Data science – at the intersection of revolutionary medicine and technology – is transforming healthcare. BlueGranite’s team is at the forefront of this innovation. Collaborating with a noted pediatric neurosurgeon, whose expertise spans hydrocephalus, congenital disorders, cranial tumors, and epilepsy in children, our data scientists designed a machine learning analysis model to predict intracranial pressure spikes far enough in advance to allow time-critical therapeutic intervention.
BlueGranite worked with one of the top U.S. children’s healthcare organizations, and the affiliated pediatric neurosurgeon, to design and implement the brain pressure prediction model. The hospital system, with 638 beds, three hospitals, and almost 30 neighborhood locations, had a prediction prototype in place, but it only looked at data 15 minutes out, and there were issues with operationalizing the model.
Our team was able to build out a model that analyzes real-time patient metrics – continuous intracranial pressure, vitals, and medications over two hours – to predict, with extreme accuracy, intracranial pressure surges in children, 30 minutes, and up to an hour, in advance.
We used Apache Kafka to process streaming patient data through an Azure Databricks API we built, trained, and deployed. The successful, real-time solution is turning reactive therapy into proactive therapy. It’s also opening the door to future care improvements and deeper study.
