Patient adherence has been a top priority in healthcare for quite some time now, but driving improvements looks different in recent years. New technologies and innovations have introduced a host of robust strategies to improve patient adherence to prescribed medication.
Let’s look at those strategies in 2023 and beyond.
Modern Strategies to Improve Medication Adherence
Post-it Note reminders, pillbox routines, and 90-day medication supplies are limited in their effectiveness when improving patient adherence and persistence.
Fortunately, as digital health technologies evolve, healthcare organizations can become savvier and more successful in their efforts to improve medication adherence. By combining advanced technology with robust data, there are more opportunities to intervene with strategies for improving medication adherence, such as:
1. Reminder Apps
Reminder mobile applications help patients track their own medication intake, addressing memory issues and forgetfulness as barriers to adherence. Incorporating medication reminders onto smartphones has become a mainstay in healthcare, offering patients a convenient and affordable way to monitor their own medication adherence.
2. Wearable Devices
Smart wearable devices (SWDs) feature built-in biosensors that allow real-time medication monitoring. SWDs go beyond simple medication reminders, incorporating self-reporting capabilities. Wearable devices ranging from smartwatches to patches have proven to be one of the more effective medication adherence strategies.
3. Smart Products
Smart medication adherence products (MAPs) such as smart pills, pill bottles, medication organizers, and blister packaging that contain radio frequency identification (RFID) technology and track real-time medication intake. Embracing smart MAPs enables healthcare organizations to monitor patients remotely and respond to maintain or improve medication adherence.
4. Artificial Intelligence
Artificial intelligence (AI) is perhaps the most promising of all modern strategies to improve patient adherence to medication. Predictive analytics and machine learning makes data-driven predictions that enhance the effectiveness of patient support programs. This ability to predict thousands of touchpoints was nearly impossible to do in the past. But today, AI is used by pharmaceutical organizations worldwide to predict non-adherence, personalize engagement strategies, and maximize interventions for the best possible patient experience and outcomes.
The Role of AI Technology in Medication Adherence Strategies
What role does AI technology play in improving medication adherence?
Amid the rise of healthcare consumerism and the ever-evolving digital health landscape, healthcare organizations have found that a one-size-fits-all approach no longer meets the mark. Every patient is unique, so patient support programs need to be as patient-centric as possible to achieve positive results.
The key is personalization, which is one area where AI shines. Large, varied datasets from different sources—including medical claims, historical program engagement, consumer behaviors, and social determinants of health (SDOH)—provide healthcare organizations with the insights needed to tailor adherence interventions to best suit the needs, goals, and preferences of each individual. Traditional patient engagements use business rules and persona journeys to customize the outreach to a segment of the population, but AI can tailor the experience even further down to the individual level.
Numerous factors play a role in personalizing interventions, such as the intervention channel, content, timing, and frequency. Getting the right message to the right patient through the right channel at the right time is tricky business, but it’s possible—not to mention cost-efficient and effective—with healthcare AI.
Predict, Personalize, Maximize: Patient Engagement for Better Health Outcomes
Using AI, pharmaceutical organizations can deliver custom-tailored interventions designed to identify and address gaps in adherence. At AllazoHealth, our AI platform leverages robust datasets to predict patients with a high risk of medication non-adherence and those most likely to benefit from intervention. The AI is trained on a robust dataset (of more than 25 million patients) alongside the customer’s dataset for medication adherence.
Healthcare organizations receive data-driven actionable recommendations for the optimal channel, messaging, and timing for each patient. For example, some patients will benefit more from low-touch medication reminders via text message or mobile app, whereas others may require higher-touch methods, such as personal phone calls to educate on the importance of adherence. Medication use is personal and by using AI to personalize patient interventions, pharmaceutical manufacturers can maximize initiation and adherence, improve patient engagement, and achieve better patient outcomes in the process.
