Population health management (PHM) has emerged as a priority in healthcare in recent years. The shift from volume- to value-based care has prompted  payers to implement PHM strategies to control costs, boost quality performance, and improve patient outcomes. Many payers have even  doubled down on population health programs amid the COVID-19 pandemic.

As payers seek more effective ways to manage patient populations without breaking the bank, artificial intelligence (AI) enters the conversation.  Around half of payers believe that AI and machine learning will drive innovation forward, and PHM is just one example—albeit a critical one—of how these technologies are used today.

With AI at their disposal, payers and other healthcare organizations can leverage  smart data to drive higher engagement, deliver tailored interventions, and build healthier communities. Let’s talk about how and why AI-powered strategies are the right approach for population health management:

Woman working on a computer with smart data icons surrounding her.

Using Data to Inform Population Health Management Strategies

Improving population health management requires payers to have a comprehensive understanding of plan members’ unique health needs—which is where data comes into play. AI technology leverages data from varied, robust datasets to help payers predict patient behaviors and identify high-risk individuals within specific populations.

Commonly used smart data sources include historical engagement data, medical claims data, enrollment data, consumer behaviors, and  social determinants of health (SDOH). Social determinants—or the conditions in which people live and work—have a profound impact on patient outcomes. In fact, research points to SDOH being responsible for more than 80 percent of health outcomes.

Payers can use smart data to understand and proactively address the socioeconomic barriers that lead to gaps in care, such as medication non-adherence or missed health screenings. In addition to identifying high-risk patients, AI can also predict which individuals within specific populations will likely benefit from outreach, enabling smarter, more cost-effective patient targeting.

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Engaging and Empowering Patients with Personalized Interventions

With a data-driven blueprint for their PHM initiatives, payers can use AI to deploy more effective, affordable interventions. The right outreach at the right time can guide patients to make healthier choices, change their behaviors, self-manage conditions, and take a more active role in their care.

The question is: What’s the right type of outreach and optimal timing for each individual? How can payers personalize interventions to increase patient engagement and see better results? AI is the answer—or at least the best way of predicting it.

Using smart data, healthcare payers can take an omnichannel approach, effectively tailoring communications to reach the right patients via their preferred channels. Gone are the days of phone-based interventions being the go-to channel. Instead, payers and other healthcare organizations now use numerous intervention channels, including text messages, emails, chatbots, apps, and more.

That said, it’s not only about getting the targeting and the intervention channel right. The messaging and timing matter as well. Using AI, payers can personalize the content, timing, and cadence of their interventions to have the greatest impact on each patient. 

Optimizing Population Health Management With AI Technology

AI has the power to transform population health management as we know it. With AI technology, payers can deploy personalized, cost-effective interventions, optimize patient support programs, and make a positive impact on health outcomes across patient populations. 

Andrew Renda, associate vice president of population health at Humana, feels smart data is pivotal in advancing the company’s strategy.

“We’ve used a lot of that data to create advanced analytics, like predictive models and natural language processors,” he explained. “That really informs our strategy because it helps us understand number one, what the needs are, but also, how do we prioritize outreach to address needs and those people? So, analytics and data have been really important.”

Humana is just one example of how payers use smart data to optimize their initiatives. Other payers—such as Blue Cross Blue Shield of North Carolina—have also seen exceptional results when using AI to improve the effectiveness of patient interventions. 

Download our case study to learn how Blue Cross Blue Shield of North Carolina achieved a 5.5 times uplift in medication adherence and a 23 percent reduction in intervention spend using AllazoHealth’s AI engine.

Here's how to leverage AI to build a best-in-class patient support program.