineffective for the patient or if it’s simply not being taken as prescribed. Studies have shown that clinicians may advocate for switching to another medication instead of monitoring compliance. This is problematic not only for the pharmaceutical company, but also for the healthcare system as switching medications carries high costs.

RELATED: Find out how pharma companies use AI to improve medication adherence  across the drug lifecycle.

How is medication adherence addressed today?

Pharmaceutical companies, as well as other stakeholders, perceive medication non-adherence as a significant hurdle. As with most industries, it is less costly to keep an existing customer than to acquire a new one – pharmaceutical and life science industries are no exception. They understand that solving medication non-adherence can improve patient outcomes, generate real-world evidence to appeal to payers/regulators, and increase revenue.

A few strategies suggested by industry experts to improve medication adherence are: diverting some of the consumer marketing budget to adherence efforts; improving patient education and support throughout treatment; and leveraging technology.

When it comes to intervention strategies, there is no silver bullet solution that offers universal effectiveness for patients and conditions. Nevertheless, for pharmaceutical brands that build adherence programs, there are many interventions to choose from that can yield impressive dividends. Clinical intervention methods, such as nurse educators and pharmacist programs, have been shown to be highly effective but are predominately used for specialty and costly medications. Because this type of intervention requires a significant level of human interaction, it often leads to programs that become cost centers achieving marginal ROI, forcing brand managers to redirect their budgets. As a result, widespread adoption has not yet been achieved.

Roadblocks to Success

Most adherence programs employ a one-size-fits-all approach that focuses on building high-touch engagement programs, instead of smarter and more timely engagement with patients. Some of the more sophisticated programs may target intervention delivery based on patient segments, but in reality, individual patients within a segment can differ significantly.

Medication adherence is extremely unique and individualized to each patient. For example, two patients may be categorized into the same patient segment because of similarities in age, marital status, salary, education and even interests (like having a monthly gym membership). Often these patients will have the same messages delivered to them at relatively similar points in time. However, there are hundreds of variables unique to each patient that are not captured by simple profiling. These variables are statistically correlated to be predictive of medication adherence behaviors.

Some examples include:

  • Polypharmacy (use of multiple medications by a patient)
  • Comorbidities
  • Dosing regimen (complexity, frequency, dosing)
  • Medication synchronization
  • Miles from nearest pharmacy, or using multiple pharmacies
  • Health insurance and reimbursement eligibility
  • … and hundreds of additional calculated variables unique to each patient

One of the biggest challenges that pharmaceutical companies face in creating adherence programs is the lack of accessibility to patient data due to regulatory constraints. With little information available to them for guiding their efforts, companies tend to oversimplify targeted interventions. As a result, pharmaceutical companies often spend money inefficiently. To ensure the proper intervention, it must be delivered at the right time – when the patient needs it most and is most likely to respond.

Artificial intelligence to the rescue

AllazoHealth uses artificial intelligence (AI) to help pharmaceutical manufacturers overcome barriers to medication adherence. The AllazoHealth AI engine predicts and targets at-risk patients and then optimizes interventions by channel, message and timing.

Through its strategic partnerships with retail pharmacy chains, pharmacy network aggregators, and consumer behavior data companies, AllazoHealth helps aggregate data on behalf of pharmaceutical manufacturers to source patient data. Our AI engine is the only RCT-validated AI-powered solution that is actively servicing the pharmaceutical industry specific to medication adherence. Unlike traditional medication adherence programs, our AI engine achieves a 5.5x greater adherence uplift.

Discover how AI increased length of therapy for a manufacturer through personalized patient experiences