Using Big Data Analytics to Improve Population Health Management
A Case Study on COVID-19 Vaccine Distribution and Tips for Getting More from Your Data
From RS21 Health Lab, with contributor Stefany Goradia
Big data analytics are becoming increasingly important in improving population health and health equity.
But while there is more data at our fingertips now than ever before, many decision makers still feel utterly starved for insights.
We need more from our data.
Big Data Initiatives to Close Gaps in Care and Optimize Access to Public Health Services
More data means more opportunity to create a better view of patient and population health. Many organizations have already found success using big data to improve surveillance or signal detection, predict future risk and needs, and inform precision public health strategies.
New technologies and methods are emerging rapidly, and we already have quite a few capabilities to help close gaps in care and improve public health services.
A Case Study
To disrupt typical approaches and get better insights for precision strategies and targeted public health outreach, RS21 partnered with the Wellness & Equity Alliance (WEA), a national organization of public health clinicians, on a pilot study funded by the Centers for Disease Control and Prevention (CDC).
The study focused on improving COVID-19 vaccine distribution among asylum seekers and historically marginalized communities along the U.S. border.
Dig Deeper
White House Summit on COVID-19 Equity and What Works Showcase, Dr. Madison of Wellness & Equity Alliance discusses strategies for disruptive public health services.
Nearly 2 million people live in unincorporated, substandard housing developments known as Colonias, and Texas has one of the largest concentrations of poverty in the U.S. with an estimated 500,000 people living in 2,294 colonias.
To reach these communities efficiently and effectively with limited resources, we used a site selection technique to strategically determine where to place “pop-up” mobile vaccination clinics. Blending over 90 social determinants of health (SDoH) indicators, we narrowed in on two neighborhoods in Laredo, TX.
At first glance, the entire region along the border of Laredo appears to be comprised of equally “high risk” neighborhoods. Further analysis, however, began to reveal significant differences.
- A neighborhood in the north was closer to the border crossing, had poorer health overall, and tended to have an older age demographic.
- A neighborhood to the south was closer to the Colonias where many asylum seekers live, had slightly better health on average, and greater social vulnerabilities (e.g., crime, poverty, access to care).
Based on the specific characteristics WEA and the CDC were targeting, we zeroed in on the southern neighborhood that had a larger population of migrants.
RS21 then used location data and GIS analysis to understand typical travel patterns, areas of interest, and traffic density based on day and time.
From this, we were able to recommend 3 specific locations to deploy the pop-up clinics, down to the street corner and time of day.
“COVID-19 amplified the inequities in the health system that have existed for decades and predated on vulnerable public health systems that intended to protect the most marginalized communities in the U.S.
“After administering over 2 million COVID-19 vaccines in 10 states with a focus on communities lacking historical health care access, we believe that the private-public partnership is the future of public health,” said Tyler B. Evans, CEO and Co-Founder of the Wellness & Equity Alliance.
Getting More From Your Data
The project undertaken by RS21 and WEA in Laredo, TX is a great example of how big data analytics and data technologies can help improve public health services.
So how can you replicate approaches to get more from your data?
1. It starts with curated data that is easy to exchange, ingest, and use.
Starting with curated data sets — like RS21’s community risk factors, social determinants of health, cellphone, and GIS data used in the “pop-up” clinic example in Laredo — takes out 80% of the challenge of data analysis.
Having the data in an accessible, standardized format allows you to move much faster. You can begin to get insights in days or weeks rather than months or years.
But it’s not enough to just have the curated data.
2. The data must be unique, usable, and novel.
Novel data integrated with your standard data sets reveals new insights because the data has never existed together before.
One of the things we’ve been working on at RS21 is using aggregated location data to understand how and where people move through their communities.
This kind of anonymized data can be paired with other data sets, as described in the “pop-up” clinic example, to support efforts such as:
- Discovering when and where to reach the most people for improved public health outreach.
- Determining how far people have to travel for important amenities, like healthcare and food.
- Identifying travel patterns that indicate where congestion could bottleneck or impede emergency evacuations or responses.
3. Use data science to extract more insight.
Data scientists are in high demand because they can apply techniques that provide extremely valuable insights that typical analysis can’t deliver.
One thing RS21 data scientists have pioneered is a way to estimate and predict data very precisely, even more granularly than the census block, using a small area estimation technique.
RS21 used this technique to build an online application for Humana, where we extrapolated over 90 different social determinants of health (SDOH) data sets and calculated how they uniquely interact down to the neighborhood level. This helped Humana understand the conditions and risks of people living in different neighborhoods to guide treatment plans and support referrals.
Data science models and methods help us predict, visualize, and tap into new potential from the data we have at our fingertips. Even if you don’t have a data science team in-house, there are companies like ours that can provide the expertise to support your team.
Overall, big data analytics has the potential to revolutionize the delivery of public health services by enabling healthcare providers to deploy targeted interventions and address health disparities more effectively.
About RS21
RS21 is a data science company that uses artificial intelligence, data engineering, design, and modern software development methods to empower organizations to make data-driven decisions that positively impact the world.
We believe we reach our full potential only as we come together as our authentic selves. Dissimilar perspectives, diverse experiences, and different backgrounds strengthen our team, our ideas, and our work. At RS21, we seek out dreamers who will share fresh viewpoints and challenge our status quo.
RS21 is an Inc. 5000 fastest-growing company and a Fast Company Best Workplace for Innovators.
