FLAACOs 2021: Maximizing health engagement with a data-fueled… | MOBE

FLAACOs 2021: Maximizing health engagement with a data-fueled approach.

By: Travis Hoyt, Chief Analytics Officer

Technology-powered data science is paramount to the future of patient engagement, and at Florida Association of Accountable Care Organizations (FLAACOs) this year, technology innovation was top of mind for ACO leaders, health care professionals, and public and private payers alike. And it’s no surprise—after all, the pandemic has shed light on long-standing realities of how patients engage (or don’t) with the health support they may not even know they need.

If we assume people want to improve their health and would be open to connecting with health professionals to do so, what’s stopping them? Together with colleagues Evan Carter of Audacious Inquiry, and Andrew Chang of Aledade, I had the privilege of exploring this topic during a panel discussion titled “Patient Engagement: The Ultimate ‘Magic Bullet’.”

Barriers to engagement

When we talk about “engagement,” it’s important to consider how that term might mean something different for every patient. Social determinants of health (SDOH—the conditions in which people are born, grow, live, work and age—cannot be ignored, and are often huge barriers to engagement and access. At MOBE, 56% of the population that we work with is considered “high risk” for health concerns due to at least one of these factors. Nearly a quarter—24%—of our population struggles with health literacy.

For some, “engagement” could mean scheduling a yearly check-up and following through with their doctor’s advice—for others, it could mean connecting with a health and wellness professional to guide them through their health care journey. From wearables to remote sensors to telehealth, technology is increasing individuals’ ability to engage in their own health—and underpinning it all are two key elements: data and access.

Data science: the gamechanger

Our data show the MOBE participant population is more likely to engage with our offering when social risk factors are present. Loneliness in particular was the strongest factor that predicted when engagement would be high. And that means for those individuals most in need of health support, providers and employers must take additional steps to ensure they’re aware of and have access to the resources they need.

Earlier this year MOBE commissioned The 2021 Workplace Wellness Action Index, conducted by YouGov and Harris Poll. We surveyed 201 HR decision-makers at companies with 5,000+ employees and self-insured/self-funded health coverage and 2,572 consumers across the country.

The findings told us that workers are struggling with the same basic health needs—exercise, nutrition, and sleep—year after year, and 75% reported facing health challenges outside of work. Additionally, 44% of respondents with mental health concerns did not visit or call a mental health specialist during the past year, despite most (77%) reporting access to a mental health benefit.

Respondents also craved more information and better personalized support—and to meet that need, we must harness the power of data science and machine learning to take health risk factors into account, to help us identify who needs support the most, and predict the next step.

Social determinants of health are a huge part of this equation, but of course, can’t predict every health need alone. Collaboration between providers and payers to evaluate patient data—with privacy continuing to be critical—is essential to inform who we should be engaging with and when.

As we look to the future and seek to address the barriers to access that are common across the health system, it’s critical that we use the technology at our fingertips to identify these risk factors and address them head-on.

Data science is certainly a secret ingredient, but the full recipe also must include a one-to-one personalized approach, to engage and support participants on their path to better health. It’s time for us to take this newfound focus on technology and set our sights on what’s next: adding it to the big picture to improve the health care system for everyone.