Big data and population health management: Improving outcomes, decreasing costs

June 27, 2016 conduentblogs

(Editor’s note: An earlier version of this post was published in HR Insights.)

Big data – collections of large, complex sets of numbers – is one of the most promising business trends of the decade. Few industries have not jumped on the big data band wagon. And rightfully so. Understanding data can be powerful. Employers who provide their employees and their families with health care have known the power of data to help manage costs long before it became trendy.

Population health management uses a data-driven approach to identify and stratify health plan populations according to health risk. With such data, appropriate strategies are developed to proactively address the levels of risk within the population with a goal of improving population health as well as decreasing costs.

"Identifying opportunities to decrease these risks through data analysis is the first step in better managing your population’s health and your health care costs." Patricia Curran, RN, Health and Wellness Consultant
“Identifying opportunities to decrease these risks through data analysis is the first step in better managing your population’s health and your health care costs.” Patricia Curran, RN, Health and Wellness Consultant

As a registered nurse and a principal in our National Clinical Practice, I’ve seen inappropriate health care utilization patterns, non-compliance to treatment plans, and poor lifestyle choices within a population lead to significant and frequently avoidable complications.

These trends often result in poor clinical outcomes and can be costly. Identifying opportunities to decrease these risks through data analysis is the first step in better managing your population’s health and your health care costs.

When analyzing claims data for an employee population, analysts can identify opportunities for “risk reduction ” and improved outcomes. “Early stage” health conditions (e.g., hypertension, high cholesterol, obesity) can escalate to more serious, costly conditions because of ineffective treatment, non-compliance or poor lifestyles.

For example, according to the American Heart Association (AHA), approximately 41 million adults in the United States have cholesterol levels that place them at high risk for heart disease. An additional 61 million are borderline high risk. AHA advises that a 10% decrease in total cholesterol levels may result in a 30% reduction in heart disease, yet in the claims data analyzed by Buck for one population, 91% of claimants with hyperlipidemia had inadequate medical follow-up during the 12-month interval being examined.

Under such a scenario, there are numerous opportunities for improvement. Health plan sponsors need to understand the risk profile of their health plan members. In general, a small minority of health plan members generate disproportionate health care costs and a majority of healthy ones account for a commensurately small share.

Through data analysis, a population can be divided into four distinct segments based on health risks:

  • Low risk – Approximately 60-70% of the population that are generally healthy.
  • Moderate risk – About 20-25% of the population that are medically stable and generally compliant with treatment plans.
  • Chronic risk – About 5-10% of the population. These members are less stable, often non-compliant with more serious, less controlled conditions and complications.
  • Acute risk – About 1-3% of the population that is unstable, with high utilization, more serious disease, frequent emergency room and hospital admissions and multiple complications.

For effective population health management, plan sponsors should implement health management initiatives for each risk level with the goal of empowering members and improving their health care experiences and outcomes. Initiatives such as health risk appraisals, predictive modeling, lifestyle coaching, disease management, utilization and case management, fitness classes and other programs that emphasize education, self-care, and compliance with evidence-based treatment protocols can be used to improve health outcomes while reducing risks and costs. In developing a population health management strategy, employers should view gaps in care, non-compliance and poor utilization patterns as opportunities for improvement.

An effective population health management strategy can slow down or stop the progression of some individuals’ risk escalation, decrease other members’ risks as their compliance and medical stability improve and, most importantly, improve clinical outcomes and reduce health care costs.

About the Author

Biography

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