Improve Engagement, Satisfaction and Resource Allocation Using the Social Determinants of Health

July 11, 2017
Jin On, Data Scientist

Healthcare organizations are increasingly on the hook for improving the health of their populations. Every avenue for improving health while controlling costs must be explored and leveraged. One of the most promising avenues is to bring the social determinants of health (SDoH) into the analytical mix.

It’s no secret that where a person grew up, lives, works and ages play a huge role in determining health outcomes. In fact, the Centers for Disease Control report that SDoH are the number one factor in health inequality. Other experts estimate that about 80 percent of the difference in people’s health can be attributed to factors outside of the clinical setting. 

Patient engagement

The challenge is – what can we do with SDoH to meet immediate needs today while taking steps to prepare for the future of increasingly personalized healthcare?  

Right now, mature and innovative health plans apply SDoH data to improving consumer engagement, satisfaction and resource allocation. 

Improve Engagement and Satisfaction

Effectively enrolling and engaging members in the right cost-saving case and disease management programs is a long-standing challenge for healthcare organizations.

Conventionally, health plans employ a resource-intensive strategy toward enrollment and matching members to available programs. First, they identify members for enrollment, then stratify them based on any combination of risk factors, disease severity, comorbidities, utilization and cost. Once stratified, nurses start at the top of the list and outreach their way down while members below a certain threshold get a postcard in the mail.

Today, machine-learning algorithms help health plans better understand each individual member – who they are as people – and what they are most likely to do if presented with the opportunity to participate in a case or disease management program. Because people are irrational, we don’t always do the things we know we should, even when it’s in our best interest. Many seemingly ideal candidates will simply never participate because of who they are as people. At the same time, other people are highly motivated before they hit the outreach threshold – when their risk is rising – but they never get the call to join.

Every day a health plan is not talking to a member who would become engaged is a day lost. Leveraging social determinants of health data enables health plans to prioritize members who are best suited and most likely to engage, thereby ensuring better health outcomes for members and higher returns for the health plan

Improve Resource Allocation

After figuring out whom to engage, the next step is understanding and refining how.

Typical outreach strategies include outbound direct nurse calling, outbound automated calling, physical/digital mailing and digital messaging. Each method varies in its effectiveness, speed and expense. 

Choosing the correct approach for each member increases the likelihood of successful enrollment. We all know people who respond right away via text or email, but never pick up a voice call, while others let digital messages pile up because they prefer to talk. Social determinants of health data help health plans to understand and predict member communication preferences and success rates.

Further, analytics balances preferences against available methods, cost of each method, program effectiveness, and overall budgetary restrictions. In this way, cost-effective and coordinated outreach is directed at the right member in the right way for the right program.

As programs fill up with the right, motivated members, health plans reap improvement in many areas, including:

  • Member satisfaction 
  • Member engagement
  • Program efficacy 
  • Resource efficiency 

Better still, these motivated members reap the intended benefits of learning to better control their medical conditions through coordinated disease and case management programs.

Understanding SDoH are especially important for those members less likely to engage, but whose conditions make participation in a program important. Consider the young father with type one diabetes and three little kids at home. He’s missed a few appointments, his most recent HbA1C result was over 9.3, and his BMI is trending steadily upward. For a variety of reasons, his propensity to engage is low and previous outreach attempts were unsuccessful. However, by using additional social determinant data in its analytical models, the health plan could predict he is more likely to respond positively to digital messages and online resources. This provided clinical teams with crucial information that allowed them to outreach more efficiently and effectively. 

Looking ahead, SDoH will be used in increasingly innovative ways to control costs and improve member health. Get a head start on the future by learning to leverage this data today to allocate resources more effectively while improving member engagement and satisfaction.

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