Addressing Social Determinants of Health Using Google Maps and Machine Learning

By all means, health systems should do everything possible to give patients the best possible medical care. But let’s take a step back.

The largest contributors to premature death, accounting for a full 40%, are the patient’s own behaviors. Another 15% are their social circumstances. Add in genetic predispositions and environmental exposure. Now you’re up to 90% of what contributes to a person’s premature demise. What’s left? Only 10%. And that is where medical care fits in1.

It’s not just premature death that matters, though. The healthcare system measures health in other resource use, including hospital days, ER visits, outpatient visits and prescriptions, to name a few. And of course, quality of life and a person’s productivity are impacted by health and affect society as a whole.

Addressing the Social Determinants of Health

For too long, the healthcare industry had a myopic view of its role in patient health, focusing exclusively on that 10%: medical care. Fortunately, many in the health sector are gradually realizing that by expanding their scope to address the remaining 90%, referred to as the social determinants of health (SDOH), they strengthen the patient’s health.

The World Health Organization defines SDOH as “the conditions in which people are born, grow, live, work and age2.” That’s a broad swath to cover, and no one says that a healthcare organization should accept responsibility for all SDOH. However, it’s actually in a provider or payer’s financial interests to at least address some of them.

More than 80% of health plans are integrating SDOH into their member programs, according to a 2017 survey from Change Healthcare and the HealthCare Executive Group3. Even some state Medicaid programs are mandating SDOH screenings, community referrals and follow-ups, understanding that health is impacted when a person’s foundational social needs aren’t addressed[iv]. Health plans and state programs are targeting SDOH factors like access to transportation for health care visits, affordable housing, nutritional food, and water quality.

A study published in Health Affairs found that states with a higher level of social spending compared to health spending had better outcomes for key health metrics, including asthma, type 2 diabetes, obesity, lung cancer mortality rates, acute myocardial infarction, and others4.

SDOH Helps the Shift From Volume to Value

As the healthcare paradigm shifts from volume to value, it’s increasingly important to address SDOH. Traditional payment models don’t usually reimburse for them, and providers are ill-equipped to formulate a response plan to address them. It’s hard enough to see patients and track everything on the electronic medical records without also trying to determine if someone has enough food to eat and then helping them get it. We’ve heard from providers that they are spread too thin already, and that general programs don’t work to meet the needs of their diverse population.

Innovative providers and payers are forging their own pathways, with pilot projects and new initiatives. Healthcare infrastructure is slowly changing to accommodate these models, with payments focusing more on value and outcomes than fee-for-service. But even if a small pilot project proves to be successful, rolling it out to a larger population is another story. Healthcare providers need a solution that can achieve the following:

  • Scalable: This systemic challenge requires a coalition of complementary partners to leverage a uniform platform to share real-time insights.
  • Simplicity: Any solution must be simple enough so it won’t contribute to physician burnout or increase stress for the already limited numbers of social workers, nurses or healthcare extenders on staff.
  • Sustainable: As behavior change is 40% of the equation in affecting patient lives, this solution requires continuity along a patient’s journey.

Maven Wave’s Solution

Maven Wave developed an Assess, Personalize, Respond (APR) solution to rapidly address these challenges for healthcare providers. The combined solution leverages Google Cloud for maps and machine learning (ML), along with Maven Wave’s behavioral management methodology. The combination can help providers advance their SDOH strategy.

The APR solution includes:

  1. Assess: Analyzing key social determinants with heat maps. Overlaying clusters with patient populations. Predicting challenges via proprietary ML models. This helps isolate those geospatial gaps in care and support.
  2. Personalize: Segmenting patients into practical cohorts. This includes stratifying neighborhoods with persona grids and providing personalized behavioral responses with care plans. Helping one patient at a time is a lot of work, but by providing each patient what they need to succeed, there’s an increased likelihood of success. Separating patients into cohorts based on their needs is one way to personalize responses while still keeping it practical for the healthcare providers.
  3. Respond: Calibrating responses in real time, based on behavior. Aligning resources, e.g. transportation, social workers, and food banks, so healthcare providers can give individualized options.

If you are interested in learning more about how Maven Wave’s solution can help your organization, please join our healthcare consulting team at HIMSS on Wednesday, February 13 at the Lobby E Market Debut Theater, between 11:15 – 11:35 a.m. If you’re not attending HIMSS, please contact us to schedule a separate demonstration.


About the Author

Kylie McKee
Kylie McKee is a Content Marketing Strategist at Maven Wave with more than eight years of tech industry experience and five years of content marketing experience. Prior to joining the Maven Wave team, Kylie worked as a Content Marketing Specialist for WebPT, Inc. and earned an Associate in Applied Science in Motion Picture, Television, and New Media Production with a CCL in Screenwriting from Scottsdale Community College.
February 12th, 2019

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