In the digital age, we have access to more data than ever before. Companies of all shapes and sizes use data to make smarter business decisions, manage budgets, improve efficiency, meet customer expectations, and more.

As technology advances, people are becoming savvier in their use of data—and predictive analytics is a prime example. Learn more about predictive analytics and how it can prevent and address non-adherence. 

How Can Predictive Analytics Prevent Non-Adherence?

Predictive Analytics: What It Is and How It’s Used

Predictive analytics is the use of historical data and statistical modeling to identify patterns and make predictions about future unknowns. Companies are increasingly employing predictive analytics to proactively identify risks and opportunities across many different industries, ranging from retail to manufacturing to healthcare and beyond.

In fact, you have probably seen real-world uses of predictive analytics. For example, personalized recommendations for content to watch on Netflix or products to purchase on Amazon are both powered by predictive analytics. But how does it work in healthcare?

More and more healthcare organizations are utilizing data to make predictions that improve the quality of patient care and individual health outcomes. This data comes from various sources, including medical records, historical  patient engagement, consumer behaviors, and social determinants of health (SDOH). 

From there, data-driven predictive models are created to ensure a more proactive, personalized healthcare experience for each patient.  Improving medication adherence through data-driven interventions is one example of how predictive analytics can achieve better patient outcomes.

RELATED: Learn how AllazoHealth helped a leading retail pharmacy achieve 2.3  times greater uplift in patient fill rate. >>

How Can Predictive Analytics Prevent Non-Adherence?

Healthcare organizations use predictive analytics to improve traditional  patient support programs designed to prevent medication non-adherence. In the past, most adherence programs were rules-based—meaning the same rules applied to each patient.

Instead, with a combination of predictive analytics,  artificial intelligence (AI), and  machine learning, healthcare organizations—including pharmacies, payers, pharmaceutical companies, and providers—can more effectively and efficiently:

Identify which patients to target.

Rather than targeting all patients, predictive analytics can help predict patient behaviors, identify patterns, and anticipate a high risk of non-adherence. Predictive analytics can also identify patients likely to be influenced by an intervention, allowing healthcare organizations to refine targeting and tailor outreach to those who would benefit from it the most.

Personalize adherence interventions.

Personalization is critical in modern healthcare. Personalized interventions are more likely to be effective because they appeal to each individual’s unique needs and preferences. Predictive analytics and AI personalize interventions by:

  • Channel: Multiple channels can be used for adherence interventions, with different methods appealing to different patients. These channels include text messages, chatbots, apps, emails, live calls, and in-person or telehealth visits.
  • Content: It’s not only important to determine which channel to use for an intervention, but also how the messaging can be personalized for the greatest impact. Some patients benefit more from direct reminders, whereas others are more likely to respond to educational content about the importance of adherence. 
  • Timing: Timing and frequency matter. Along with determining the best channel and content for interventions, predictive analytics can predict the optimal timing and messaging cadence for each patient. 

As a result, the right messages are delivered to the right patients via the right channels at the right time, contributing to positive outcomes. What’s more, with predictive analytics and machine learning, the AI gets smarter as it goes, continuously learning from new data and optimizing predictions over time. 

With targeted channels, messaging, and timing—all tailored to meet the needs of each patient—healthcare organizations can deploy more cost-effective, efficient, and successful interventions to improve medication adherence.  Schedule a live demo of AllazoHealth’s AI Engine to get a firsthand look at the  smart data behind the scenes and the benefits it can provide to an organization like yours.

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