Traditional methods of defining and measuring health status rely heavily on epidemiological data, with an emphasis on mortality rates. Over time, this approach has become less meaningful as health conditions have changed and the underlying causes of health problems have been altered. The “man on the street” views health status in terms of factors that affect everyday life. The social determinants of health (SDoH) are currently recognized as major contributors to health status. HPR has been actively involved in efforts to develop a more meaningful measure of health status that is closely aligned with the perspectives driving the population health movement.

HPR announces Life Circumstances Intelligence Version 3.0, a population health assessment that combines demographic, socioeconomic and psychographic data of individual consumers and households into “clusters” to generate more comprehensive and revealing health profiles. LCI Version 3.0 enables healthcare providers, health plans and employers to thoughtfully target users for the most appropriate interventions and communications. Life circumstances, including social determinants, for most consumers are important drivers of healthcare outcomes. Download the Life Circumstances Intelligence white paper on the Resources page.

Social conditions that impact communities negatively at the neighborhood level often become social determinants of health (SDoH). Poverty, housing instability, food insecurity, elevated crime rates, toxic-waste and environmental challenges influence the health status and behavior of both individuals and population groups. There is widespread recognition of the reality that SDoH influences population health status. HPR has worked with Life Circumstances Intelligence (LCI), including SDoH factors, for a number of years. The LCI model is able to deliver these metrics at individual and neighborhood levels to inform population health initiatives.

An understanding of the life circumstances and social determinants of health for individuals, households and population groups that are likely to experience chronic disease diagnoses and higher levels of healthcare service utilization can improve the prospect of engaging at-risk population members with timely and effective interventions. Engaging at-risk population members in health behaviors that will minimize disruptive and costly health events is a highly important issue for healthcare sponsors utilizing the LCI model Version 3.0. Download the MAP Case Study on the Resources page.