Why Population Health Management Matters For Large Employers

Better health outcomes and lower costs are also the two main goals of value-based care, which pays providers based on the quality rather than quantity of services they deliver. Successful population health management drives value-based care. Here’s how.

Providing Proactive Whole-Person Care And Benefits

The concept of population health is closely tied to employee health and wellness. For example, many employers now offer personalized wellness programs that create meaningful connections in support of employees' total person care.

Employers and employees both benefit from these health and wellness programs. The programs improve employee productivity and retention. Healthier employees can better focus on their work, are less likely to be absent, and more likely to stay at a company where they feel supported and valued.

Wellness solutions, whether offered through a program or through health benefits, can save money for employers by focusing on preventing and managing chronic illnesses and addressing mental health. An employee with a complex chronic condition and mental illness could cost employers 1.5 times more per year than someone with a chronic condition alone and 12 times more per year than a healthy employee, according to PwC.

Population health takes these health and wellness programs to the next level to target specific groups. One way is through the use of digital tools, which make it easier and more affordable for employees to have access to the care and support they need. Another way to make an impact on specific groups is through personalization. Empire’s Total Health, Total You program is an example of a personalized advocacy solution that helps lower overall medical costs, especially for high-cost chronic conditions.

Using Data To Improve Outcomes And Control Costs

Data analytics is key to the success of population health efforts. Understanding the needs of each population means analyzing data from electronic health records, pharmacies, labs, insurance claims, health information exchanges, fitness trackers, devices that collect biometric data, and other sources.

Providers and health plans use predictive data analytics to group individuals based on shared traits, such as health conditions, social drivers of health, and other categories. This grouping is called risk stratification, a way to predict their health risks, who needs what care, and when.

Risk stratification can drastically improve employee well-being when paired with digital solutions that help members navigate the health system to find the right care at the right time. Risk stratification is a process that providers and health plans should continue to do regularly as they gather new data, particularly data showing that the needs or traits of the workforce have changed.

How Employee Wellness Programs Can Impact Population Health

Individuals spend the majority of their waking hours working. It makes sense, therefore, that the workplace health models employers design play a critical role in supporting employees' holistic health.

Wellness programs and interventions that target specific groups with the same health conditions tend to be particularly effective. For example, the Centers for Disease Control and Prevention provides a variety of resources on how employers can create population health management programs for individuals with diabetes. Similar interventions can be equally effective for employee populations with asthma, depression, hypertension, and other chronic conditions.

The success of population health management efforts involves a combination of data analysis, risk stratification, and, most importantly, engagement. To achieve this, employers should choose health plans that actively support population health management with a full set of tools. This includes connecting with in-network health systems that perform risk stratification and use sophisticated tools to assess population health. Lastly, it means connecting with your employees to make care simpler to access and easier to understand.