An article in Health Affairs asks how to measure and understand the distribution of health metrics across a population.
The authors conclude with these implications for policymakers:
“There exists a clear consensus among healthcare experts around the need for population segmentation in order to measure population health and health equity. However, there is no single way to do this. {T}en population segmentation approaches were considered important by the panel. These results highlight the value of considering the wide range of different population groups that may influence health outcomes.
“The results of this study can help researchers and policymakers prioritize the way they analyze and present population health data. In addition, these results should guide the collection of data. For example, the panel considered socioeconomic status and risk factors to be very important, but administrative datasets collect information on these issues in different ways and according to different definitions. Standardizing the collection of segmentation variables would allow population-wide analysis of the distribution of health.
“Policymakers should also consider using a data-driven approach to identify population segments, rather than a priori defined population groups. Big data and data mining techniques can help quantify the distribution of outcomes in a population and identify the factors driving these differences.”
To read the piece, please hit this link.