To understand health at a community level, subpopulations must be analyzed through use of granular data and powerful health technology, according to a study at the American Journal of Preventative Medicine.
The study, co-authored by College of Health and Human Services faculty at the University of North Carolina Charlotte, examined morality data from Florida for a new approach to subpopulation analytics.
The researchers used a data warehouse to stage "multiple sources of event level data" combined with an analytic processing interface and customized algorithms to look at specific populations that have high levels of a health issue. They were able to use this model to define subpopulations in Orange County, Florida, as well as cause of death, racial disparities and other factors.
"The advantage comes from warehousing individual data rather than relying on aggregates," study co-author James Studnicki, the Irwin Belk Endowed Chair of Health Services Research and Professor, said in an announcement. When deployed on a national scale, the study's findings will be a major step forward in public health, he said.
"Existing sources of publicly available granular de-identified data and powerful information technology enable hundreds of millions of subpopulations to be defined and analyzed for multiple outcomes, such as deaths, avoidable hospitalizations, inpatient and ambulatory surgical complications, readmissions, newly diagnosed cancers, emergency room visits, and many others," the study's authors said. "Because of the event-level nature of this data, integration with clinical data from electronic health records and other treatment subpopulations is feasible. Subpopulation analytics that is deployed and evolved on a national scale will inform population health improvement in the same way that genomics and metabolomics are informing clinical disease management."
Studnicki added that breaking populations down into smaller groups is necessary for "precision public health" as part of the growth of precision medicine as well as population health management.
To learn more:
- here's the study
- read the announcement