Practical Solutions for Population Health Analytics

A number of challenges confound the use of administrative health data to identify and prioritize those who are at the greatest risk of poor health outcomes. Central challenges include the timeliness, quality, and utility of claims and other administrative health data. Additionally, many who work with available health data resources report that they are swimming in too much information, and their inability to translate it into useful analysis leads them to a sense of drowning.

A key issue in health data analytics is the inability to extract and translate actionable information for care coordination. Many systems attempt to construct analytic platforms that are so detailed and complex that the result generated have limited end-user utility. Additionally, most health analytic systems fail to adequately account for the influences of behavioral health and social determinants in their design.

Based on this health data conundrum, the central question is: what can and should be done? One approach, as adopted by InfoMC, has been to address the process of health data analytics by focusing the resolution of the lens to identify a few key and actionable items that have practical utility. This includes using readily available sources of cost; utilization; quality of care; and adverse outcomes data among both physical and behavioral health experience, and integrating them with social determinant health factors. In all cases, the true test of population health tools for the identification, stratification, and outcomes analytics is the extent to which they are guided by three central principles. These include: 1) use simple and readily available population data such as claims and other administrative sources; 2) stratification and analytics tools must be designed to have maximum practical utility for all end users including care coordinators; and, 3) the most important principle of all, these tools must be person-centered and focused on improving the health and well-being of individuals.

It is time to migrate away from population health tools and resources that have limited practical utility and value. The journey to improve population health outcomes begins with identifying the key factors that influence an individual’s engagement with health services, their activation for improved health behaviors, and supports for long term well-being. This must also include the three central tenants of physical, behavioral, and social health.