Background

Population Health models have become an increasingly valuable approach for understanding how individual health outcome are related to individual care, the overall healthcare system and the social, economic, and environmental context within which individual and population health outcomes evolve. Population Health is a “conceptual framework for thinking about why some populations are healthier than others” which lends itself to the study of lifecourse transitions that lead to cognitive change such as Alzheimer's and other dementias.

Methods

This presentation will review emerging opportunities to incorporate cognitive change in later life within a Population Health framework. Working within the generalized framework as described in Figure 1, the presentation describes available databases within each information vector that can be used to measure cognitive change across time and be incorporated into Population Health models. The presentation will also discuss new tools emerging from the NACDA Program on Aging at the University of Michigan that will allow researchers to link confidential EHRs to contextual data, which provides insight on community and environmental impacts on the risk of cognitive health concerns.

Results

The presentation shows that the Population Health framework is a very useful model to employ when describing cognitive change across individuals and population groups. While barriers do exist in terms of access to confidential and individual level health records, new approaches will allow researchers to incorporate contextual resources into health outcomes analysis of cognitive change in treatment.

Conclusions

The use of Population Health models are becoming more common research framework across health research disciplines. The routine incorporation of this framework into the study of cognitive change will greatly enhance our understanding of this phenomenon at both the individual and population level.