Artificial intelligence (AI) has transformed industries around the world, and healthcare is no exception. More and more, we’re learning that AI can be used to enhance the effectiveness of various pharmacy patient engagement programs. In many cases, AI technology can eliminate as many as 50 percent of ineffective patient interventions, while still maintaining 85 percent of the impact.
Recently, our very own Dr. Linda Schultz, vice president of clinical and customer success at AllazoHealth, presented at the 2021 Pharmacy Quality Alliance (PQA) Annual Meeting on “Best Practices for Utilizing Artificial Intelligence in Evolving Patient Engagement Programs.”
Here are the key takeaways and must-know insights from Dr. Schultz’s presentation:
Enhancing Patient Engagement Programs with Healthcare AI
Before we dive into how AI can be utilized to enhance patient engagement programs, it’s important to explain what these programs are like without it. Without AI, technology must follow a specific sequence of steps in a linear process that is not based on outcomes. On the other hand, when AI technology is used, it is able to make decisions on how to best achieve the desired outcome based on what will resonate with each individual patient.
In other words, instead of us telling the technology what to do, AI allows us to tell the technology where to go, and then figures out the best way to get there itself.
How exactly does artificial intelligence do this? By using large, varied datasets, such as prescription data, medical data, historical engagement data, consumer behaviors, and social determinants of health (SDOH). Leveraging this data, AI can predict and prioritize patients who are the most likely to have a change in behavior. It continues to learn and optimize as it goes, predicting patterns of effectiveness to increase each intervention’s success and fill gaps in care over time.
With AI technology to inform your efforts, you can update existing interventions and suggest new interventions worth adding to a patient engagement program. You can then redeploy resources with more fine-tuned interventions to better impact behavior changes. The result is an impactful patient journey, personalized according to each person’s unique needs.
Personalizing Interventions for Better Outcomes
The beauty of using AI to enhance patient engagement programs is the individual-focused approach, which allows for the optimization of existing outreaches to drive the biggest impact on therapies. AI enables targeted interventions that are based on each patient’s level of risk and likelihood of being influenced.
From there, it determines the optimal channel methods to provide an engagement journey that is unique to the patient, rather than a one-size-fits-all experience. In short, AI ensures that the right message is delivered to the right patient, via the right channel, at the right time.
Today there are a number of ways to interact and intervene, including live calls, apps, text messages, emails, chatbots, digital pills, and both telehealth and in-person appointments. An omnichannel engagement strategy—meaning one that includes multiple engagement channels—allows for a more custom-tailored approach.
For example, some patients require more in-depth, high-touch interventions such as in-person appointments, whereas others may respond to something as simple as a text message reminder. The point is, no two patients are the same—and that’s exactly why personalization is essential in order to effectively influence behavior.
Revamping Patient Engagement Program with Healthcare AI
Implementing AI-powered interventions in patient engagement programs allows for targeted channels, targeted messaging, and targeted timing and cadence of those messages. Each intervention is informed by robust datasets—personalized to the individual, optimized over time, and set up for success.
If you’re looking for ways to improve the efficiency and effectiveness of your patient engagement programs, artificial intelligence is the optimal solution. Request a demo to see AllazoHealth’s AI technology in action.