Powering Better Health Care: Data Analytics at Independence Blue Cross

Two people look over data visualizations on a tablet

You have probably seen the term “data analytics,” but if you don’t work in this field, you may not be sure what it means or how it works.

So, what exactly is data analytics, and how do health insurance companies like Independence Blue Cross (Independence) use it to make informed and innovative decisions to power better health care?

You Can’t Manage What You Can’t Measure

The simplest definition of data analytics is the science of identifying patterns in data and gaining insights from that data. One of our main objectives in using data analytics is to enable our company leaders and stakeholders to make evidence-based decisions that are transparent, verifiable, and robust.

This involves using techniques, tools, and systems that help:

Identify and clarify patterns in data
Identify trends and changes
Validate the next best action to achieve desired change

Simply put, you can’t manage what you can’t measure, but with robust data, analysis, and metrics, it becomes easier to make the most informed decisions.

Redefining Health Care Delivery

These decisions are helping us advance our company’s mission to improve the health of the community.

“Independence has a long history of serving our community, and we’re committed to creating a better health care system for all,” says Mike Vennera, senior vice president and chief information officer at Independence.

Data analysis plays an increasingly important role in how Independence is helping to redefine health care delivery to improve our nation’s health care system. It influences how quality-based decisions are being made at various levels to ensure that care is equitable, effective, affordable, and simple.

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With insights from reports, dashboards, trends, benchmarks, and descriptive analysis, we can use what we’ve learned from the past to plan for the future. Taking this a step further, we can use this information to answer questions about trends that influence health outcomes and health equity.

We can also use techniques like predictive modeling, which can highlight relationships between events and issues and can help anticipate future outcomes and occurrences.

For example, we can create models to predict future hospitalizations and readmissions, the onset of diabetes, and the likelihood of high-risk pregnancies ― issues that affect communities of color at a higher rate ― to make more informed decisions to help reduce racial health disparities and improve health outcomes.

A Mix of Talent, Technology, and Methodology

Advanced analytics have the potential for use in many different realms of health care. These range from clinical and operations research to clinical decision support, population health management, fraud prevention, and evaluating the effectiveness of specific programs.

For an organization like Independence to benefit from analytics as part of its mission to improve health care delivery, it must have the right resources, which include talent, technology, and analytics methodology.

It is also important to continually adapt processes to accommodate new information and improve decision-making. Analytics should be considered a continual improvement process and not a one-time event. At Independence, this means ongoing collaboration and engagement with providers, customers, and members to drive change that promotes equitable, whole-person health.

Breaking Down Barriers to Achieve Health Equity

Health care analytics is an exciting field, and there are a lot of topics to cover. Over the next few months, we’ll explore how data informs the work we do at Independence.

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We’ll take a more in-depth look at topics such as risk stratification, customer and provider reporting, advanced analytics, how to detect bias in algorithms, and how we use data to break down barriers to address racial health disparities to achieve health equity.