Faced with perpetually rising health care and pharmacy costs, challenges in retaining and attracting employees, and now a surge in inflation, today's business owners, benefits advisors and HR managers find themselves operating with little margin for error. These challenges create a difficult dynamic: To attract top talent, businesses must offer a total rewards program that is demonstrably valuable to employees, and to keep businesses running, they must design and implement these programs in a manner that is purposeful, efficient and effective.

Data analytics provides the needed insight into benefits performance plan metrics, enabling empowered decision making to reduce pharmacy and medical costs while also enhancing the health and wellness of the workforce. Through analytics, businesses can not only predict the future health and wellness needs of their workforce but also develop timely interventions to maximize savings and health outcomes.

The population health approach

To truly move the needle on benefits spend, businesses and their advisors need to adopt a population health approach that addresses cost, impact and experience of care. Through data-driven risk-stratification, businesses can identify and group employees based on common traits, including medical history, vital statistics and the potential for developing chronic conditions, and then develop meaningful health and wellness programs to target the needs of these various groups. Over time, employers will not only save money on health care costs, but also benefit from an engaged workforce that's more productive and likely to stay with the organization.

In addition to improving the health of populations within the workforce, analytics help employers and benefits advisors determine how best to allocate their health care spend. According to data from Vital Incite, waste ¾ use of services that do not advance the health of the individual ¾ accounts for least 35% of medical plan spending in the U.S. A deep dive into claims data can reveal the sources of waste, as well as identify ways to redirect the spending to achieve better health and financial outcomes. The following examples reveal how analytics can identify the needs of the employee population, access current spending and the efficacy of care, and pinpoint solutions to improve access to services that ultimately enhance health outcomes.

Empowered decision making

Many businesses are experiencing higher spending on cancer care even though cancer rates have not increased among their employee population. Common reasons for this uptick in spending include an increase in use of more expensive medications and later-stage diagnoses. Businesses can counter these cost drivers by promoting and incentivizing cancer screenings, and by providing genetic testing to determine the efficacy of the high-cost treatment. In some instances, testing may direct care toward a treatment plan that is both less expensive and a better, more effective option for the patient.