PM360 asked life sciences industry experts with knowledge about improving adherence to medication to share the latest trends and approaches being used and to tell us how better data and monitoring can help solve this issue. Specifically, we wanted to know:
- What are the current biggest trends in how the life sciences industry is approaching ways to improve medication adherence? How are the methods being used or the issues they are looking to address different from previous years? What, if any areas, are still being ignored in relation to adherence?
- How can the industry better measure adherence to medication and monitor it at both a large and small scale? What data sets best indicate actual adherence? How can data itself play a larger role in addressing adherence?
The industry has been limited in its ability to implement creative solutions to engage and motivate patients because the FDA has strict guidelines for what pharma companies can communicate with patients. To address the $290 billion problem of non-adherence, industry stakeholders have generally employed a combination of one-size-fits-all patient education and technology investment to support broad outreach, but as recognition grows of patients’ unique circumstances, more effective, personalized approaches are emerging.
Some life sciences companies kick-started their own adherence programs via apps or digital platforms but with lackluster results. Now we’re seeing companies pivot from DIY to partnering with recognized patient engagement leaders that have the expertise required to improve adherence to medication regimens through nonbiased content. Already known and trusted by patients, these partners enable life sciences companies to communicate content and have confidence it’s being delivered in a way that motivates patients to act.
Today, we still can’t easily discern whether a patient took their pill or not and the reason why. More innovation is needed with this highly practical goal in mind but developing more tailored adherence information for patients and encouraging their partnership is a critical step.
The life sciences industry is increasingly realizing that digital technology cannot be the only route to patient connection. There needs to be a hybrid of personalization and technology combined that treats the patient as a person first. According to the 2021 Accenture Healthcare Experience Survey, 52% of patients say having emotional support is important to having a positive healthcare experience. HCPs understand patients want support tools and resources. Yet, pharma companies spend more than $5 billion on patient support programs every year, and only 3% of patients are using them. An approach gaining traction is care collaboration between the industry and patients that combines tech-driven support with tailored human interaction to provide multi-dimensional information for patients.
Where adherence also needs more attention is reaching patients before an adherence event even starts. This can be accomplished by introducing digital capabilities via AI to predict who might be at risk for non-adherence and when in the cycle they are falling off their HCP’s radar. The human connection combined with this type of technology puts the focus back on the patient. By proactively reaching more patients early, and “listening” to their insights and feedback, the life sciences industry can set up patients for treatment success.
Previously, addressing lack of adherence to a medication regimen was based primarily on reminders. Today, with the industry’s patient-centric approach, we see more reliance on behavioral science to gain a holistic understanding of the patient journey. Accordingly, multiple reasons for subpar patient adherence are gaining attention, including fear of side effects, lack of medical understanding, or even financial limitations. Furthermore, when providers rely on self-reporting, they may be receiving inaccurate data, such that providers may erroneously acknowledge a patient’s filled prescription as evidence of adherence.
To begin addressing this issue, the first step is understanding it—and accordingly there has been a shift in the drug delivery industry towards incorporation of smart technologies within drug delivery devices and pharmaceutical packaging. Connected drug delivery devices, such as smart infusion pumps and wearable injectors, can provide not only accurate injection data per patient, but also a better understanding of lack of adherence as an industry-wide challenge.
With multiple methods to improve adherence, the first step must be to have a clear depiction of the problem at hand. Only by having accurate data about drug adherence will we be able to address the issue more effectively and improve patient care.
Medical adherence is complex and correlates to factors across patients’ continuity of care. Measuring, collecting, and utilizing data related to medical adherence must come from understanding patients’ and communities’ social determinants of health (SDoH). The economic and social conditions that influence health are diverse. Housing, access to food and transportation, as well as the ability to pay for healthcare and medicine are just a few economic barriers to medical adherence. Non-adherence through a social lens is seen via the duo of poor communication and inadequate health literacy.
The screening process for SDoH is more nuanced than traditional medical screenings. Despite this difference, the screening objective is the same. In the context of medical adherence, any identified needs found through SDoH screening require systems and resources across the continuum of care for the unmet need to be addressed.
Numerous data surrounding poor medical outcomes are related to non-adherence. These suboptimal medical sequelae also increase healthcare costs on an individual and industry level. To boost adherence the industry must recognize the impact of socioeconomic factors on health formally and develop a screening standard. The data can be used to pivot the focus of medical care from healthcare to simply health.
Adherence can be measured via both direct and indirect methods. Direct methods include therapeutic drug monitoring (TDM), which measures the concentration of drug in body fluids. This is the most accurate measurement but becomes challenging due to both cost and process. Meanwhile, indirect methods include fill/refill (claims) data sets, payer/pharmacy data, EHR (e-prescribe) data, and patient self-reported questionnaires, all of which help calculate an average adherence, but miss the regular ingestion pattern.
Claims data help us understand the behaviors around taking medication. EHR and pharmacy data can help establish consistent patterns between the prescriber and dispenser, which can be applied to understand the correlation between refills and medication-taking behavior. Data from brief medication questionnaires can lead to overestimated adherence, given the info is self-reported, but can also result in valuable insights regarding attitude, barriers, influence, and other behavioral attributes.
The “gold standard” approach is calculating Medication Possession Ratio (MPR) and Proportion of Days Covered (PDC). This takes into account all the data sets from claims, pharmacy, insurance, and EHR such as pill counts, duration between refills, total days in the study, days with access to medication, and overlays it with behavioral data from the questionnaire to better understand underlying causes and influence.
It is often assumed adherence is not a problem in clinical trials, but research shows this is not the case. When considering three adherence behaviors: starting the medication (initiation), taking it as prescribed (implementation), and continuing with it for the protocol-defined duration (persistence), studies have found more than a third of trial participants were non-adherent. Measuring and monitoring adherence in clinical trials would add valuable information about the effectiveness and safety of drugs.
Adherence can be measured in a variety of ways, including electronic monitors. Pill counts, however, overestimate adherence. Measures should include the identification of barriers to adherence (e.g., via electronic patient-reported outcomes in response to a missed dose). Identifying modifiable barriers would make it possible to develop targeted interventions to support patients and equip HCPs to address potential misconceptions and concerns ahead of label approval. These interventions could be refined based on monitoring of adherence in the real-world setting.
The EMERGE guideline has been developed by the International Society for Patient Medication Adherence (ESPACOMP) to increase transparency and consistency of measurement, analysis, and reporting of adherence. Trial sponsors can use it to increase the success of treatment and facilitate understanding of barriers to adherence.