Innovative Data Mining and Analytics: Population Health 2.0

Many community health centers have access to a plethora of data that are not fully utilized and analyzed. In collaboration with the University of California at Irvine (UCI) Division of Hematology, we sought to take a closer look at two rare blood disordersthrombocytosis and erythrocytosis. The initial screening for these disorders can be easily noted from a CBC with evidence of an elevated platelet count or hemoglobin level. We sought to run a data mining pilot project to delineate how many of our patients could potentially have these rare blood disorders.

In our initial data filter, there were about 100 patients who had elevated levels of platelets which will need further investigation. The researcher and hematologist/oncologist at UCI will also address our providers on this topic and our future research collaboration, as approximately 20 percent of these patients may also have an associated co-morbid inflammatory bowel disease and would benefit from genetic testing.

This pilot project will demonstrate how partnerships between community health centers and major university research institutions can function in the future models of population health and data analytics/mining.

• Explain the advanced role of Population Health 2.0.
• Identify the steps involved in undergoing a data analytic approach (presented by an informatics health specialist).
• Elaborate on how to collaborate with major university research organizations.