Artificial intelligence (AI) has the power to dramatically transform healthcare – and in many ways, it already has. Its use in patient support programs is just one example of how this advanced technology can encourage healthy behaviors, adherence to prescribed medications, and proactive self-management, all with the ultimate goal of improving patient outcomes.
How is AI-enabled patient engagement reshaping medication adherence programs? We’ll fill you in:
Evolving views on patient engagement
It’s a common belief among healthcare stakeholders that in order to successfully promote engagement, they have to reach out to as many patients – and glean as much data from them – as possible to be effective.
What we’re learning more and more is that this is not only inefficient, but also ineffective. Every healthcare consumer is unique, and taking a cookie-cutter segmentation approach to patient engagement is no more than a shot in the dark.
Fortunately, advancements in AI technologies are changing how these stakeholders think about engaging with patients. Rather than over communicating with patients through uncoordinated phone calls, emails, and SMS texts, pharmaceutical and healthcare organizations can now focus on proactively targeting patients that need support most and personalizing their outreach for the best result.
Targeting the right patients at the right time
By leveraging large datasets from a number of different sources (including medical claims data, consumer behavior data, social determinants of health, and historical program data), we can now predict which patients are at risk of non-adherence or gaps in therapy. On top of that, AI can also help determine which of those high-risk patients are most likely to benefit from, and be positively influenced by, an intervention.
AI enables healthcare organizations to make smarter, more strategic decisions around patient engagement by targeting patients with the greatest likelihood of changing their behaviors. Using data-driven insights, healthcare organizations can prioritize patient outreach, fine-tune omni-channel campaigns, and determine the frequency and timing of said communications.
Personalizing interventions for better outcomes
From there, AI learns and accurately predicts which intervention is best to effectively influence a patient’s behavior. Although in-person and phone interventions were once the norm, now healthcare organizations are embracing omni-channel patient engagement strategies that include text messaging, email, web chat, direct messaging, video, telehealth visits, in-person visits, and phone calls.
Personalizing patient interventions with custom-tailored interactions allows organizations to determine who will benefit more from higher-touch intervention methods, such as phone calls with a nurse, or more cost-effective channels, like text messages or apps. However, personalized outreach not only requires using omni-channel technologies to engage patients, but also determining the right messaging strategy.
When you deliver personalized engagements to the right patients via the right channels at the right time, getting the messaging spot-on is essential. AI can help with that too.
Pulling from the same varied datasets used to make predictions, AI empowers healthcare organizations to figure out not only who to engage with, where to interact, and when to reach out, but also what to say to compel patients to take a more active role in their own care.
As a result, healthcare and pharmaceutical companies can deliver the most effective engagement possible – and it’s all thanks to AI. Interested in learning how AllazoHealth’s AI technology can promote better patient engagement, improve the effectiveness of support programs, and boost health outcomes for your patients? Request a live demo to see it in action.
