Hope partnered with dātma BASE (previously ODA) in their research focused on preterm births.

In partnership with dātma.BASE, the UCSF’s Hope Consortium interrogated data across its pipeline of investigations – from EHR, to survey data, to multiple “omic” data (metaboloic, genetic).

UCSF’s Hope Consortium conducted a study on the causes of premature birth for a demographic it serves. The scope of the study entailed storing, managing, and analyzing data from pregnant women, including surveys, social determinants, Fitbits, clinical charts, biospecimen analyses, and other such data.

Enter dātma.BASE: set up on a local cloud, our platform managed both structured and unstructured data for the study. Data also came from several “omics,” all which seamlessly worked with the framework.

dātma.BASE offered several analysis pipelines: clustering, prediction, and causal analysis. Not only did the platform leverage the data to make predictions, but it also sifted through data to examine potentially causal pathways.

In partnership with dātma.BASE, the study generated data that will be used to create data-driven preventive care pathways and dashboards that will improve care for women. Ultimately, the partnership allowed the study to provide population health data insights that will enable scalable prenatal personalized care.